Technical Assistance for Strengthening the Statistical Capacity of

Transcription

National Programme for Turkey 2007 under the
Instrument for Pre-Accession Assistance (IPA)
This project is financed by
the European Union
Technical Assistance for Strengthening
the Statistical Capacity of MoNE
FINAL PRACTICAL GUIDELINE
25 June 2012
EUROPEAID/126853/D/SER/TR
MONESTAT - TA for Strengthening the Statistical Capacity of MoNE
Contract No
TR 0702.23-01/001
Contracting Authority
Central Finance and Contracts Unit (CFCU)
Beneficiary / Client
Ministry of National Education
Report Name
Final Practical Guideline
Document Filename
Activity_2.8.1_Final_Practical_Guideline_20120625
Publication Date
25.06.2012
Prepared by
Technical Assistance Team (TAT)
Document History
Revision No
Revision Date
Revision By
Summary of Changes
1.0
25.06.2012
TAT
Initial Release
1|FINAL PRACTICAL GUIDELINE
Table of Contents
ABBREVIATIONS AND ACRONYMS .................................................................................................... 24
EXECUTIVE SUMMARY ...................................................................................................................... 26
Section A.
INTRODUCTION ............................................................................................................. 28
1
CONTENT OF THE PG................................................................................................................. 28
2
PURPOSE AND SCOPE ............................................................................................................... 29
Section B.
1
GENERAL PRESENTATION OF THE UOE DATA COLLECTION ...................................................... 30
1.1
Objectives.......................................................................................................................... 30
1.2
Organisation ...................................................................................................................... 30
1.3
Who is responsible for what at international level? ......................................................... 30
1.4
Reference year, timeline and submission of all UOE questionnaires ............................... 31
1.5
Instruments: UOE questionnaires and guidelines............................................................. 32
1.6
The content of the UOE data collection............................................................................ 33
1.7
Users ................................................................................................................................. 33
1.8
Organisation of the UOE data submissions for Turkey ..................................................... 34
1.8.1
2
THE UOE DATA COLLECTION ......................................................................................... 30
Participants in the UOE data collection in Turkey ........................................................ 35
UOE CONCEPTS IN THE TURKISH CONTEXT .............................................................................. 37
2.1
ISCED classification and implementation in Turkey .......................................................... 37
2.1.1
Division of the tasks in Turkey ...................................................................................... 37
2.1.2
ISCED in the Turkish context: school types ................................................................... 38
2.1.3
Implementation of ISCED in the UOE data ................................................................... 42
2.2
Formal/non-formal education .......................................................................................... 42
2.3
Full Time/Part Time And Full Time Equivalents ................................................................ 46
2.4
Public/private institutions................................................................................................. 46
2.5
Fields of education and training (FOET) ............................................................................ 48
3
COVERAGE OF THE UOE DATA COLLECTION IN TURKEY ........................................................... 49
3.1
The scope of education ..................................................................................................... 49
3.2
Coverage of Early childhood education programmes....................................................... 52
3.3
Coverage of “Special education” ...................................................................................... 52
3.4
Coverage of “adult education” and “continuing education.............................................. 56
3.5
Coverage of vocational and technical education .............................................................. 56
3.6
Coverage of students enrolled in educational institutions organised by Ministries other
than the Ministry of Education ..................................................................................................... 57
3.7
Coverage of foreign and mobile students......................................................................... 58
3.7.1
Distance learning/e-learning involving two countries .................................................. 58
3.7.2
Commuting students..................................................................................................... 59
3.7.3
Foreign campus ............................................................................................................. 59
3.7.4
Exchange programmes.................................................................................................. 60
3.8
Coverage of PERSONNEL DATA ......................................................................................... 60
3.9.
The Coverage of FINANCE DATA ....................................................................................... 61
3.9.1.
Finance data in UOE: overview ..................................................................................... 61
3.9.2.
Data needs in order to obtain UOE reports .................................................................. 64
3.9.3.
Statistical infrastructure and coverage in relation to the UOE data collection ............ 65
3.10. International Standard Classification of Education 2011 (ISCED 2011) ............................... 67
3.10.1
Overview ....................................................................................................................... 67
3.10.2
ISCED 2011: main changes ............................................................................................ 67
3.10.4
Turkish ISCED mapping ................................................................................................. 73
Section C.
1
UOE DATA SUBMISSION IN TURKEY .............................................................................. 81
MAIN RESOURCES OF UOE in TURKEY ...................................................................................... 81
1.1.
Analysed and examined all utilised Statistics Related Reports in MoNE .............................. 81
1.1.1.
Published Statistics ........................................................................................................... 81
1.1.1.1.
Non-Formal Education Statistics ................................................................................... 81
1.1.1.2.
Formal Educatıon Statistics ........................................................................................... 84
1.1.1.3.
Higher Educatıon Statistics (Provided by ÖSYM) .......................................................... 95
1.1.2.
Meis Query Statistics ....................................................................................................... 99
1.1.3.
Oracle Discoverer Statistics (Sample) ............................................................................. 111
1.2.
Reviewing Existing Mone Modules ..................................................................................... 114
1.2.1.
E-School (e-okul) ............................................................................................................. 114
1.2.2.
E-Staff module (Özlük Modülü)....................................................................................... 114
1.2.3.
TEFBIS .............................................................................................................................. 114
1.2.4.
Devlet Kurumları Modülü (E-public) ............................................................................... 114
1.2.5.
Özel Öğretim Kurumları Modulu (E-private - ÖÖK) ........................................................ 115
1.2.6.
E-non formal (Outside MEBBIS Infrastructure) ............................................................... 115
1.2.7.
E-butce (E-budget) (Outside MEBBIS Infrastructure) ..................................................... 115
1.2.8.
Higher education data collection (Outside MEBBIS Infrastructure) ............................... 115
1.2.9.
Education programmes/school under the responsibility of other ministries (outside MEB
direct responsibility) ....................................................................................................................... 116
2
GENERAL PROCEDURES on UOE DATA SUBMISSION PROCESS in TURKEY ............................. 116
General presentation ...................................................................................................................... 117
2.1.
Phase 1: Specify needs ........................................................................................................ 118
2.1.1.
Determine needs for information ................................................................................... 118
2.1.2.
Consult and confirm needs ............................................................................................. 119
2.1.3.
Establish output objectives ............................................................................................. 120
2.1.4.
Identify concepts............................................................................................................. 121
2.1.5.
Check data availability .................................................................................................... 122
2.1.6.
Prepare business case/Documentation .......................................................................... 122
2.2.
Phase 2: Design ................................................................................................................... 123
2.2.1.
Design outputs ................................................................................................................ 124
2.2.2.
Design variable descriptions ........................................................................................... 124
2.2.3.
Design data collection methodology .............................................................................. 125
2.2.4.
Design Statistical processing methodology .................................................................... 126
2.2.5.
2.3.
Design production systems and workflow ...................................................................... 128
Phase 3: Build ...................................................................................................................... 129
2.3.1.
Build data collection instrument..................................................................................... 129
2.3.2.
Build or enhance process component ............................................................................ 130
2.3.3.
Configure workflows ....................................................................................................... 131
2.3.4.
Test production system................................................................................................... 132
2.3.5.
Test Statistical business process ..................................................................................... 132
2.3.6.
Finalise production system ............................................................................................. 132
2.4.
Phase 4: Collect ................................................................................................................... 133
2.4.1.
Set up collection.............................................................................................................. 134
2.4.2.
Run collection.................................................................................................................. 134
2.4.3.
Finalise collection ............................................................................................................ 135
2.5.
Phase 5 – Process ................................................................................................................ 135
2.5.1.
Integrate the data ........................................................................................................... 136
2.5.2.
Classify and code ............................................................................................................. 136
2.5.3.
Review, validate and edit ................................................................................................ 136
2.5.4.
Estimation ....................................................................................................................... 137
2.5.5.
Derive new variables and Statistical units ...................................................................... 137
2.5.6.
Calculate aggregates ....................................................................................................... 138
2.5.7.
Finalise data files ............................................................................................................. 138
2.6.
Phase 6 – Analyse................................................................................................................ 139
2.6.1.
Prepare draft output ....................................................................................................... 139
2.6.2.
Validate output ............................................................................................................... 140
2.6.3.
Scrutinize and explain ..................................................................................................... 141
2.6.4.
Apply disclosure control.................................................................................................. 142
2.6.5.
Finalize outputs ............................................................................................................... 142
2.7.
Phase 7 – Disseminate ........................................................................................................ 143
2.7.1.
Update output system .................................................................................................... 144
2.7.2.
Produce dissemination products .................................................................................... 144
2.7.3.
Manage release of dissemination products .................................................................... 144
2.7.4.
Promote dissemination products.................................................................................... 145
2.7.5.
Manage user support ...................................................................................................... 145
2.8.
Phase 8 – Archive ................................................................................................................ 145
2.8.1.
Define archive rules ........................................................................................................ 146
2.8.2.
Manage archive repository ............................................................................................. 147
2.8.3.
Preserve data and metadata ........................................................................................... 147
2.9.
Phase 9 – Evaluate .............................................................................................................. 148
2.9.1.
Gather evaluation input .................................................................................................. 148
2.9.2.
Conduct evaluation ......................................................................................................... 149
2.9.3.
Agree action plan ............................................................................................................ 150
2.10.
Quality Management and Metadata Management ........................................................ 150
Section D.
1
TECHNICAL PROCEDURES on UOE DATA SUBMISSION PROCESS in TURKEY .............. 152
BUSSINES INTELIGENCE PROCEDURES on UOE DATA SUBMISSION PROCESS........................ 152
1.1.
Statistics Subject Areas ....................................................................................................... 152
1.2.
Statistic Flow, Network and BI Archıtecture ....................................................................... 153
1.3.
BI Workflow ........................................................................................................................ 155
1.4.
ETL Constraınts of Public and prıvate ınstıtutıons .............................................................. 156
1.5.
ETL Contraınts of Formal Educatıon Student Data ............................................................. 162
1.5.1.
Prımary school educatıon level of actıve&passıve students (includes also pre-prımary)
162
1.5.2.
Upper Secondary school educatıon level of actıve&passıve students (includes also preprımary) 166
1.6.
ETL Contraınts of Dısabled Students ................................................................................... 172
1.7.
ETL Contraınts of Open Prımary School Students ............................................................... 173
1.8.
ETL Contraınts of Open Hıgh School Students .................................................................... 174
1.9.
ETL Contraınts of Summer School Pre-prımary Students ................................................... 176
1.10.
ETL Contraınts of Mobıle Pre-prımary Students ............................................................. 177
1.11.
ETL Contraınts of Other Instıtutıons Pre-prımary Students ............................................ 177
1.12.
ETL Contraınts of SHCEK Students .................................................................................. 178
1.13.
ETL Contraınts of Schoolarship Students ........................................................................ 178
1.14.
ETL Contraınts of Boarding Students .............................................................................. 182
1.15.
ETL Contraınts of Private Dormıtorıes ............................................................................ 183
1.16.
ETL Contraınts of Foreign Language for Formal Education ............................................. 184
1.17.
ETL Contraınts of Staff data ............................................................................................ 187
1.18.
ETL Contraınts of Finance data ....................................................................................... 193
1.19.
ETL Contraınts of Combined Institution, Classroom, Division and Teacher Dataset ...... 210
1.20.
Non-Formal Education .................................................................................................... 211
2
DATABASE OBJECTS FOR INTERNAL USAGE ............................................................................ 218
2.1.
Look-Up Tables.................................................................................................................... 218
2.2.
Vıews ................................................................................................................................... 231
2.3.
Materıalızed Vıews .............................................................................................................. 232
3
UOE TRANSFORMATION RULES .............................................................................................. 242
3.1.
Database Tables for UOE .................................................................................................... 242
3.2.
UOE Transformation Rules .................................................................................................. 243
4
BI BUSINESS LAYER DESIGN..................................................................................................... 247
4.1.
Layers In The BI Admınıstratıon Tool .................................................................................. 247
4.2.
Institutions Business Model ................................................................................................ 248
4.3.
Formal educatıon Business Model ...................................................................................... 249
4.4.
Staff Business Model ........................................................................................................... 252
4.5.
Fınance Business Model ...................................................................................................... 253
4.6.
Non-Formal Business Model ............................................................................................... 254
Section E.
USER MANUEL FOR USAGE OF THE BI DASHBOARD ....................................................... 255
1.1.
General Usage of Dashboard .............................................................................................. 255
1.2.
Designed Dashboard Pages ................................................................................................. 259
1.2.1.
INSTITUTIONS DASHBOARD ............................................................................................ 259
1.2.1.1.
THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP TYPES IN LOCATION
HIERARCHY 259
1.2.1.2.
THE NUMBER OF INSTITUTIONS DUE TO THEIR MAIN TYPE / SUB TYPE STATUS AND
CURRENT SITUATIONS IN LOCATION HIERARCHY........................................................................... 261
1.2.1.3.
THE NUMBER OF INSTITUTIONS WITH RESPECT TO INSTITUTION TYPES WITH THE
SELECTION FOR PROVINCES & DISTRICTS ....................................................................................... 262
1.2.1.4.
THE NUMBER OF INSTITUTIONS IN INSTITUTION TYPE HIERARCHY........................... 264
1.2.1.5.
THE NUMBER OF PUBLIC/PRIVATE/OPEN INSTITUTIONS WITH LOCATION HIERARCHY,
NORMAL/TWO BASED EDUCATION ................................................................................................ 266
1.2.1.6.
THE NUMBER OF INSTITUTIONS DUE TO THEIR ENTRANCE TO SERVICE YEARS ........ 268
1.2.1.7.
THE NUMBER OF INSTITUTIONS WHICH HAVE A PREPARATORY CLASS .................... 269
1.2.1.8.
THE NUMBER OF INSTITUTIONS WITH SELECTED PROVINCE AND DISTRICT LEVEL ... 271
1.2.1.9.
THE NUMBER OF CLOSED INSTITUTIONS WITH CLOSURE REASONS .......................... 272
1.2.2.
INSTITUTIONS ADDITIONAL INFORMATIONS DASHBOARD ............................................ 274
1.2.2.1.
THE NUMBER OF INSTITUTIONS &CLASSROOMS IN NUTS LEVEL 2 ........................... 274
1.2.2.2.
THE NUMBER OF INSTITUTIONS & USAGE AREAS IN NUTS HIERARCHY .................... 276
1.2.2.3.
THE NUMBER OF PUBLIC HOUSES IN INSTITUTION TYPE HIERARCHY ........................ 277
1.2.2.4.
THE NUMBER OF PENSIONS IN INSTITUTION TYPE HIERARCHY ................................. 279
1.2.2.5.
THE BUILDING AND GARDEN AREAS IN LOCATION HIERARCHY ................................. 281
1.2.2.6.
THE NUMBER OF LIBRARY MATERIALS IN LOCATION OF RESIDENCE HIERARCHY ..... 282
1.2.2.7.
THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP TYPES IN LOCATION
HIERARCHY 284
1.2.3.
1.2.3.1.
FORMAL EDUCATION DASHBOARD ................................................................................ 286
THE NUMBER OF STUDENTS IN INSTITUTION TYPE HIERARCHY ................................ 286
1.2.3.2.
THE NUMBER OF STUDENTS IN LOCATION HIERARCHY FOR FORMAL EDUCATION BY
MEANS OF LOCATION OF RESIDENCE, SEX AND OWNERSHIP OF INSTITUTION............................. 287
1.2.3.3.
THE NUMBER OF STUDENTS BY MEANS OF LOCATION OF RESIDENCE, SEX AND
SEMESTERS 289
1.2.3.4.
THE NUMBER OF ENROLLED STUDENTS FOR WITH RESPECT TO LOCATION OF
RESIDENCE AND SEX BY MEANS OF NUTS3 CLASSIFICATION ......................................................... 290
1.2.3.5.
THE GENDER EQUALITY INDEX .................................................................................... 292
1.2.3.6.
THE PERCENTAGE OF ENROLLMENT IN PRIVATE INSTITUTIONS ................................ 293
1.2.3.7.
Year)
THE PERCENTAGE OF REPEATERS (According to the Data of Beginning of the Education
294
1.2.3.8.
THE PERCENTAGE OF REPEATERS (According to the Data of End of the Education Year)
296
1.2.3.9.
THE REPEAT RATIO ...................................................................................................... 297
1.2.3.10. THE NUMBER OF PASSIVE STUDENTS BY CAUSES AND SEMESTERS IN LOCATION
HIERARCHY 299
1.2.3.11.
THE NUMBER OF PASSIVE STUDENTS BY CAUSES, OWNERSHIP AND SEX ................. 300
1.2.3.12. THE PASS-FAIL STATUSES OF THE STUDENTS BY THE END OF SEMESTERS WITH
RESPECT TO LOCATIONS OF RESIDENCE ......................................................................................... 302
1.2.3.13. THE NUMBER OF STUDENTS BY CLASS LEVELS, LOCATIONS OF RESIDENCE AND
PUBLIC/PRIVATE INSTITUTION ........................................................................................................ 303
1.2.3.14. THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL BY GENDER IN NUTS
HIERARCHY 305
1.2.3.15.
THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL WITH EXAM CENTERS ...... 306
1.2.3.16.
THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL BY GENDER IN NUTS HIERARCHY
307
1.2.3.17.
THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL WITH EXAM CENTERS ............. 308
1.2.3.18. SUMMER KINDERGARTENS, MOBILE CLASSES & KINDERGARTENS OF OTHER
INSTITUTIONS.................................................................................................................................. 310
1.2.3.19.
PRE-PRIMARY STUDENTS STATİSTİCS ......................................................................... 311
1.2.3.20.
PROVINCE BASED PRE-PRIMARY STUDENTS STATİSTİCS ............................................ 313
1.2.3.21.
DISABLED STUDENTS WITH OBSTACLE GROUPS......................................................... 314
1.2.3.22.
DISABLED STUDENTS WITH SERVICE GROUPS ............................................................ 316
1.2.3.23.
DISABLED STUDENTS IN SPECIAL CLASSES IN GENERAL SCHOOLS ............................. 318
1.2.3.24. NUMBER OF STUDENTS WITH PROVINCE, DISTRICT, NORMAL/TWO BASED
EDUCATION 319
1.2.3.25.
NUMBER OF DIVISIONS WITH PROVINCE AND CLASS LEVELS .................................... 320
1.2.3.26.
NUMBER OF STUDENTS WHOSE RELATION WITH SCHOOL IS CANCELED ................. 322
1.2.4.
SCHOOLARSHIP, BOARDING STUDENTS AND PRIVATE DORMITORIES DASHBOARD ..... 323
1.2.4.1.
THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS ................................ 323
1.2.4.2.
THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS AND GENDER ......... 325
1.2.4.3.
THE SCHOLARSHIP AMOUNTS DUE TO PROVINCES AND DISTRICTS .......................... 326
1.2.4.4.
THE DOMESTIC SCHOLARSHIP RATES ......................................................................... 328
1.2.4.5.
THE NUMBER OF BOARDING STUDENTS DUE TO DEPARTMENTS, GENDER AND
PAYMENT SITUATIONS .................................................................................................................... 329
1.2.4.6.
GENDER
THE NUMBER OF BOARDING STUDENTS DUE TO NUTS-3 CLASSIFICATION AND
330
1.2.4.7.
FROM
THE NUMBER OF BOARDING STUDENTS DUE TO INSTITUTION WHERE THEY BENEFIT
332
1.2.4.8.
THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR STATUES ........................... 333
1.2.4.9.
THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR PLACE OF RESIDENCE TYPES
335
1.2.4.10. THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES AND THE NUMBER OF
RESIDENT STUDENTS DUE TO OWNERSHIP TYPES ......................................................................... 336
1.2.4.11. THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES AND THE NUMBER OF
RESIDENT STUDENTS DUE TO NUTS3 CLASSIFICATION .................................................................. 337
1.2.4.12.
THE NUMBER OF PRIVATE DORMITORIES WITH EDUCATION LEVELS ........................ 339
1.2.4.13.
THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH OPEN DATES ...... 340
1.2.4.14.
THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH CLOSURE DATES . 341
1.2.5.
1.2.5.1.
STAFF DASHBOARD ......................................................................................................... 342
THE NUMBER OF STAFF DUE TO GENDER IN INSTITUTION HIERARCHY ..................... 342
1.2.5.2.
THE NUMBER OF STAFF DUE TO PUBLIC/PRIVATE/OPEN DISCRIMINATION IN
LOCATION (NUTS) HIERARCHY ........................................................................................................ 344
1.2.5.3.
THE NUMBER OF STAFF DUE TO AGE GROUPS IN LOCATION (NUTS) HIERARCHY ..... 345
1.2.5.4.
THE NUMBER OF STAFF DUE TO PROVIENCE AND EDUCATION LEVEL OF STAFF ...... 347
10 | F I N A L P R A C T I C A L G U I D E L I N E
1.2.5.5.
THE NUMBER OF PUBLIC STAFF BY INSTITUTION HIERARCHY DUE TO JOB TITLES ... 348
1.2.5.6.
GENDERS
THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES, EDUCATION LEVELS AND
350
1.2.5.7.
THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES AND JOB TITLES........................ 351
1.2.5.8.
GENDERS
THE NUMBER OF PUBLIC STAFF DUE TO AGE GROUPS, EDUCATION LEVELS AND
353
1.2.5.9.
THE NUMBER OF PUBLIC TEACHERS DUE TO EDUCATION LEVELS AND PROVINCES . 354
1.2.5.10.
THE NUMBER OF PUBLIC STAFF DUE TO PROVINCES AND GENDERS......................... 356
1.2.5.11. THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION LEVELS FOR PUBLIC
INSTITUTIONS.................................................................................................................................. 357
1.2.5.12. THE NUMBER OF STAFF BY INSTITUTIONAL HIERARCHY DUE TO JOB TITLES FOR
PRIVATE INSTITUTIONS ................................................................................................................... 359
1.2.5.13. THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION LEVELS FOR PRIVATE
INSTITUTIONS.................................................................................................................................. 360
1.2.5.14. THE NUMBER OF STAFF DUE TO BRANCHES, EDUCATION LEVELS AND GENDERS FOR
PRIVATE INSTITUTIONS ................................................................................................................... 362
1.2.5.15. AD-HOC_MODULE_PERS UOE TABLE - EDUCATIONAL PERSONNEL BY LEVEL OF
EDUCATION, PROGRAMME ORIENTATION, PROGRAMME DESTINATION, TYPE OF INSTITUTION,
PERSONNEL CATEGORY AND EMPLOYMENT STATUS..................................................................... 364
1.2.5.16. PERS1 UOE TABLE - CLASSROOM TEACHERS BY LEVEL OF EDUCATION, PROGRAMME
ORIENTATION, PROGRAMME DESTINATION,SEX,AGE, TYPE OF INSTITUTION AND EMPLOYMENT
STATUS
365
1.2.5.17. PERS2 UOE TABLE - SCHOOL LEVEL MANAGEMENT PERSONNEL AND TEACHER AIDES
IN ISCED LEVELS 0, 1, 2 AND 3 ........................................................................................................ 366
1.2.5.18. PERS-ENRL UOE TABLE - NUMBER OF STUDENTS WITH COVERAGE ADJUSTED TO
STATİSTİCS ON EDUCATION PERSONNEL BY LEVEL OF EDUCATION, PROGRAMME ORIENTATION,
PROGRAMME DESTINATION, TYPE OF INSTITUTION, AND INTENSITY OF PARTICIPATION ........... 367
1.2.6.
FINANCE DASHBOARD .................................................................................................... 368
1.2.6.1.
FINANCE-1 (UOE) TABLE, Education Expenditure by Level of Education, Source and
Type of Transaction......................................................................................................................... 368
1.2.6.2.
FINANCE-2 (UOE) TABLE, Education Expenditure by Level of Education, Nature and
Resource category .......................................................................................................................... 369
1.2.6.3.
TEFBIS FINANCE-1 TABLE REPORT (DUE TO LOCATION) ............................................. 370
1.2.6.4.
TEFBIS FINANCE-1 TABLE REPORT (DUE TO EDUCATION LEVEL) ................................ 372
1.2.6.5.
TEFBIS FINANCE-2 TABLE REPORT (DUE TO LOCATION) ............................................. 374
1.2.6.6.
TEFBIS FINANCE-2 TABLE REPORT (DUE TO EDUCATION LEVEL) ................................ 376
1.2.6.7.
CENTRAL BUDGET FINANCE-1 TABLE REPORT ........................................................... 378
1.2.6.8.
CENTRAL BUDGET FINANCE-2 TABLE REPORT ........................................................... 379
1.2.6.9.
CENTRAL BUDGET FINANCE-1 TABLE REPORT (EXPENDITURES OF SPECIAL PROVINCE
ADMINISTRATION) .......................................................................................................................... 381
1.2.6.10. CENTRAL BUDGET FINANCE-2 TABLE REPORT (EXPENDITURES OF SPECIAL PROVINCE
ADMINISTRATION) .......................................................................................................................... 382
1.2.6.11.
1.2.7.
1.2.7.1.
PERIODS
TEFBIS-HOUSEHOLD QUESTIONNAIRE ANALYSIS RESULTS......................................... 383
NON-FORMAL DASHBOARD ............................................................................................ 384
THE NUMBER OF APPLICANTS FOR MOTOR VEHICLES BY CERTIFICATE TYPES AND
384
1.2.7.2.
THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES BY CERTIFICATE TYPES
AND PERIODS .................................................................................................................................. 385
1.2.7.3.
THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES BY EDUCATION LEVELS
AND PERIODS .................................................................................................................................. 386
1.2.7.4.
THE NUMBER OF COURSES OPENED BY SETTLEMENT TYPES AND PERIODS .............. 387
1.2.7.5.
THE NUMBER OF TRAINEES BY COURSE TYPES AND PERIODS ................................... 388
1.2.7.6.
THE NUMBER OF TRAINEES BY EMPLOYEMENT TYPES AND PERIODS ....................... 389
1.2.7.7.
THE NUMBER OF STAFF BY STATUS AND PERIODS ..................................................... 390
1.2.8.
UOE DATA TABLES DASHBOARD ..................................................................................... 391
1.2.8.1.
ENRL-1 UOE DATA TABLE ............................................................................................ 391
1.2.8.2.
ENRL1-ADULT UOE DATA TABLE ................................................................................. 392
1.2.8.3.
ENRL1a UOE DATA TABLE ........................................................................................... 393
1.2.8.4.
ENRL1a-ADULT UOE DATA TABLE ............................................................................... 394
1.2.8.5.
1.2.8.6.
1.2.8.7.
1.2.8.8.
ENTR-1 UOE DATA TABLE ............................................................................................ 398
1.2.8.9.
ENTR-2 UOE DATA TABLE ............................................................................................ 399
1.2.8.10.
GRAD-1 UOE DATA TABLE ........................................................................................... 400
1.2.8.11.
1.2.8.12.
1.2.8.13.
REGIO-1 UOE DATA TABLE .......................................................................................... 403
1.2.8.14.
REGIO-2 UOE DATA TABLE .......................................................................................... 404
1.2.8.15.
CLASS UOE DATA TABLE .............................................................................................. 405
1.2.8.16.
ENRLLANG-1 UOE DATA TABLE ................................................................................... 406
1.2.8.17.
ENRLLANG-2 UOE DATA TABLE ................................................................................... 406
1.2.8.18.
PERS-1 UOE DATA TABLE ............................................................................................ 407
1.2.8.19.
PERS-2 UOE DATA TABLE ............................................................................................ 408
1.2.8.20.
ADHOC-MODULE-PERS UOE DATA TABLE................................................................... 409
1.2.8.21.
PERS-ENRL UOE DATA TABLE ...................................................................................... 410
1.2.9.
COMBINED INSTITUTION, CLASSROOM, STUDENT, TEACHER DASHBOARD .................. 411
1.2.9.1.
INSTITUTION, TEACHER, STUDENT STATİSTİCS BY PROVINCE AND DISTRICT LEVELS 411
1.2.9.2.
INSTITUTION, TEACHER, STUDENT INDICATORS BY PROVINCE AND DISTRICT LEVELS
412
1.2.9.3.
NUMBER OF ENROLLED STUDENT IN NUTS HIERARCHY WITHIN PUBLICATION PERIOD
414
1.2.9.4.
PERIOD
NUMBER OF GRADUATED STUDENT IN NUTS HIERARCHY WITHIN PUBLICATION
415
1.2.9.5.
NUMBER OF STUDENTS IN OPEN HIGH SCHOOL IN NUTS HIERARCHY WITHIN
PUBLICATION PERIOD ..................................................................................................................... 416
1.2.9.6.
NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL IN NUTS HIERARCHY WITHIN
PUBLICATION PERIOD ..................................................................................................................... 417
1.2.9.7.
SUMMER KINDERGARTENS, MOBILE CLASSES, SHCEK & KINDERGARTENS OF OTHER
INSTITUTIONS.................................................................................................................................. 418
1.3.
PACKAGES, JOBS AND RELATIONS ...................................................................................... 419
1.4.
IMPORTANT NOTES............................................................................................................. 429
1.4.1.
Cache Structure of Oracle BI ........................................................................................... 429
1.4.2.
Indexes in Materialized Views ........................................................................................ 431
1.4.3.
Partitions in Fact Tables .................................................................................................. 432
1.4.4.
Performance Tuning of BI System ................................................................................... 433
Section F.
USE OF ESTIMATIONS ..................................................................................................... 434
1
USE OF ESTIMATIONS ............................................................................................................. 434
1.1
Introduction .................................................................................................................... 434
1.2
Estimation methods: general guidelines and taxonomy ................................................ 434
1.2.1
Taxonomy of estimation methods .............................................................................. 434
1.2.2
General recommendations ......................................................................................... 442
1.2.3
Special focus on internal estimation methods and underlying assumptions ............. 444
1.3
Identification of estimation needs in Turkey .................................................................. 445
1.4
Practical guidelines for estimations ................................................................................ 446
1.4.1
Splitting the ISCED spanning levels 1-2 ....................................................................... 446
1.4.2
ISCED breakdown for the administrative and support staff in combined schools ..... 447
1.4.3
ISCED breakdown for staff in the central bodies ........................................................ 448
1.4.4
ISCED breakdown for expenditure in combined schools ............................................ 449
1.4.5
Anticipating the new 4+4+4 regulation ...................................................................... 451
1.4.6
how to complete rest of the UOE tables .................................................................... 453
1.4.4.1.
Alignment of enrolment data to finance data (table FIN_ENRL2) .............................. 454
1.4.4.2.
Alignment of enrolment data to personnel data (table Pers_ENRL2) ........................ 454
2
PREPARING THE TRANSITION TO ISCED 2011 ......................................................................... 455
3
ROUTINES FOR TIME SERIES VALIDATION AND PRESENTATION ............................................ 456
4
QUALITY ISSUES ...................................................................................................................... 456
5
4.1
Quality in the European Statistical system (ESS) ............................................................ 456
4.2
Quality reporting in the UOE........................................................................................... 457
SUMMARIZING DATA FROM DIFFERENT SOURCES ................................................................ 458
6
TRAINING NEEDS ..................................................................................................................... 458
ANNEXES ............................................................................................................................................. 459
Annex 1: List of UOE Tables .......................................................................................................... 460
Annex 2: UOE Quality Reporting ................................................................................................... 465
Table of Figures
FIGURE 1: FRAMEWORK FOR THE ISCED MAPPİNG İN TURKEY......................................................... 40
FIGURE 2 Statistics Flow Within the Ministry ................................................................................. 153
FIGURE 3 Source and Target of BI Architecture ............................................................................ 153
FIGURE 4 BI Network Flow ............................................................................................................... 154
FIGURE 5 Design & Development Life Cycle ................................................................................. 155
FIGURE 6 - Table Description of ST_KURUMTUR ....................................................................... 157
FIGURE 7 Table Description of ST_KURUMLAR .......................................................................... 158
FIGURE 8 Table Description of FACT_KURUMLAR ..................................................................... 159
FIGURE 9 Table Description of FACT_KURUM_BINA ................................................................. 159
FIGURE 10 Table Description of FACT_KURUM_ KULLANIM_ALAN ....................................... 160
FIGURE 11 Table Description of FACT_KURUM_KUTUPHANE_MATERYAL ........................ 160
FIGURE 12Table Description of FACT_IO_OGRYIL_BASI_BILGILERI .................................... 163
FIGURE 13Table Description of FACT_IO_OGRYIL_SONU_BILGILERI .................................. 164
FIGURE 14Table Description of FACT_IO_OGRENCI_PASIF.................................................... 165
FIGURE 15Table Description of FACT_IO_OGRYIL_BASI_BILGILERI .................................... 168
FIGURE 16Table Description of FACT_IO_OGRYIL_SONU_BILGILERI .................................. 169
FIGURE 17Table Description of FACT_IO_OGRENCI_PASIF.................................................... 170
FIGURE 18 Table Description of FACT_IO_ENGELLI_OGR....................................................... 172
FIGURE 19 Table Description of FACT_AIO_OGRENCI_YENI .................................................. 174
FIGURE 20 Table Description of FACT_AOL_OGRENCI_YENI ................................................. 175
FIGURE 21 Table Description of FACT_DIS_KURUM_OGR_OGRETMEN ............................. 176
FIGURE 22 Table Description of FACT_AKTIF_BURS_OGR_BILGILERI ................................ 179
FIGURE 23 Table Description of FATCT_BURS_MIKTAR .......................................................... 180
FIGURE 24 Table Description of FACT_BURSU_IPTAL_OGR_BILGILERI ............................. 180
FIGURE 25 Table Description of FACT_BURS_SINAV_ONAY_OGR ...................................... 181
FIGURE 26 Table Description of FACT_YATILILIK_DURUM_OGR ........................................... 182
FIGURE 27 Table Description of FACT_OZEL_YURT_KAPASITE ............................................ 183
FIGURE 28 Table Description of FACT_YABANCI_DIL ............................................................... 186
FIGURE 29 Table Description of FACT_YABANCI_DIL_UOE .................................................... 187
FIGURE 30 Table Description of FACT_PERSONEL_BILGILERI TABLE ................................ 189
FIGURE 31 Table Description of FACT_PERSONEL_UOE ......................................................... 190
FIGURE 32 Table Description of FACT_PERS_UOE12 ............................................................... 190
FIGURE 33 Table Description of FACT_PERS_ENRL ................................................................. 191
FIGURE 34 Table Description of ST_ISCED_FINANS ................................................................. 193
FIGURE 35 Table Description of BI_TEFBIS_FINANS_GIDER .................................................. 194
FIGURE 36 Table Description of BI_TEFBIS_FINANS_GELIR ................................................... 196
FIGURE 37 Table Description of BI_EBUTCE................................................................................ 197
FIGURE 38 Table Description of BI_BELEDIYE ............................................................................ 198
FIGURE 39 Table Description of BI_HANEHALKI_ANALIZ ......................................................... 199
FIGURE 40 Table Description of ST_ISLEM_TARIHI_FINANS .................................................. 200
FIGURE 41 Table Description of ST_EBUTCE_IDARIBIRIM_TURU ......................................... 200
FIGURE 42 Table Description of ST_HANEHALKI_ANKET_TIPLERI ....................................... 200
FIGURE 43 Table Description of FINANS_TOPLAM_HESAP ..................................................... 201
FIGURE 44 Table Description of FACT_TEFBIS_FINANS1 ........................................................ 201
FIGURE 45 Table Description of FACT_EBUTCE_FINANS1 ...................................................... 202
FIGURE 46 Table Description of FACT_EBUTCE_FINANS1_BELTAB .................................... 203
FIGURE 47 Table Description of FACT_TEFBIS_FINANS2 ........................................................ 203
FIGURE 48 Table Description of FACT_TEFBIS_FINANS_OZEL .............................................. 204
FIGURE 49 Table Description of FACT_EBUTCE_FINANS2 ...................................................... 204
FIGURE 50 Table Description of FACT_EBUTCE_FINANS2_BELTAB .................................... 205
FIGURE 51 Table Description of FACT_TEFBIS_FINANS1_UOE ............................................. 206
FIGURE 52 Table Description of FACT_TEFBIS_FINANS2_UOE ............................................. 206
FIGURE 53 Table Description of FACT_EBUTCE_FINANS1_UOE ........................................... 207
FIGURE 54 Table Description of FACT_EBUTCE_FINANS2_UOE ........................................... 207
FIGURE 55 Table Description of FACT_HANEHALKI_FINANS1_UOE ..................................... 208
FIGURE 56 Table Description of FACT_FINANS........................................................................... 208
FIGURE 57 Table Description of FACT_YAYGIN_KURS_BLG ................................................... 215
FIGURE 58 Table Description of FACT_YAYGIN_KURSIYER_BLG ......................................... 216
FIGURE 59 Table Description of FACT_YAYGIN_PERSONEL_BLG ........................................ 217
FIGURE 60 Table Description of FACT_MTSAS_BASVURU ...................................................... 217
FIGURE 61 Table Description of FACT_MTSAS_SERTIFIKA ..................................................... 218
FIGURE 62 Table Description of T_UOE_TANIM_TABLOSU ..................................................... 219
FIGURE 63 Table Description of T_GECICI_SHCEK_BILGI ....................................................... 219
FIGURE 64 Table Description of T_KURUM_OGR_OGRETMEN .............................................. 220
FIGURE 65 Table Description of ST_ISLEM_TARIHI ................................................................... 220
FIGURE 66 Table Description of ST_ISLEM_TARIHI_KURUM .................................................. 221
FIGURE 67 Table Description of ST_ISLEM_TARIHI_ACIK ........................................................ 221
FIGURE 68 Table Description of ST_ISLEM_TARIHI_FINANS .................................................. 222
FIGURE 69 Table Description of ST_ISLEM_TARIHI_YAYGIN .................................................. 223
FIGURE 70 Table Description of ST_YAS_GRUPLARI ................................................................ 223
FIGURE 71 Table Description of ST_MTSC_EGITIM_DURUMU ............................................... 223
FIGURE 72 Records in ST_MTSC_EGITIM_DURUMU ................................................................ 223
FIGURE 73 Records in ST_OGRENCI_DURUM ........................................................................... 224
FIGURE 74 Table Description of ST_KURUMTUR ........................................................................ 225
FIGURE 75 Table Description of ST_OZELYURT_YERLESIM_YERI ....................................... 225
FIGURE 76 Table Description of ST_YIL_GRUPLARI .................................................................. 226
FIGURE 77 Records of ST_SINIF_SEVIYESI ................................................................................ 226
FIGURE 78 Records of ST_ULKELER............................................................................................. 227
FIGURE 79 Table Description of ST_EBUTCE_IDARIBIRIM_TURU ......................................... 227
FIGURE 80 Table Description of ST_HANEHALKI_ANKET_TIPLERI ....................................... 228
FIGURE 81 Table Description of ST_HANEHALKI_SORU_TANIM............................................ 228
FIGURE 82 Table Description of ST_FOET .................................................................................... 228
FIGURE 83 Table Description of ST_GUNLER .............................................................................. 228
FIGURE 84 Table Description of ST_ISCED .................................................................................. 229
FIGURE 85 Records of ST_ISCED................................................................................................... 229
FIGURE 86 Table Description of ST_ISCED_VIEW ...................................................................... 230
FIGURE 87 Records of ST_ISCED_VIEW ...................................................................................... 230
FIGURE 88 Table Description of ST_ISCED_EK_TANIMLAR .................................................... 230
FIGURE 89 Table Description of ST_PERSONEL_GOREV_KATEGORI ................................. 231
FIGURE 90 Records of ST_PERSONEL_GOREV_KATEGORI.................................................. 231
FIGURE 91 Table Description of ST_OKULONCESI_KURUMTUR ........................................... 231
FIGURE 92 Table Description of FACT_DIS_KURUM_OGRANCI_V ........................................ 232
FIGURE 93 Table Description of ST_NUTS_IL_ILCE ................................................................... 232
FIGURE 94 Table Description of ST_NUTS_IL_ILCE_YURT ...................................................... 233
FIGURE 95 Table Description of ST_OGRYIL_ISCED_MV ......................................................... 233
FIGURE 96 Table Description of ST_KURUM_IL_MV .................................................................. 233
FIGURE 97 Table Description of ST_ANA_SINIFI_VAR .............................................................. 234
FIGURE 98 Table Description of FACT_UOE_CLASS_MV ......................................................... 234
FIGURE 99 Table Description of ST_BURS_DONEM .................................................................. 234
FIGURE 100 Table Description of ST_DONEM_BILGILERI ........................................................ 235
FIGURE 101 Table Description of ST_ENGELLI_SINIF ............................................................... 235
FIGURE 102 Table Description of ST_DIL_KODLARI_MV .......................................................... 235
FIGURE 103 Table Description of BI_YABANCIDIL_MV .............................................................. 236
FIGURE 104 Table Description of ST_ATAMA_SEBEPLERI_MV .............................................. 236
FIGURE 105 Table Description of ST_BRANSLAR_MV ............................................................... 237
FIGURE 106 Table Description of ST_GOREV_UNVAN_MV ...................................................... 237
FIGURE 107 Table Description of ST_HIZMET_SINIFLARI_MV ................................................ 237
FIGURE 108 Table Description of ST_ISTIHDAM_TIPLERI_MV ................................................ 237
FIGURE 109 Table Description of ST_OGRENIM_DURUMLARI_MV ....................................... 238
FIGURE 110 Table Description of ST_UNVANLAR_MV............................................................... 238
FIGURE 111 Records of ST_YAYGIN_BASARI_DURUMU_MV ................................................. 238
FIGURE 112 Records of ST_YAYGIN_BRANSLAR_MV .............................................................. 238
FIGURE 113 Records of ST_YAYGIN_CALISMA_DURUMU_MV .............................................. 239
FIGURE 114 Records of ST_YAYGIN_ENGEL_DURUMU_MV .................................................. 239
FIGURE 115 Records of ST_YAYGIN_KURS_ACMA_BICIMI_MV ............................................ 239
FIGURE 116 Table Description of ST_YAYGIN_KURS_DURUMU_MV .................................... 240
FIGURE 117 Table Description of ST_YAYGIN_KURS_TIPI_MV .............................................. 240
FIGURE 118 Table Description of ST_YAYGIN_MEDENI_DURUMU_MV ................................ 240
FIGURE 119 Table Description of ST_YAYGIN_OGRENIM_DURUMU_MV ............................ 241
FIGURE 120 Table Description of ST_YAYGIN_PERSONEL_STATUSU_MV ........................ 241
FIGURE 121 Table Description of ST_YAYGIN_SERTIFIKA_TIPI_MV ..................................... 241
FIGURE 122 Three Layers in the BI Administration Tool .............................................................. 248
FIGURE 123 Institutions Business Model ........................................................................................ 249
FIGURE 124 Formal Education Business Model ............................................................................ 251
FIGURE 125 Staff Business Model ................................................................................................... 252
FIGURE 126 Finance Business Model ............................................................................................. 253
FIGURE 127 Non-Formal Business Model ...................................................................................... 254
FIGURE 128 - Login Page .................................................................................................................. 255
FIGURE 129 Dashboard Wellcome Page ........................................................................................ 256
FIGURE 130 Dashboard Prompt Sample ........................................................................................ 256
FIGURE 131 Sample Dashboard Page ........................................................................................... 257
FIGURE 132 Sample Dashboard Page For DrillDown................................................................... 257
FIGURE 133 Sample Dashboard Page For Rollup ........................................................................ 258
FIGURE 134 Sample Dashboard Page For Ordering .................................................................... 258
FIGURE 135 Dashboard Report - THE NUMBER OF INSTITUTIONS DUE TO THEIR
OWNERSHIP TYPES IN LOCATION HIERARCHY................................................................... 259
FIGURE 136 Dashboard Report -THE NUMBER OF INSTITUTIONS DUE TO THEIR MAIN
TYPE / SUB TYPE STATUS AND CURRENT SITUATIONS IN LOCATION HIERARCHY 261
FIGURE 137 Dashboard Report -THE NUMBER OF INSTITUTIONS WITH RESPECT TO
INSTITUTION TYPES WITH THE SELECTION FOR PROVINCES &DISTRICTS .............. 262
FIGURE 138 Dashboard Report -THE NUMBER OF INSTITUTIONS IN INSTITUTION TYPE
HIERARCHY ..................................................................................................................................... 264
FIGURE 139 Dashboard Report - THE NUMBER OF PUBLIC/PRIVATE/OPEN INSTITUTIONS WITH
LOCATION HIERARCHY, NORMAL/TWO BASED EDUCATION.............................................................. 266
FIGURE 140 Dashboard Report -THE NUMBER OF INSTITUTIONS DUE TO THEIR
ENTRANCE TO SERVICE YEARS ............................................................................................... 268
FIGURE 141 Dashboard Report -THE NUMBER OF INSTITUTIONS WHICH HAVE A
PREPARATORY CLASS ................................................................................................................ 269
FIGURE 142 Dashboard Report - THE NUMBER OF INSTITUTIONS WITH SELECTED
PROVINCE AND DISTRICT LEVEL ............................................................................................. 271
FIGURE 143 Dashboard Report - THE NUMBER OF CLOSED INSTITUTIONS WITH
CLOSURE REASONS..................................................................................................................... 272
FIGURE 144 Dashboard Report- THE NUMBER OF INSTITUTIONS &CLASSROOMS IN
NUTS LEVEL 2 ................................................................................................................................. 274
FIGURE 145 Dashboard Report-THE NUMBER OF INSTITUTIONS & USAGE AREAS IN
NUTS HIERARCHY ......................................................................................................................... 276
FIGURE 146 Dashboard Report -THE NUMBER OF PUBLIC HOUSES IN INSTITUTION
TYPE HIERARCHY ......................................................................................................................... 277
FIGURE 147 Dashboard Report -THE NUMBER OF PENSIONS IN INSTITUTION TYPE
HIERARCHY ..................................................................................................................................... 279
FIGURE 148 Dashboard Report-THE BUILDING AND GARDEN AREAS IN LOCATION
HIERARCHY ..................................................................................................................................... 281
FIGURE 149 Dashboard Report -THE NUMBER OF LIBRARY MATERIALS IN LOCATION OF
RESIDENCE HIERARCHY............................................................................................................. 282
FIGURE 150 Dashboard Report - THE NUMBER OF INSTITUTIONS DUE TO THEIR
OWNERSHIP TYPES IN LOCATION HIERARCHY................................................................... 284
FIGURE 151 Dashboard Report -THE NUMBER OF STUDENTS IN INSTITUTION TYPE
HIERARCHY ..................................................................................................................................... 286
FIGURE 152 Dashboard Report -THE NUMBER OF STUDENTS IN LOCATION HIERARCHY
FOR FORMAL EDUCATION BY MEANS OF LOCATION OF RESIDENCE, SEX AND
OWNERSHIP OF INSTITUTION ................................................................................................... 287
FIGURE 153 Dashboard Report - NUMBER OF STUDENTS BY MEANS OF LOCATION OF
RESIDENCE, SEX AND SEMESTERS ........................................................................................ 289
FIGURE 154 Dashboard Report - THE NUMBER OF ENROLLED STUDENTS FOR WITH
RESPECT TO. LOCATION OF RESIDENCE AND SEX BY MEANS OF NUTS3
CLASSIFICATION............................................................................................................................ 290
FIGURE 155 Dashboard Report - THE GENDER EQUALITY INDEX ........................................ 292
FIGURE 156 Dashboard Report - THE PERCENTAGE OF ENROLLMENT IN PRIVATE
INSTITUTIONS ................................................................................................................................. 293
FIGURE 157 Dashboard Report - THE PERCENTAGE OF REPEATERS (According to the
Data of Beginning of the Education Year) .................................................................................... 294
FIGURE 158 Dashboard Report - THE PERCENTAGE OF REPEATERS (According to the
Data of End of the Education Year) ............................................................................................... 296
FIGURE 159 Dashboard Report - THE REPEAT RATIO .............................................................. 297
FIGURE 160Dashboard Report - THE NUMBER OF PASSIVE STUDENTS BY CAUSES AND
SEMESTERS IN LOCATION HIERARCHY ................................................................................. 299
FIGURE 161 Dashboard Report - THE NUMBER OF PASSIVE STUDENTS BY CAUSES,
OWNERSHIP AND SEX ................................................................................................................. 300
FIGURE 162 Dashboard Report - THE PASS-FAIL STATUSES OF THE STUDENTS BY THE
END OF SEMESTERS WITH RESPECT TO LOCATIONS OF RESIDENCE ....................... 302
FIGURE 163 Dashboard Report - THE THE NUMBER OF STUDENTS BY CLASS LEVELS,
LOCATIONS OF RESIDENCE AND PUBLIC/PRIVATE INSTITUTION ................................. 303
FIGURE 164 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY
SCHOOL BY GENDER IN NUTS HIERARCHY ......................................................................... 305
FIGURE 165Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY
SCHOOL WITH EXAM CENTERS (Students located in Turkey) ............................................. 306
FIGURE 166 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY
SCHOOL WITH EXAM CENTERS (Students located abroad) ................................................. 306
FIGURE 167 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL
BY GENDER IN NUTS HIERARCHY ........................................................................................... 307
FIGURE 168Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL
WITH EXAM CENTERS (Students located in Turkey) ............................................................... 308
FIGURE 169 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL
WITH EXAM CENTERS (Students located abroad) ................................................................... 309
FIGURE 170 Dashboard Report - SUMMER KINDERGARTENS, MOBILE CLASSES &
KINDERGARTENS OF OTHER INSTITUTIONS........................................................................ 310
FIGURE 171 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Indepandant
Pre-Primary Schools)....................................................................................................................... 311
FIGURE 172 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Pre-Primary
Students in Primary Schools) ......................................................................................................... 311
FIGURE 173 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Pre-Primary
Students in Upper-Secondary Schools)........................................................................................ 312
FIGURE 174 Dashboard Report - PROVINCE BASED PRE-PRIMARY STUDENTS
STATİSTİCS ..................................................................................................................................... 313
FIGURE 175 Dashboard Report - DISABLED STUDENTS WITH OBSTACLE GROUPS (First Data Table)
............................................................................................................................................................ 314
FIGURE 176 Dashboard Report - DISABLED STUDENTS WITH OBSTACLE GROUPS (Second Data
Table With Obstacle Groups) .............................................................................................................. 315
FIGURE 177 Dashboard Report - DISABLED STUDENTS WITH SERVICE GROUPS ............................ 316
FIGURE 178 Dashboard Report - DISABLED STUDENTS IN SPECIAL CLASSES IN GENERAL SCHOOLS
............................................................................................................................................................ 318
FIGURE 179 Dashboard Report - NUMBER OF STUDENTS WITH PROVINCE, DISTRICT,
NORMAL/TWO BASED EDUCATION .................................................................................................... 319
FIGURE 180 Dashboard Report - NUMBER OF DIVISIONS WITH PROVINCE AND CLASS LEVELS .... 320
FIGURE 181 Dashboard Report - NUMBER OF STUDENTS WHOSE RELATION WITH SCHOOL IS
CANCELED ........................................................................................................................................... 322
FIGURE 182 Dashboard Report - THE NUMBER OF SCHOLAR STUDENTS DUE TO
DEPARTMENTS .............................................................................................................................. 323
FIGURE 183 Dashboard Report - THE NUMBER OF SCHOLAR STUDENTS DUE TO
DEPARTMENTS AND GENDER ................................................................................................... 325
FIGURE 184 - THE SCHOLARSHIP AMOUNTS DUE TO PROVINCES AND DISTRICTS ... 326
FIGURE 185 Dashboard Report - THE DOMESTIC SCHOLARSHIP RATES Parameters : .. 328
FIGURE 186 Dashboard Report - THE NUMBER OF BOARDING STUDENTS DUE TO
DEPARTMENTS, GENDER AND PAYMENT SITUATIONS .................................................... 329
NUTS-3 CLASSIFICATION AND GENDER ............................................................................... 330
INSTITUTION WHERE THEY BENEFIT FROM ......................................................................... 332
FIGURE 189 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES DUE TO
THEIR STATUES ............................................................................................................................. 333
FIGURE 190 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES DUE TO
THEIR PLACE OF RESIDENCE TYPES ..................................................................................... 335
FIGURE 191 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES, THE BED
CAPACITIES AND THE NUMBER OF RESIDENT STUDENTS DUE TO OWNERSHIP
TYPES ............................................................................................................................................... 336
FIGURE 192 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES, THE BED
CAPACITIES AND THE NUMBER OF RESIDENT STUDENTS DUE TO OWNERSHIP
TYPES ............................................................................................................................................... 337
FIGURE 193 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES AND
CAPACITIES WITH OPEN DATES............................................................................................... 340
FIGURE 194 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES AND
CAPACITIES WITH CLOSURE DATES ....................................................................................... 341
FIGURE 195 Dashboard Report - THE NUMBER OF STAFF DUE TO GENDER IN
INSTITUTION HIERARCHY ........................................................................................................... 342
FIGURE 196 Dashboard Report - THE NUMBER OF STAFF DUE TO
PUBLIC/PRIVATE/OPEN DISCRIMINATION IN LOCATION (NUTS) HIERARCHY ............ 344
FIGURE 197 Dashboard Report - THE NUMBER OF STAFF DUE TO AGE GROUPS IN
LOCATION (NUTS) HIERARCHY ................................................................................................. 345
FIGURE 198 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVIENCE AND
EDUCATION LEVEL OF STAFF ................................................................................................... 347
FIGURE 199 Dashboard Report - THE NUMBER OF STAFF BY INSTITUTION HIERARCHY
DUE TO JOB TITLES ...................................................................................................................... 348
FIGURE 200 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES,
EDUCATION LEVELS AND GENDERS ...................................................................................... 350
FIGURE 201 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES
AND JOB TITLES............................................................................................................................. 351
FIGURE 202 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO AGE
GROUPS, EDUCATION LEVELS AND GENDERS ................................................................... 353
FIGURE 203 Dashboard Report - THE NUMBER OF PUBLIC TEACHERS DUE TO
EDUCATION LEVELS AND PROVINCES ................................................................................... 354
FIGURE 204 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO PROVINCES
AND GENDERS ............................................................................................................................... 356
FIGURE 205 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVINCES AND
EDUCATION LEVELS FOR PUBLIC INSTITUTIONS ............................................................... 357
FIGURE 206 Dashboard Report - THE NUMBER OF PRIVATE STAFFBY INSTITUTIONAL
HIERARCHY DUE TO JOB TITLES FOR PRIVATE INSTITUTIONS ..................................... 359
FIGURE 207 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVINCES AND
EDUCATION LEVELS FOR PRIVATE INSTITUTIONS ............................................................ 360
FIGURE 208 Dashboard Report - THE NUMBER OF STAFF DUE TO BRANCHES,
EDUCATION LEVELS AND GENDERS FOR PRIVATE INSTITUTIONS .............................. 362
FIGURE 209 Dashboard Report - AD-HOC_MODULE_PERS UOE TABLE............................ 364
FIGURE 210 Dashboard Report - PERS1 UOE TABLE............................................................... 365
FIGURE 211 Dashboard Report - PERS2 UOE TABLE............................................................... 366
FIGURE 212 Dashboard Report - PERS-ENRL UOE TABLE ..................................................... 367
FIGURE 213 Dashboard Report - FINANCE-1 TABLE ................................................................ 368
FIGURE 214 Dashboard Report – FINANCE-2 TABLE................................................................. 369
FIGURE 215 Dashboard Report - TEFBIS FINANCE-1 TABLE REPORT (DUE TO
LOCATION) ....................................................................................................................................... 370
EDUCATION LEVEL) ...................................................................................................................... 372
LOCATION) ....................................................................................................................................... 374
EDUCATION LEVEL) ...................................................................................................................... 376
FIGURE 219 Dashboard Report - CENTRAL BUDGET FINANCE-1 TABLE REPORT ......... 378
FIGURE 220 Dashboard Report - CENTRAL BUDGET FINANCE-2 TABLE REPORT ......... 379
FIGURE 221 Dashboard Report - CENTRAL BUDGET FINANCE-1 TABLE REPORT
(EXPENDITURES OF SPECIAL PROVINCE ADMINISTRATION) ......................................... 381
(EXPENDITURES OF SPECIAL PROVINCE ADMINISTRATION) ......................................... 382
FIGURE 223 Dashboard Report – TEFBIS-HOUSEHOLD QUESTIONNAIRE ANALYSIS
RESULTS (HOUSEHOLD EXPENDITURES) ............................................................................. 383
FIGURE 224 Dashboard Report – THE NUMBER OF APPLICANTS FOR MOTOR VEHICLES
BY CERTIFICATE TYPES AND PERIODS ................................................................................. 384
FIGURE 225 Dashboard Report – THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR
VEHICLES BY CERTIFICATE TYPES AND PERIODS ............................................................ 385
FIGURE 226 Dashboard Report – THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR
VEHICLES BY EDUCATION LEVELS AND PERIODS ............................................................. 386
FIGURE 227 Dashboard Report – THE NUMBER OF COURSES OPENED BY SETTLEMENT
TYPES AND PERIODS ................................................................................................................... 387
FIGURE 228 Dashboard Report – THE NUMBER OF TRAINEES BY COURSE TYPES AND
PERIODS .......................................................................................................................................... 388
FIGURE 229 Dashboard Report – THE NUMBER OF TRAINEES BY EMPLOYEMENT TYPES
AND PERIODS ................................................................................................................................. 389
FIGURE 230 Dashboard Report – THE NUMBER OF STAFF BY STATUS AND PERIODS . 390
FIGURE 231 Dashboard Report - ENRL-1 UOE DATA TABLES ................................................ 391
FIGURE 232 Dashboard Report - ENRL1-ADULT UOE DATA TABLES ................................... 392
FIGURE 233 Dashboard Report - ENRL1a UOE DATA TABLES ............................................... 393
FIGURE 234 Dashboard Report - ENRL1a-ADULT UOE DATA TABLES ................................. 394
FIGURE 238 Dashboard Report - ENTR-1 UOE DATA TABLES ................................................ 398
FIGURE 239 Dashboard Report - ENTR-2 UOE DATA TABLES ................................................ 399
FIGURE 240 Dashboard Report - GRAD-1 UOE DATA TABLES ............................................... 400
FIGURE 243 Dashboard Report - REGIO-1 UOE DATA TABLES .............................................. 403
FIGURE 244 Dashboard Report - REGIO-2 UOE DATA TABLES .............................................. 404
FIGURE 245 Dashboard Report - CLASS UOE DATA TABLES ................................................. 405
FIGURE 246 Dashboard Report - ENRLLANG-1 UOE DATA TABLES ..................................... 406
FIGURE 247 Dashboard Report - ENRLLANG-2 UOE DATA TABLES ..................................... 406
FIGURE 248 Dashboard Report - PERS-1 UOE DATA TABLES ................................................ 407
FIGURE 249 Dashboard Report - PERS-2 UOE DATA TABLES ................................................ 408
FIGURE 250 Dashboard Report - ADHOC-MODULE-PERS UOE DATA TABLES ................. 409
FIGURE 251 Dashboard Report - PERS-ENRL UOE DATA TABLES........................................ 410
FIGURE 252 Dashboard Report - INSTITUTION, TEACHER, STUDENT STATİSTİCS BY
PROVINCE AND DISTRICT LEVELS .......................................................................................... 411
FIGURE 253 Dashboard Report - INSTITUTION, TEACHER, STUDENT INDICATORS BY
PROVINCE AND DISTRICT LEVELS .......................................................................................... 412
FIGURE 254 Dashboard Report - NUMBER OF ENROLLED STUDENT IN NUTS
HIERARCHY WITHIN PUBLICATION PERIOD.......................................................................... 414
FIGURE 255 Dashboard Report - NUMBER OF GRADUATED STUDENT IN NUTS
HIERARCHY WITHIN PUBLICATION PERIOD.......................................................................... 415
FIGURE 256 Dashboard Report - NUMBER OF STUDENTS IN OPEN HIGH SCHOOL IN
NUTS HIERARCHY WITHIN PUBLICATION PERIOD .............................................................. 416
FIGURE 257 Dashboard Report - NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL IN
NUTS HIERARCHY WITHIN PUBLICATION PERIOD.............................................................. 417
FIGURE 258 Dashboard Report - SUMMER KINDERGARTENS, MOBILE CLASSES,SHCEK
& KINDERGARTENS OF OTHER INSTITUTIONS .................................................................... 418
FIGURE 259 Cache MAnager Menu Item in Oracle BI Administrator ......................................... 429
FIGURE 260 Cache Manager ............................................................................................................ 430
FIGURE 261 Presentation Cache Bypass Atribute in Analysis .................................................... 431
ABBREVIATIONS AND ACRONYMS
BI
CLA
DPG
EUROSTAT
DPT
EGITEK
FOET
FTE
INES
ISCED
IT
MEBBIS
MoNE
NFQ
NUTS
OECD
PG
R&D
SDP
SHÇEK
TA
TEFBIS
TUIK/TURKSTAT
UOE
UNESCO-UIS
YÖK
ÖSYM
Business Intelligence
Classification of Learning Activities
Draft Practical Guidelines
Statistical Office of the European Union
Prime Ministry State Planning Organisation
Education Technology Department in MoNE (named as Information
Technologies Group Presidency with the re-organization)
Fields of Education and Training. International standard classification
of the content of education programmes
Full-Time Equivalents
Indicators of Education Systems
International Standard Classification of Education
Information Technology
Data collection and database system for schools, students, staff
member etc. in MoNE
Ministry of National Education
National Framework of Qualifications
EU standard coding system for geographical regions
Organisation for Economic Co-Operation and Development
Practical Guideline
Research and Development
Strategy Development Presidency
Social Services and Child Protection Agency
Technical Assistance
Data collection routine for finance data in MoNE (in operation from
2011)
Turkish Statistical Institute
UNESCO-UIS / OECD / EUROSTAT
United Nation Education and Culture Organisation- UNESCO Institute
of Statistics
Council of Higher Education
Assessment, Selection and Placement Centre
Practical UOE Guidelines
Note to the reader: Most of the information that have been used to this report were collected
from the various department of MoNE and the authors would like to thanks all the persons
from the MoNE that have spent time during meetings and interviews to present the various
tools and to answer questions. They were complemented by the analysis of printed
documents.
EXECUTIVE SUMMARY
The objective of the Practical Guidelines is to “explain the methodology for adaptation of EU
norms and standards to MoNE”, in order to assist the suppliers of data for the joint data
collection for education Statistics from UNESCO, OECD and Eurostat (UOE). It discusses
how the concept and definitions used by international organisations should be interpreted in
the context of the Turkish education system, how the BI tool used by MoNE users aligned
with UOE standards and how the education Statistics in Turkey is used to fill in the UOE
questionnaires. It also gives recommendation regarding the use of estimation methods,
when needed to answer the UOE data request.
It has been agreed that this PG deals with issues related to the UOE data collection only.
The PG is considered to include sections on how to produce education indicators in
connection with UOE data routines or other relevant sources or routines in Turkey.
The PG is meant to be a living document. It should be updated when changes occur in the
educational Statistics framework in Turkey or internationally.
The objective of the joint UNESCO-UIS/OECD/EUROSTAT (UOE) data collection on
education Statistics is to provide internationally comparable data on key aspects of
education systems, specifically on the participation and completion of education
programmes, as well as the cost and type of resources dedicated to education. The UOE
data collection is presented in this PG.
The international manuals, mainly the UOE and ISCED manuals, are comprehensive and in
most parts quite clear. However, they need to be interpreted/ adopted to the Turkish context.
Some important UOE concepts are discussed in this DPG, for example formal/non-formal
education.
The coverage of the Turkish UOE submission is very important and a large part of this DPG
is about coverage and quality issues. It is believed that there is currently an under coverage
in the Turkish UOE data collection.
As the chapter on UOE data submission on Turkey, the existing BI Statistical information
system is explained. Main resources of the BI, BI procedures, BI user guide to fill the UOE
tables and determine the national education Statistics are the main parts of the PG which will
be helpful for the data preparation and submission periods.
The chapter on estimations aims at providing theoretical as well as practical guidelines about
estimation methods. Estimation is becoming more and more important in the UOE data
collection framework. The UOE Manual states: Countries should make every effort to
provide complete data. As such they are strongly encouraged to make estimations of
missing or incomplete data. Recently in 2010, a specific project in Eurostat has been
developed in order to inventory all estimation methods in use by countries for the UOE
questionnaires completion.
ISCED 2011 has been adopted by the general conference of UNESCO. Despite TURKSTAT
is in charge of the overall implementation of ISCED 2011 in all Statistical sources, it is
essential that MoNE takes fully part in the implementation of ISCED 2011 revision. It is
suggested that both TURKSTAT and MoNE attends the various EU meetings that will drive
the implementation process of ISCED 2011. Accordingly, the existing 4+4+4 system and its
effects to the current system are also included within the PG
As a new ISCED is in the pipeline and Turkey like all other counties should prepare for the
new ISCED 2011. The ımplementatıon of ISCED 2011 ıs scheduled for 2014 wıth a lot of
other changes expected in the UOE data collectıon.
Section A.
INTRODUCTION
The UOE data collection is an annual data request organised by the three international
organisations (UNESCO, OECD and Eurostat) together. It is launched in May-June and the
data are requested to be submitted to the international organisations not later than 30
September. The practical guidelines (PG) are meant to give recommendations and guidance
on how to apply the UOE concepts and definitions in the UOE data submissions for Turkey.
It is also meant as a tool for users of the Statistics presented by international organisations
to better understand how the underlying data for Turkey are reported. It is important to
understand how the Turkish education Statistics is used internationally. International
comparisons of education systems using Statistical indicators are common already today
and will surely increase in the future. Knowledge of Statistics and educational concepts are
necessary for everybody (both data providers and data users) involved in international
education Statistics in order to properly understand how international education Statistics is
compiled and used.
This PG draws heavily on the two reports 2.1.5 (Methodology Analysis Report) and 2.1.10
(Data Collection and Dissemination Analysis Report). Data processing issues are dealt with
in an: IT Analysis & Design Report. The reports 2.3.2 Training Needs Analysis Report and
2.7.3 Prioritized Indicators have also been used.
References are made to these reports and also to international documents and manuals,
mainly the UOE manual, the ISCED manual and the Eurydice report.
1
CONTENT OF THE PG
The main users of the PG will be data providers and also users who need to understand
better the international concepts and definitions. The PG is also meant as a tool for users of
the Statistics presented by international organisations to better understand how the
underlying data for Turkey are reported.
It has been agreed that this PG deals with issues related to the UOE data collection only. It
is considered to include sections on how to produce education indicators in connection with
UOE data routines or other relevant sources or routines in Turkey. As the chapter on UOE
data submission on Turkey, the existing BI Statistical information system is explained. Main
resources of the BI, BI procedures, BI user guide to fill the UOE tables and determine the
national education Statistics are the main parts of the PG which will be helpful for the data
preparation and submission periods.
The data collection routines for higher education are not in the scope of the project. Only
some guidelines on the UOE reporting of higher education will be included in the PG. For the
UOE data collection on higher education there is cooperation between MoNE and the
Council for Higher Education (YÖK). YÖK fills out the UOE questionnaires. YÖK and MoNE
together verify that the data are consistent.
All UOE data for Turkey provided to UNESCO/OECD/Eurostat are sent by MoNE.
It should be underlined that all Turkish data sources used for UOE are administrative. There
are at present no sample-based surveys designed for collecting data within the UOE
framework for Turkey.
The PG is meant to be a living document. It should be updated when changes occur in the
educational Statistics framework in Turkey or internationally. It should be noted that this
current DPG is to be considered as a first draft. A three day workshop, tentatively planned
for the beginning of February, will discuss and elaborate the issues raised in the DPG. All
decisions made in creating the data processing system for the Turkish UOE data collection
must be documented and added to the PG.
It should also be noted that when a country wants guidance on how to interpret the UOE
manual, they can always contact OECD or Eurostat with their direct questions. MoNE is
recommended to include the answers to such questions in the PG.
2
PURPOSE AND SCOPE
The objective of the Practical Guidelines is to “explain the methodology for adaptation of EU
norms and standards to MoNE”, in order to assist the suppliers of data for the joint data
collection for education Statistics from UNESCO, OECD and Eurostat (UOE). It discusses
how the concept and definitions used by international organisations should be interpreted in
the context of the Turkish education system, how the BI tool used by MoNE users aligned
with UOE standards and how the education Statistics in Turkey is used to fill in the UOE
questionnaires. It also gives recommendation regarding the use of estimation methods,
when needed to answer the UOE data request.
Section B.
1
1.1
THE UOE DATA COLLECTION
GENERAL PRESENTATION OF THE UOE DATA COLLECTION1
OBJECTIVES
The objective of the joint UNESCO-UIS/OECD/EUROSTAT (UOE) data collection on
education Statistics is to provide internationally comparable data on key aspects of
education systems, specifically on the participation and completion of education
programmes, as well as the cost and type of resources dedicated to education.
The data collected are covering the following subject tables: enrolments, entrants, class size,
graduates/graduations, personnel and finance. These tables are common for all three
organisations; they also include two alignment tables PERS-ENRL2 and FINANCE-ENRL2.
In addition Eurostat collects data on language learning and regional data. These tables are
also part of the data collection but are only used by Eurostat.
The UOE data collection on education systems is a so-called output harmonised source
meaning that it brings together a number of different sources at national level in order to fulfil
data needs at international level. This implies that the data are often transformed to fit
international standards (in particular following ISCED).
The UOE data sources are to a large degree administrative registers/information of different
sorts used for Statistical purposes. Information provided for the administrative sources are
often given by education institutions. Some sample surveys may also be used; and a recent
methodological work showed that data estimations are used to some degree.
1.2
ORGANISATION
The UOE data collection is administered jointly by the United Nations Educational, Scientific,
and Cultural Organisation Institute of Statistics (UNESCO-UIS), the Organisation for
Economic Co-operation and Development (OECD), and the Statistical Office of the
European Union (EUROSTAT). These are referred to as the data requesters.
Participants of the UNESCO-UIS World Education Indicators project (for simplicity, we will
henceforth refer to them as WEI participants) complete instruments very similar to the UOE
instruments. However, WEI deviations from the UOE core data collection do exist, and are
indicated in the UOE guidelines. Altogether, over 60 countries world-wide now complete the
UOE or WEI electronic questionnaire.
1.3
WHO IS RESPONSIBLE FOR WHAT AT INTERNATIONAL LEVEL?
OECD is responsible for the collection and processing of data submissions from OECD
countries as well as non-OECD countries that have joined the INES programme.
1
Information of this section are based on/taken from the UOE manual volume 1 and Commission Regulation
as regards Statistics on Education and Training Statistics - Explanatory note provided by Eurostat during its
training session.
Eurostat is responsible for the collection and processing of data submissions from EU, EEA
and candidate countries that are not OECD member countries unless they have joined the
INES programme (in which case, they shall be under OECD responsibility).
UIS is responsible for the collection and processing of data submissions from WEI
participant countries.
Turkey is an OECD country and an EU candidate country: As a result, Turkey should send
back the completed Excel questionnaire to OECD.
Turkey is of EU relevance: as a result Turkey should also send the EU specific
questionnaires and tables (language and regional data).
1.4
REFERENCE
YEAR ,
TIMELINE
AND
SUBMISSION
OF
ALL
UOE
QUESTIONNAIRES
Reference Year
The UOE data collection is always organised according to the same principles. To be selfexplanatory, the following will show the example of the UOE2011 data collection. During
year 2011, questionnaire (labelled 11ENRL, etc.) were sent by data requesters to countries.
This 2011 data collection collects data on the following reference year:

The school / academic year 2009/2010. The reference is then the academic year
2009/2010 for all tables of the data collection:
Except:


The reference is calendar year 2010 or school/academic year 2009/2010 at the
convenience of the country for graduates;
The reference is financial year 2009 for data on expenditure.
Timeline
The following timeline is followed by the data collection:
Questionnaires
Enrolment, Entrance, Finance,
Graduates, Personnel, Class
size, Demography, ISCED
mapping
UOE 2011 Ad Hoc module:
Educational personnel
categories
EU specific questionnaires
and tables*: Foreign
Languages, Regional
Enrolment, Graduations
according to the BachelorMaster structure,
*: only for countries having EU
relevance
Deadline for data
providers to return
the completed
questionnaires
30 September of
the data collection
year (2011 in our
example)
Where to send questionnaires
Deadline
for
data requesters
to
complete
validation
estat-uoe-joint@ec.europa.eu
https://webgate.ec.europa.eu/edamis
December
2011
30 September of
the data collection
year (2011 in our
example)
estat-uoe-joint@ec.europa.eu
https://webgate.ec.europa.eu/edamis
Submission
The completed data collection questionnaires are to be sent to the data requesters in
electronic form only. The questionnaires can be sent by:

e-mail to a unique address estat-uoe-joint@ec.europa.eu, which is managed by
Eurostat on behalf of the three data requesters, are then forwarded to all data
requesters.

via eDAMIS UOE data providers in EU Member-States are requested to use
eDAMIS. eDAMIS (electronic Data files Administration and Management Information
System) is the Eurostat standard system to exchange data files. It guaranties secure
(encrypted) transmission of all data and offers services such as traffic monitoring,
acknowledgements and reminders. It can be accessed via the web in the following
address: https://webgate.ec.europa.eu/edamis. All data submitted via eDAMIS are
automatically forwarded to all data requesters. UOE data providers in countries
outside of the EU can also send the questionnaires via eDAMIS.
OR
Currently, Turkey is sending the Turkish data via the e-mail address: estat-uoejoint@ec.europa.eu. In the future eDAMIS might be used.
1.5
INSTRUMENTS: UOE QUESTIONNAIRES AND GUIDELINES
The UOE data collection is made up of two categories of instruments: the questionnaires
(MS Excel format) and the UOE methodological guidelines (MS Word format).
The UOE questionnaires
The MS Excel questionnaires are the following: ENRL, ENTR, GRAD, CLASS, PERS,
FINANCE, ISCMAP97-11, DEM and the Eurostat questionnaire: LANG, REGIO.
At this stage ISCMAP97-11 could be considered as transitional in its form. However, the
ISCED mapping will be part either of the UOE data collection or the quality reporting
framework in the future.
The questionnaires are available at:
http://circa.europa.eu/Public/irc/dsis/edtcs/library?l=/public/unesco_collection&vm=detailed&sb=Title
The UOE methodological guidelines
The UOE methodological guidelines are set out in three manuals:
1. UOE data collection on education systems, Volume1, Manual, Concepts,
definitions and classifications;
2. UOE data collection on education systems, Volume 2, 20XX UOE questionnaires
and instructions for their completion and submission;
3. 20XX UOE data collection on education systems, Volume 3: Electronic
questionnaires: User guide.
All these three manuals are sent in electronic format by data requesters when the data
collection is launched. They are also available at:
http://circa.europa.eu/Public/irc/dsis/edtcs/library?l=/public/unesco_collection&vm=detailed&sb=Title
The content of the UOE data collection may change slightly between years, but the core
tables are normally the same. The manuals are usually updated annually. The adoption of
the revised International Standard Classification of Education (ISCED 2011) will cause a
major revision of both the UOE questionnaires and the UOE methodological guidelines.
Indeed, as a result of the implementation of the ISCED 2011, the UOE questionnaires will be
revised considerably for the data collection 2014, i.e. for the reference year 2012 or the
school year 2012/2013 and onwards.
Apart from this major future revision, it is highly recommended to verify the changes in the
UOE manual by comparing the current version with the version for the previous year by
using the tool for comparing documents in e.g. Microsoft Word.
The UOE manual for the 2011 data collection has been translated to Turkish. According to
national experts the translated version suffers from limitations. For many of the concepts the
corresponding terminology in Turkish may not be precise enough to explain properly what is
meant to a person not familiar with the international concept. Therefore it is recommended to
work with the English terminology for the international reporting to avoid misunderstandings
regarding the concepts.
1.6
THE CONTENT OF THE UOE DATA COLLECTION
Since March 2011 there is an EU regulation defining which UOE tables should be mandatory
for EU countries and which are considered optional. The data specified as mandatory in the
regulation should be considered to be highest priority also for Turkey since they will be part
of the Acquis in Statistics.
Indeed, the “COMMISSION REGULATION (EU) No 88/2011 of 2 February 2011
implementing Regulation (EC) No 452/2008 of the European Parliament and of the Council
concerning the production and development of Statistics on education and lifelong learning,
as regards Statistics on education and training systems”2 details:

The title of each table to be completed (specifying if the table is mandatory or
optional);

The breakdowns and their specifications.
A detailed list of the UOE tables is given in annex 1; if they are mandatory or not and if
Turkey filled in the table in the 2010 UOE data collection.
1.7
USERS
The UOE data are used extensively by the international organisations collecting them. UISUNESCO uses them in their reporting regarding global education Statistics; UIS runs a
separate but UOE compatible data collection at world level. OECD has for many years used
the data in their annual publication 'Education at a Glance' (EaG) and the success of the
2
Available at:
http://circa.europa.eu/Public/irc/dsis/edtcs/library?l=/public/education_Statistics_1&vm=detailed&sb=Title
data collection can to a large degree be contributed to the voluntary commitment of countries
to provide data for this publication.
Eurostat also uses the data extensively, - and many indicators are published on the Eurostat
website. Data are used in specific publications covering education, training and lifelong
learning as in the Key data series elaborated by and with Eurydice (DG EAC), DG EAC's
progress reports, - recently a publication has also been published in regard to the Bologna
process for Higher Education. Besides this, Eurostat publishes Statistics and Data in Focus
as well as data in compendium publications as the yearbook, the regional yearbook and
different pocket books.
Main users of the data at EU Commission level are DG Education and Culture, DG
Employment and DG Research and Development. There is also extensive co-operation with
CEDEFOP, as well as with other EU agencies.
In Turkey, potential users are:

Central Bodies: President, the Prime Minister and the Board of Ministers, Ministries
and Ministers. In the MoNE, various stakeholders are users of Statistics: the Main
Service Units3, the Advisory and Supervisory Units, the Inner Inspection Unit, the
Auxiliary Units and the Permanent Boards;

Provincial and local bodies: Provincial national education directorate, district national
education directorate;

Educational institutions (managers and teachers);

Researchers;

Media and general public (including parents).
1.8
ORGANISATION OF THE UOE DATA SUBMISSIONS FOR TURKEY
The MoNE is coordinating the UOE data collections for Turkey and is also responsible for
submitting the data to UNESCO/OECD/Eurostat. Within MoNE, the SDP is the contact point
for the data requesters and the coordinator at national level of the UOE data collection.
Thus, the SDP coordinates with ‘institutions’ outside MoNE and other department within
MoNE.
Outside MoNE:

SDP coordinates with TURKSTAT regarding the classifications;

SDP coordinates with YÖK/ÖSYM for data on higher/tertiary education. The data
delivered by YÖK/ÖSYM to MoNE are delivered in the same format as the UOE
tables. MoNE and ÖSYM usually have meetings to clarify the content, changes
compared to previous year etc. The UOE format is the agreed default standard for
exchange of data for the UOE between MoNE and ÖSYM, which is considered a
good practice. As MoNE and ÖSYM data never overlap each other in the same
columns of the UOE data collection, the ÖSYM data can easily just be pasted into
the corresponding file for the whole country. It should be noted that the international
3
According to the Law on Organization and Duties of Ministry of National Education; Article 9
organisations pay much attention to the data for higher education, and in many cases
the data collection instruments have more detailed tables for the higher education.

SDP coordinantes with other ministries when they manage educational insitutions
(see section 3.6).
Within MoNE:
 SDP coordinates with Egitek which collects the administrative data and perform the
MEIS queries which results are provided to SDP.
1.8.1 PARTICIPANTS IN THE UOE DATA COLLECTION IN TURKEY
The purpose of table 1 is to detail the name, institutions, role and email address of all the
persons participating in the UOE data collection in Turkey. It is suggested to provide only the
contact points in each institution. In order to guarantee the sustainability of the data
collection process in Turkey, it is advised to update regularly the information provided in this
table.
It is recommended to maintain the current organisation structure for the UOE data
submissions, with one unit (i.e. SDP) being the main responsible and also the contact point
for communication with Eurostat, OECD and UNESCO regarding the data submissions.
From an organisational perspective, the main responsible unit (i.e. SDP) should also:
 Encourage having regular briefings with other data suppliers to verify that the
concepts and definitions defined in the UOE manual are applied correctly;
 Provide to all other data suppliers a clear timetable of the UOE timeliness constraints.
From a methodological perspective: the main responsible (i.e. SDP) also has to take on
the task to verify that the contributions to the data collection from other units are complete
and don’t overlap with other contributions. Thus, it should develop the dissemination of UOE
methodological manuals to other relevant data suppliers. Such dissemination of UOE
methodological manuals is especially important for the FINANCE data for which it is
important to verify the coverage to avoid double-counting, and to verify that overhead costs
are included correctly.
From a practical perspective:
As the source for the data are live databases it is important that routines are in place to
extract the necessary data for the reference date for the UOE. This has to be defined and
performed in cooperation with Egitek, but also with sources outside the MoNE (section 3.6).
The reference date has to be agreed between the units responsible for different parts of the
IT systems. It is recommended to use the same reference date as for the national Statistics.
Even if another part of the organisation is responsible for the private institutions, compiling
the data may still be the tasks of the same IT function as for other education. The same may
be the case for what is nationally called “non-formal” but internationally called “formal” and
requested in the UOE.
Table 1: PARTICIPANTS IN THE UOE DATA COLLECTION IN TURKEY – Year 2012
MODULE
IT Staff
SDP Staff
Institutions
Şima Köprü
Bayram Taran
Hilal Kaya
Sadiye Budanur
Yasemin Kireçci
Formal
Education
Mete Han Keleş
Murat Uçar
Bülent Turhan
Özlem Beyazpirinç
Turgut Özkılıç
Pension,
Scholarship
Mete Han Keleş
Murat Uçar
Gülçin Tuncer
Yurdanur Öktem
Ayşegül Çabuk
Open Schools
Erdem Yıldız
Fazıl Aydemir
Murat Uçar
Turgut Özkılıç
Fatma Canagir
Serap Konuk
Pesonnel Data
Gülçin Tuncer
Emine Uçar
Bayram Taran
Cengiz Saraçoğlu
Yasemin Kireçci
Sadiye Budanur
Finance Data
Metin Çetin
Tarık Tosun
Dilek Güleçyüz
Hümeyra Altuntaş
Nilgün Çalışkan
Non-Formal
Education
İbrahim Ediz
Özgür Türk
Devrim Çelik
Ayşegül Çabuk
Serap Konuk
Neşe Bolkol
UOE Tables
Hilal Kaya
Mete Han Keleş
Özgür Türk
Filiz Alan
Dilek Güleçyüz
Hümeyra Altuntaş
Hulusi Yamuk
Fatma Canagir
Asuman Oral
Şule Karadavut
Nilgün Çalışkan
Osman Yıldırım
Bilal Aday
Cengiz Saraçoğlu
2
UOE CONCEPTS IN THE TURKISH CONTEXT
The international manuals, mainly the UOE and ISCED manuals, are comprehensive and in
most parts quite clear. However, they need to be interpreted/ adopted to the Turkish context.
The international manuals do not cover everything. In some cases Turkey needs to make
decisions from their own perspective. Such decisions should be documented in the PG.
Some important UOE concepts are discussed below; please see also section 3 on coverage.
The two main stakeholders in education Statistics in Turkey, MoNE and TURKSTAT should
both take part in the international cooperation on education Statistics. One representative
from MoNE and one from TURKSTAT should participate in both Eurostat WG meetings and
INES meetings. This is important if Turkey wants to improve its international reporting and
thus be more present/visible in the international publications on education. Most of all it is
important to ascertain that the Turkish interpretation of the UOE and ISCED concepts is
applied correctly.
2.1
2.1.1
ISCED CLASSIFICATION AND IMPLEMENTATION IN TURKEY
DIVISION OF THE TASKS IN TURKEY
The implementation (e.g. in the case of ISCED 2011) and the follow-up in the use of the
ISCED classification should show a clear definition of the division of the tasks at national
level. In Turkey, it involves two institutions: the national Statistical institute (TURKSTAT) and
the ministry of national education (MoNE)4.
The role of ISCED and the ISCED mapping: overview
The data collection and dissemination report and the methodological report detailed the role
of the ISCED classification and the role of the ISCED mapping in the UOE data collection.
It is thus clear that the ISCED mapping is an essential tool to ensure the compliance towards
the UOE methodology. It especially allows documenting the transition (and the transcodification) from datasets collected for national purposes toward the UOE questionnaires. It
will also allow a better monitoring of the implementation of ISCED2011.
In addition the ISCED 2011 emphasises the link between educational programmes and
qualifications, suggesting that both components of the ISCED mapping (former ISCMAPPROG and ISCMAP-QUAL) are important.5 6 7
4
The division of the tasks within Turkey relate to the institutional organisation. This section only provide
suggestions on this issue.
5
ISCMAP-PROG and ISCMAP-QUAL are the two components the ISCED mapping. Only ISCMAP-PROG is
available for the Turkish education system. Its reference year is academic year2004.
6
The UOE 2011 data collection adopted a transitory format for the ISCED mapping which differ from the past
versions.
7
Making the link between educational programme and qualifications would also allow clarifying national
information on educational attainment during the implementation phase of ISCED 2011. Indeed, Educational
attainment is a key variable in numerous social sample surveys (and especially the European Labour Force
Survey).
The role of TURKSTAT
TURKSTAT is in charge of the repository, the maintenance and the updating of
classifications. As such, TURKSTAT is in charge of the ISCED classification and other
classifications used in education Statistics (FOET, NUTS, etc.).
As the Statistical office, TURKSTAT is the national contact organisation for Turkey regarding
the implementation of the ISCED 2011taxonomy in all Statistical sources (incl. UOE data
collection and any other sources using the ISCED classification).
The implementation of the ISCED classification in data collection instruments is made
through the creation and maintenance of the ISCED mapping. TURKSTAT actively
participated in the revision of ISCED and sent comments to UNESCO and Eurostat during
the ISCED revision process.
The role of MoNE
The last ISCED mapping has been produced by MoNE and provides information for the
2004 reference year. After that this ISCED mapping was produced, classification
‘maintenance’ fell in the scope of TURKSTAT activities. Thus, TURKSTAT is in charge of the
ISCED classification but has not updated the ISCED mapping since then. From 2004
reference year onwards, subsequent UOE data collections have thus been processed
according to the last available version of the ISCED mapping.
The cooperation between TURKSTAT and MoNE
The implementation of the ISCED classification would benefit from a closer and more
formalised cooperation between TURKSTAT and MoNE on the basis of their respective
expertise. Here is what could be suggested once the basic mapping is produced:
On a yearly basis:

MoNE gathers the characteristics on the new curriculum/programmes that are
created during the reference year;

MoNE allocates new curriculum/programmes in an ISCED level and update the
existing ISCED mapping.

MoNE and TURKSTAT meet to discuss
curriculum/programmes in the ISCED level.

MoNE update the ISCED mapping that will be sent as a part of the UOE submission.
2.1.2
the
allocation
of
the
new
ISCED IN THE TURKISH CONTEXT : SCHOOL TYPES
At it has been mentioned in the data collection and dissemination report, in Turkey, the
national classification is based on the institutional arrangement. This includes the type of
schools. Indeed, educational institutions are categorised according school types and school
sub-types in the administrative data collection infrastructure. This could be considered with
caution when completing the ISCED mapping at national level.
Formal education
In Turkey, educational institutions are categorised according school types and school subtypes in the administrative data collection infrastructure. At this stage it seems that no
conceptual definition exists of what is called school-type and school sub-type. However, the
following information has been collected through discussions and meetings:
1.
School types and school sub-types are ‘concepts’ that have been developed
within Egitek for the collection of administrative information about schools (E-school
system). The purpose was to take into account the ‘real’ situation of the school
infrastructure (please see example below);
2.
School types and school sub-types are used by Egitek to identify the relative
situation of two schools regarding their implementation in existing infrastructure;
3.
The difference between school types and sub-types is not based on
conceptual issues related to education.
Example of school type and sub-type
Given two schools: School A and B.
School A is created and attributed an infrastructure. School A is considered as the
main school and thus as the main school type. School A has its own manager,
teaching staff and personnel. Later (or possibly at the same time), school B is created.
For any reasons (e.g. available infrastructure in school A), school B will:
•
use the existing infrastructure of school A or part of it;
•
have the same manager of school A; but each sub-type has a dedicated
deputy manager (most of the time).
•
have partly the same non-teaching staff as School A,
•
have possibly part of the same teaching staff and partly not as school A.
In the E-school system, school B will be considered as a school sub-type.
It follows that:

Using the same infrastructure and partly non teaching staff and teaching staff is the
main reason for considering types and sub-types.

Any type of school could be either a school type or a school sub-type so the relevant
Statistical unit is the school type.

A student is enrolled in one and only one school type.
From a practical point of view:

The list provided by Egitek contains 257 school types.

School types can at least be classified though E-school according to the following
dimensions: code, school type name, parentid, parent department name, national (in
Turkey's borders)/international, formal/non-formal, education level (primary, preprimary, upper secondary), public, private, open, general, vocational, educational
institute/administration level.
In order to “link” the structure of the administrative data collection (i.e. school types) with the
Statistical data to be provided through the UOE data submission. The following framework
applies:
Educational programmes and
characteristics
Types of schools
School type 1
Levels of education - ISCED 97
Levels of education - ISCED2011
A
Educational programme X1
School type 2
ISCED 01
School type 3
B
School type 4
School type 5
School type 6
ISCED 0
ISCED 02
ISCED level 1
ISCED level 1
ISCED level 2
ISCED level 2
ISCED level 3
ISCED level 3*
ISCED level 4
ISCED level 4*
ISCED level 5
ISCED level 5
ISCED level 6
ISCED level 6
C
Educational programme Xn
ISCED level 7
School type n
ISCED level 8
*
Content of category slightly changed
FIGURE 1: FRAMEWORK FOR THE ISCED MAPPING IN TURKEY
A. Different school types provide the same single educational programme;
B. Each school type provides a single educational programme;
C. A school type provides several different programmes: the unit for mapping is the educational
programme but each pupils should be coded according to the programme and not the school
type
When setting up the ISCED mapping, it should be clarified, which of the situation (A, B or C)
occurs in Turkey. This would help assessing the link between the institutional organisation in
Turkey and the ISCED classification. At this stage, it seems that such a link is more clearly
assessed for formal education than non formal education.
Moreover, it appears, but it should be confirmed by official data, that:

In pre-primary education: the most frequent situation is that a physical school
includes only one type (i.e. main type) – though some schools are pre-primary and
primary combined, and even in some cases vocational education for future childcare
professionals;

In primary education: the most frequent situation (always?) is that a physical school
includes only one type (i.e. main type). However, one must consider the various
stages differently that is the split between ISCED level 1 and 2. In potential ISCED
level 2, there could be general and vocational programmes.

In secondary education vocational and general type can coexist in the infrastructure
and thus combination of vocational and general school types exist.
We will make the assumption that there is no ‘school’ that overlap across levels. Each school
type (in the list provided by Egitek) is allocated to a single level, however many school types
could use the same infrastructure. This has to be considered when it comes to staff and
especially non teaching staff.
It is suggested that the Turkish ISCED mapping include the element as shown in the above
figure. It would then be adapted to meet the specific requirements of international UOE data
requesters. It should also be borne in mind that the name of the institutions and the
denomination of the programmes should not be used in priority to allocate a programme at
an ISCED level. The content of the programme is the main criteria.
Non-Formal education
Apart from the differences between international and Turkish definition of formal and nonformal education, it is clearly stated in the ISCED 2011 that “ISCED 2011 covers formal and
non formal educational programmes offered in any stages of a person’s life”.
As a result, the Turkish ISCED mapping should in any case include, at least part of what is
called non-formal education in Turkey.
It means that the same characteristics as the one provided by in the ISCED mapping for
formal education should be provided. These characteristics are listed in the annex 1 of the
methodological report.
Furthermore, in the new designed ISCED mappings, countries will have to define for each of
the programme if they are formal or non-formal in the international acceptance (i.e. as
defined in the ISCED 2011).
The classification of non-formal programme according to the ISCED classification is different
from the coverage of the UOE. Indeed, recent discussions between data requesters in the
framework of the implementation of ISCED 2011 and its impact on the UOE data collection
show that the data requesters will probably move to restrict the coverage of the UOE to
formal education.
ISCED mapping – useful links
As the ISCED mappings aims at improving the comparability of Statistical information across
countries, it could be suggested to consult the ISCED mapping of other countries when
classifying the Turkish programmes. Another tool to improve and assess the comparability of
the implementation of the ISCED is to participate in peer reviews.
Useful information i.e. other countries mapping are currently available in the public section of
the CIRCA website at:
http://circa.europa.eu/Members/irc/dsis/edtcs/library?l=/public/unesco_collection/programme
s_isced97&vm=detailed&sb=Title
The transitory version of the ISCED mapping (i.e. ISCMAP97-11) are available to the
restricted section of the CIRCA website.
2.1.3
IMPLEMENTATION OF ISCED IN THE UOE DATA
Regarding the implementation of the ISCED classification in the Turkish UOE submission,
the methodological report highlights the specific key issues that should be solved:

ISCED 1 and 2 and the single structure of the Turkish system;

ISCED 2 private preparatory programmes for some ISCED 3 programmes;

Private preparatory programmes to ISCED level 4 or beyond.
In addition; as mentioned earlier, the list of school-types provided by Egitek shows that
school-types are already classified according to their level of education (pre-primary, primary
and secondary education resp. Okul Öncesi, İlköğretim and Orta Öğretim), their orientation
(General or vocational resp. Genel and Mesleki), and the type of institutions (public, private
or open resp. Resmi, Özel and Açık)8.
However, this is valid for formal education but not for non-formal education. Indeed, Egitek
does not allocate non-formal education schools according to the following characteristics:
level of education and orientation.
2.2
FORMAL/NON-FORMAL EDUCATION
National Education Statistics is published in two separated volumes, one dedicated to the
so-called Formal education and the other to the Non-formal education. This illustrates how
important the distinction of formal/non-formal is from the national perspective in Turkey.
Within MoNE a DG is especially responsible for Non-formal education and is labeled “DG of
apprenticeship and Non formal Education”.
In the publications on National Education Statistics formal and non-formal education in the
Turkish sense are described, but even though such a description is given, no clear definition
is provided at the national level on what is non-formal education. At first sight, as the formal
definition specifies that it relates to “a certain age group”, non-formal could be seen as
educational programmes devoted to adults. However, the main responsible DG is labeled
“DG of Apprenticeship and Non-formal Education” and Apprenticeship is often part of initial
education. Moreover, it also cannot be deemed as second-chance programmes (even
though it covers citizens who have never entered the formal education system or are at any
level of it or have left at that level), as it includes programmes aiming at increasing personal
or professional development.
As a corollary, non-formal education is multi-faceted and therefore is difficult to encircle at
international level. This is quite problematic as “non-formal” has a precise meaning in the
international standards of education.
The ISCED classification and the UOE data collection as a whole cover both formal and nonformal education. Formal versus non-formal education and, by extension, qualification is of
prime importance at the international level: in the new version of ISCED (2011 version), a
8
Please note that these categories are not exclusive since open education could be, at least in theory, either
public or private.
special focus is on the fact that non-formal education can lead to formal certification/
recognition, impacting on the educational attainment of individuals.
In the Turkish data collection, the formal/ non-formal distinction has another meaning. It is
tempting to think that confusion with international meaning could lead to coverage issues.
Indeed the non-formal Turkish education is missing for a major part in the UOE data, and
also in the ISCED mapping of programmes as provided so far
This is problematic as in the UOE 2011 Manual, it is specified that “it is not stated explicitly
that UOE only covers formal education. Therefore it is suggested that the definition as
proposed in ISCED 2011 is used but applied to the scope of UOE (e.g. excluding
programmes of shorter duration than one semester, as defined nationally).
The international concepts of Formal and Non-formal Education
The definition of formal education as proposed by ISCED 2011 is the following:
Formal education is defined as education that is institutionalized, intentional, planned
through public organizations and recognized private bodies and, in their totality, makes up
the formal education system of a country. Formal education programmes are thus
recognized as such by the relevant national educational authorities or equivalent, e.g. any
other institution in co-operation with the national or sub-national educational authorities.
Non-formal education is defined as being not formal : “Non-formal education can be
alternative education paths that are not recognized by national authorities in education even
though they are generally acknowledged in society and lead to labour market relevant skills
(…) non-formal education can include learning activities pursued for self development, with
the purpose of acquiring knowledge or skills that may not be specifically job-related. The
ISCED 2011 Manual further states that “non-formal educational programmes do not
necessarily have a pathway structure and may be very short in duration, including less than
one day. However, programmes included in UOE must be equivalent to one half academic
year of full-time study”.
As stated in the ISCED 2011 document, such a formal recognition of skills or certifications
has a direct impact on the measure of educational attainment: “The educational attainment
of individuals is solely determined by formal education credentials and certificates. However,
in exceptions, credentials and certificates from non-formal educational programmes can be
explicitly recognized as equivalent to formal education certificates and as such, be a
pathway into formal education. In this case, they may be relevant to determine an
individual’s educational attainment”.
ISCED 2011 underlines that non-formal education does not normally give access to a higher
level of education unless it is appropriately validated in the formal education system and
recommends using the criteria of equivalency of content and/or of resulting qualifications for
the classification of non-formal education programmes: “for example, where a programme of
adult education satisfies the content-based criteria of ISCED level 1, it could be classified at
ISCED level 1” (ISCED 2011 draft Manual).
The official recognition by the relevant national authorities is also a key idea of the
conception proposed by the Classification of Learning Activities (CLA). According to that
classification (CLA Manual):
“There is one fundamental criterion that distinguishes Formal Education from Non Formal
Education. This is whether the activity is designed to lead upon successful completion to a
learning achievement that is possible to position within the National Framework of
Qualification (NFQ). The National Framework of Qualification (NFQ) is defined as “the
single, nationally and internationally accepted entity, through which all learning
achievements may be measured and related to each other in a coherent way and which
define the relationship between all education and training awards”.
However, as far as we know, there is no NFQ in the Turkish system yet, at least not for nontertiary levels of education (it will be developed in the near future, however).
Comparison with Formal and Non-formal in the Turkish sense
Turkish non-formal education “covers citizens who have never entered the formal education
system or are at any level of it or have left at that level, and which may accompany formal
education or be independent of it” (National Education Statistics: Non-formal Education,
2008/09). Moreover; one aim of the non-formal institutions is “to enable the participants to
acquire the same qualities as a student in formal education”.
From the latter sentence it can be assumed that, in the ISCED 2011 and CLA perspectives,
at least some of “non-formal” (in the Turkish sense) programmes could actually lead to a
formal recognition in terms of educational attainment. Indeed, if “same qualities” means
same outcomes in terms of skills acquired by the students, those students might get a
certification that is equivalent to the corresponding qualification awarded in the “formal”
education system. Moreover “there are some requirements according to the characteristic of
the program for certain age and educational levels”,meaning that a hierarchy that echoes
formal education may exist among those programmes.
According to Eurydice (Turkish national report, 2009/2010): “Recently acted, Law of
Institution for Vocational Qualifications (Meslekî Yeterlilik Kurumu Kanunu), No. 5544
envisages a framework of national vocational standards and curricula, education and
certification based on these standards to shape Turkish education system (both general
education and formal and non-formal vocational education)”.
As there most probably is an under coverage in the current Turkish UOE reporting it must be
checked which non-formal programmes should be added to the UOE data collection.
A recommendation here would be to set up a working group that would discuss –using the
criteria in the international manuals- on which “non-formal” programmes in the Turkish sense
may be decided to be included in the UOE data collection:
Educational Programmes
Formal
Non-formal
Turkish sense
Turkish sense
UOE
Non-UOE
Specific example: apprenticeship programmes
Some apprenticeship programmes at ISCED 3C deemed as non-formal in the Turkish
educational context should probably be recognised as formal in the international sense. In
such a case, those programmes if lasting more than 6 months (and less than 2 years)
should be reported in the UOE data collection, under the ISCED 352 level of education
(according to the new ISCED11 classification). The MEIS query could allow to isolate the
number of certificates (here some adjustments have to be made in order to get the number
of graduates, not the number of graduations). The e-non formal module would allow to get
the number of enrolees.
More specifically, in the Turkish non-formal education, there are some cases in
apprenticeship programs in which If some candidates working in the labour market with
Social security premium at least 6 months are considered as "on the job training
programme" and they can access the apprenticeship certificate. Those students work 4 days
a week in a company and attend scholl-based classes one day a week.
In the ISCED 2011 Manual, this kind of programme is regarded as Dual system educational
programmes and defined as Programmes that combine school - or college - and work-based
education. Both components are substantial (i.e. go beyond a single internship or occasional
class), although the work-based part usually occupies 50% of the programme time or more
(p. 4).
The table below summarises the different certificates and the corresponding ISCED level. As
a reminder, in the 3-digit coding of ISCED, the first digit means the broad ISCED level (here
upper secondary education, coded 3), the second the orientation (here vocational, coded 5)
and the last one the level completion, coded as follows:
351 insufficient for level completion or partial completion and without direct access to postsecondary non-tertiary or tertiary
352 sufficient for partial level completion and without direct access to post-secondary nontertiary or tertiary
353 sufficient for level completion, without direct access to tertiary [but may give direct
access to post-secondary non-tertiary];
354 sufficient for level completion, with direct access to tertiary [may also give direct access
to ISCED level 4]
As there is no ISCED level 4 programmes so far in Turkey, the code 353 is not applicable.
Certificate/Training
Çıraklık (Apprenticeship)
Usta (Craftsman)
Kalfa (Foreman)
ISCED level suggested
352
352
352
Usta Öğretici (Qualified Instructor)
352
İş Yeri Açma Sertifikalı Kursiyer (Trainees with business
352
licence certificate)
Some (non-formal) apprenticeships programmes to be included in the UOE tables, and
suggested ISCED level according to the new 2011 classification.
2.3
FULL TIME/PART TIME AND FULL TIME EQUIVALENTS
Both students and teaching staff data are requested by full-time status in the UOE data
collection. The indicators of students to teacher ratio are based on the reported full-time
equivalents (FTE) for both students and teachers.
According to information received all teachers in Turkey have a full-time employment, but
some may also have other duties than teaching. In UOE 2010 all Turkish students were
reported as full-time students. All teachers at ISCED levels 0-4 were full-time teachers and
only about one percent of the teachers in higher education (827 out of 100 504) were
reported as part-time.
MoNE is currently using the full time status for teachers (levels 0-3) in UOE datasheets.
Within the formal education, MoNE considers all students as full-time status. For some nonformal education, for example apprenticeship schools part-time status for students is
possible.
Using the criteria in the UOE manual MoNE should decide if changes in the current fulltime/part-time classifications of teachers (section 4.9 in the UOE Manual, Volume 1) and/or
students (section 4.8) are needed.
2.4
PUBLIC/PRIVATE INSTITUTIONS
In the UOE data collection, most of the provided data should be broken down by three types
of educational institutions: private independent, private government-dependent and public
institutions, each type being characterized by an increasing level of private management.
Educational institutions are classified as either public or private. Private institutions are
further classified between government dependent private and independent private
institutions, as shown in the following Figure.
Educational institutions
Public
Private
Government Dependent
Independent
The classification between public and private is made according to whether a public agency
or a private entity has the ultimate control over the institution. Ultimate control is decided with
reference to who has the power to determine the general policies and activities of the
institution and to appoint the officers managing the school. Ultimate control will usually also
extend to the decision to open or close the institution. As many institutions are under the
operational control of a governing body, the constitution of that body will also have a bearing
on the classification.
As a corollary an institution is classified as private if:
- It is controlled and managed by a non-governmental organisation (e.g. a Church, a Trade
Union or a business enterprise, foreign or international agency), or
- Its Governing Board consists mostly of members not selected by a public agency.
The source of funds is often erroneously considered as a determining criterion for classifying
an institution as public or private. However, the extent to which an institution receives its
funding from public or private sources does not determine the classification status of the
institution between public and private. It is possible, for example, for a privately managed
school to obtain all of its funding from public sources and for a publicly controlled institution
to derive most of its funds from tuition fees paid by households.
However, the terms “government-dependent” and “independent” do refer to the degree of a
private institution's dependence on funding from government sources; they do not refer to
the degree of government direction or regulation. A government-dependent private institution
is one that either receives 50 per cent or more of its core funding from government agencies
or one whose teaching personnel are paid by a government agency. An independent private
institution is one that receives less than 50 per cent of its core funding from government
agencies and whose teaching personnel are not paid by a government agency.
In Turkey institutional institutions are either fully publicly managed, or totally independent.
This is reflected in the UOE questionnaires sent so far by Turkey, where no data are
reported for the so-called “government-dependent institutions”. All private institutions receive
less than 50 per cent of their core funding from government agencies and their teaching
personnel are not paid by a government agency. Thus, no Turkish institutions are
recognised as being “government-dependent private institutions”. The reason is that
privately managed institutions don’t get any financial support from the government and the
teachers are employed by the institution. Therefore all private educational institutions in
Turkey shall be reported in UOE as “independent private”.
2.5
FIELDS OF EDUCATION AND TRAINING (FOET)
The availability of a common classification is only the first step towards the collection of
comparable data. The second step is to ensure a consistent application of the classification
across countries. Thus, it is the aim of the manual - adopted in 1999 - on FOET is to offer
clear guidelines on how to apply the classification for fields of education and training. The
FOET-99 is a three digit hierarchical classification. The classification contains 9 broad fields
(one digit), 25 narrow fields (two digits) and about 80 detailed fields (three digits)
hierarchically organised.
The classification of fields of education and training (FOET-99) aims at classifying
programmes according to fields of education and training for international comparability
purpose. “Fields of education and training” is defined as the subject matter taught in an
educational programme. The rationale of the classification for fields of education and training
is the subject content approach. The programmes are put together by closeness in subject
matter content. The programmes are aggregated to detailed, narrow and broad fields, based
on ‘knowledge closeness’. It must be emphasised that it is the main subject content of the
programme which decides into which field it should be classified.
Typically the classification of a programme or a degree by field of education and training is a
compromise depending on the number of hours used for different subjects and the type of
profession or labour market area the programme is preparing for. A pragmatic solution is
often to give priority to a labour market specialisation even if most of the instruction time is
used for “general” subject.
The FOET-99 classification and the FOET-99 manual are translated into Turkish and
available on the website of TURKSTAT. When a new programme is created, it is directly
coded according to the fields of education and training classification.
Fields of education are an important breakdown variable in the UOE data collection,
especially at the tertiary level of education. For lower levels, only ISCED 3 and 4 graduates
have to be provided by fields of education, for vocational qualifications (GRAD5 UOE table).
A national classification by field of education and training using the FOET manual has been
established in Turkey. According to TURKSTAT all national educational programs are coded
according to the codes of FOET-99 by three digit level. The official translation of national
classification into “Fields of Education and Training” (FOET) should be implemented in the
UOE. The list of fields used in the UOE data collection can be found in the relevant UOE
tables.
In Turkey all students in grade 11 and 12 are classified according to branch and sub-branch
and these are translated into FOET. Only for students in open high school this is currently
missing. They are classified by branch and sub-branch (not the same classification as for
other students) and these are as far as we know not yet translated into FOET. As Open High
School should be included in the UOE data collection it is needed to translate also these into
FOET. This could rather easily be done by a working group.
In tertiary education the Higher Education Board (YÖK) has national codifications for fields of
education. Detailed information on the FOET system in higher education is at present not
known to us. This will be added later if needed.
The same classification by field of education is used for all levels of education. The fields of
education are not defined within levels, but are independent of levels. It is recognised,
however, that not all fields appear at all levels.
Finally, it should be noted that it has been agreed that no assistance from the project is
needed concerning FOET.
3
COVERAGE OF THE UOE DATA COLLECTION IN
TURKEY9
It is worth noting the OECD evaluation of Turkey UOE quality for Education at a Glance
(EaG) 2011:
ENRL
ENTR
GRAD
FINANCE
PERS
3.1
Very good
Very good
Quite good
Very bad
Very good
THE SCOPE OF EDUCATION
The scope of education in the UOE data collection refers to the one displayed in the
ISCED97 classification10. In the ISCED, education is referred as “organised and sustained
communication designed to bring about learning”.11
It is clear from the UOE manual that the UOE data collection should cover “all of a country’s
domestic educational activity (i.e. within its own territory) regardless of:
-
ownership or sponsorship of the institutions concerned (whether public or
private, national or foreign) and
-
the education delivery mechanism”.
For Turkey, it implies that some of the organisational variations and alternative structures
should be included in the data collection.
At pre-primary education12:
9
Sources of this section are the UOE manual vol.1 section 2, the ISCED97 classification, the Eurydice report on
Turkey 2009/2010 and information provided by MoNE.
10
Available at: http://www.uis.unesco.org/Education/Pages/international-standard-classification-ofeducation.aspx
11
For a detailed description of these concepts, see UOE manual Vol.1, section 2.1.
-
Mobile Kindergarten (defined according to Regulation on Pre-primary Education
Institutions/Okulöncesi Eğitim Kurumları Yönetmeliği Ek Madde 2)
International Schools (defined in accordance with the Law of Private Education
Institutions Education (Özel Öğretim Kurumları Kanunu), No. 5580). International
schools exclusive for foreign students' attendance can be founded in Turkey.
At primary education in the Turkish sense13:
-
Yatılı İlköğretim Bölge Okulları (YIBO) (defined according to Primary Education
Law-İlköğretim ve Eğitim Kanunu, No. 222, Article 9);
Taşımalı Ilköğretim;
Açık Ilköğretim Okulu (defined according to Regulation on Open Primary Education
School-Açık İlköğretim Okulu Yönetmeliği, Article 5);
Private Minority Schools;
Private Foreign Schools;
Private International Schools: defined in accordance with the Law of Private
Education Institutions Education (Özel Öğretim Kurumları Kanunu), No. 5580. Only
pupils of foreign nationality are allowed to attend to these schools.
At secondary education14:
-
-
Distance Education: Open High School (institutions offering general education) and
Vocational Open High School and Vocational and Technical Open High School
(institutions offering vocational education);
Private Minority Schools;
Private Foreign Schools;
Private International Schools.
At tertiary level15:
-
Open Higher education (as defined by Regulation on Open Higher Education (Açık
Yükseköğretim Yönetmeliği))16.
As a reminder, UOE manual states that:
“Correspondingly, the coverage of the data collections should, – with the exceptions listed
below – extend to all types of students and to all age groups, to children (including children
classified as exceptional), young people, and adults (involved in programmes similar to initial
12
Eurydice section 3.15.
13
14
15
Eurydice section 6.18
16
This should be discussed in more details in section devoted to Higher education since “Turkish citizens that
live in 6 Western European countries and citizens of Turkish Republic of Northern Cyprus” since those students
should not be reported in the UOE data except in mobility (however, they will be reported by the host
country).
or “regular” educational programmes) who attend programmes or undertake studies which
fall into the categories described in this document”.
“However, the following types of education and training should be EXCLUDED:
•
Vocational and technical training in enterprises, with the exception of combined
school- and work-based programmes that are explicitly deemed to be parts of the education
system and that the school based component accounts for at least 10 percent of the study
over the whole length of the programme. However, specific instructions relate to the
coverage of personnel and expenditure related to the work component of school- and workbased programmes.
•
Entirely work-based education and training for which no formal education authority
has oversight. Correspondingly, all continuing training of employees by their employers
should be excluded from the Statistics that are reported.
•
Programmes of shorter duration than one semester, full time equivalent duration as
defined nationally. This applies to programmes specifically designed as adult education as
well as to any initial programmes of this short duration.” In Turkey this means for instance
that “Summer Schools” should be excluded.
For a discussion on non-formal programme, please see section 2.2.
4+4+4 Effects on the Education System
On the education Statistics side of the 4+4+4, the following assumptions can be considered
in MoNE-Stat Project aligned with UOE data collection.

The starting age of students for the primary schools will be changed. It means that
via 4+4+4 the lowest age limit will be 60 months not 72 months (previous one).
However, only for this year (2012-2013), the ministry decided that the starting age
will be 66 months. If their parents approve, the student within 61 and 66 months can
also start for the primary school. So, the related calculations in UOE will be changed
and therefore comparability between the previous years and the applied year will be
affected.

Extending the compulsory age at the lower limit would only have an impact when
information by single age (or age group) should be provided. Then when it comes to
indicators, this will have an impact for instance on participation rate by age.
Indeed the enrolments, graduates and schooling rates by ISCED level will probably
change and comparability affected (break in series), only if the number of grades
changes by ISCED level (for ex if students at age 6 to be included ISCED 1 in the
new future system).

The current ISCED 2011 mapping will be changed. Primary Schools 1-4 will be
ISCED 1 and Primary Schools 5-8 will be ISCED 2. Therefore, within the combine
schools we should spilt into ISCED 1 and 2 differently in our calculations which
require a minor change in the BI.

New schools will be opened aligned with the new system. Therefore, a major
difference in the number of schools is expected. Taking into consideration of the
previous year, the number of schools therefore will be affected.

The most important changes will be the destination of education programmes that it
will be re-designed. Therefore, the ISCED level 3 will be changed and the digits of
ISCED-2011 level will be affected.
Then there will probably be a reallocation of the population of pupils between general
and vocational due to the reallocation of programmes. The impact will probably be at
ISCED 2011, 2-digit level and thus as a consequence at 3-digit level.

New type of schools can be opened in ISCED 2 level (For example New Vocational
Schools in ISCED 2).This kind of new types should be considered in BI system. And
in some cases some school types can turn to different types. For example, some
vocational schools can be general schools. Or vice versa... In this case, it should be
considered in the BI system. Then there will probably be a reallocation of the
population of pupils between general and vocational due to the reallocation of
programmes. The impact will probably be at ISCED 2011, 2-digit level and thus as a
consequence at 3-digit level.

The number of personnel in ISCED Level 1 may not be affected highly from this
situation, all classroom teachers will be in ISCED Level 1 for the grades 1 to 4. The
programme for the fifth grade will be approximated to ISCED Level 2 programme,
since 5th grades would be evaluated in ISCED Level 2. However, it can be expected
that there may be at least 1/3 increase in the number of teachers in ISCED Level 2.
Moreover, the programme for the 6 to 8 grades will be the same until this generation
finishes ISCED Level 2. Then all programmes will be re-designed for ISCED Level 2
grades 5 to 8.

3.2
COVERAGE OF EARLY CHILDHOOD EDUCATION PROGRAMMES
Tables ENRL-1, ENRL-1a, ENRL-7 request data on pupils enrolled in early childhood
education programmes. For a discussion about ISCED level 0 programmes, please refer to
ISCED97 classification. Please note that ISCED2011 provides major changes regarding
ISCED level 017.
These changes should be implemented during the implementation phase of the ISCED 2011
classification as planned by data requesters.
3.3
COVERAGE OF “SPECIAL EDUCATION ”
All tables of the ENRL, ENTR, GRAD and PERS and (FIN_ENR2) questionnaires request
data on students and personnel involved in special education. However, students with
special needs should be excluded from the CLASS questionnaire.
17
Please see section 10 of the ISCED 2011 classification.
Please note that at this stage, no common definition of “special education” has been adopted
at international level so far, and it is difficult to conceive a methodology that would generate
consistent and comparable Statistics from countries. However, Eurostat is currently leading
some work to make this population more visible in Statistics and the UOE data collection.
Outcomes of this work will probably be available between 2012 and 2014 and implemented
in the UOE manual by that time.
In Turkey, special education has the following characteristics18:
 It can be either public or private;
 It can be through mainstream education or in separate special division.
3.3.1 Special needs students in mainstream education
Special needs pupils in mainstream education fall in two categories: those in full time within
the same class with their peers or those in part time within special education classes.
Special needs pupils in the same class with their peers on a full time basis should be
included in the all questionnaires except the CLASS questionnaire. They should be allocated
by grade in the table ENRL3.
The status of special needs pupils as part time within a special education classes is less
clear. İndeed, Eurydice states that “Part time mainstreaming practices are performed
through educating the students within the same classes with their peers without disabilities
or participation of students at extracurricular activities with their peers without disabilities
(Special Education Services Regulatiotn/Özel Eğitim Hizmetleri Yönetmeliği Madde 23)”.
However, the statement suggests that they are in special education classes on a part time
basis and are with pupils without disabilities also in part time basis.
1. The following students should be included:
a. Special Education Class (Primary Education) – Özel Eğitim Sınıfı(İlköğretim)
b. Inclusive Education (Primary Education) – Kaynastirma Eğitimi (İlköğretim).
c. Inclusive Education (Secondary Education) – Kaynastirma Eğitimi
(Ortaöğretim). From the current data (National Statistics – Formal education
2010-2011), it seems that special education classes do not exist in secondary
education, however Eurydice (section 10.6) says that “the individuals in need
of special education can either continue their secondary education with their
peers” which suggests that disable student attends mainstream secondary
education but not in the institutional form of ‘special classes’.
2. Students in special education classes should not be double counted: once in the
population without disability and once in the special class population
There were 13,015 pupils in primary education in special classes at primary level and 6,859
in upper secondary education during school year 2008-2009 (Turkey – UOE submission).
The National Statistics – Formal education 2008-2009 does not provide any data on special
18
Eurydice section 10.
classes (table 1.14). National Statistics – Formal education 2010-2011 provides the
information on enrolments in ‘inclusive education – primary education’ and ‘special education
class – primary education’ which account for respectively 84,580 and 1,8541 pupils.
It should be checked why pupils enrolled in “special education class – primary education”
cannot be allocated to each grade. However, according to 10Enrl_ENRL3, they only
represent 0.12 % of the population of pupils in primary education.
3.3.2. Separate special provision
The separate special provision in Turkey is organised according to the category of
disability19 and covers all levels of education:
3.3.2.1 Pre-primary education
Children aged between 36-72 months are accepted in the schools established for the
individuals in need of special education: Kindergartens within Special Education Schools
(Özel Eğitim Okulu Bünyesindeki Anasınıfları). This population should be covered by the
UOE data collection.
3.3.2.2 Primary education
At primary education, the following schools exist for each of the following groups: hearing,
visually and orthopedically impaired, the mentally retarded, autistic individuals, individuals
having inpatient treatment in the health institutions, gifted individuals:
o Primary School for the Hearing-Impaired (İşitme Engelliler İlköğretim Okulu);
o Primary School for the Visually-Impaired (Görme Engelliler İlköğretim Okulu);
o Primary School for the Orthopedic-Impaired (Ortopedik Engelliler İlköğretim
Okulu);
o Primary School for the Educable Mentally Impaired (Eğitilebilir Zihinsel
Engelliler İlköğretim Okulu)
o Training Center for Autistic Children (Otistik Çocuklar Eğitim Merkezi);
o Primary School for Children with Adaptation Problems (Uyum Güçlüğü Olanlar
İlköğretim Okulu);
o Mentally Impaired capable of Learning (Training Imp.School-Primary
Education)
(Öğretilebilir
Zihinsel
Engelliler
(Eğitim
Uygulama
Okulu)(İlköğretim));
o Mentally Impaired capable of Learning (Training Imp.School-Primary
Education)
(Öğretilebilir
Zihinsel
Engelliler
(Eğitim
Uygulama
Okulu)(İlköğretim).
All the above-mentioned schools at primary education should be included in the UOE data,
and it seems to be the case.
However, some information about the data collection routines regarding pupils with special
education needs is contradictory. On the one hand, it is stated that “Pupils with special
educational needs are also out of the scope of the modules but are collected once a year (by
19
other than the MoNE) and sent every year”. On the other hand, it is stated that pupils with
special education needs are included in the E-school modules.
Schools for “individuals having inpatient treatment in the health institutions” are not
mentioned in the Statistical book. It seems that they are not covered by the UOE data
collection. The nature of this category of institution should be assessed to reach a
conclusion towards the inclusion or not in the current UOE data collection.
3.3.3.3 Secondary education (i.e. upper secondary education)
The Eurydice report does not distinguish the categories of separated settings between
primary education and secondary education. However, the national Statistics book suggests
that the type of institutions differs between primary and secondary education.
There are three categories of schools covered by the national Statistical systems at
secondary level (i.e. upper secondary education):
o Vocational High School for the Orthopedic Imparied (Ortopedik Engelliler
Meslek Lisesi);
o Vocational High School for the Hearing Impaired (İşitme Engelliler Meslek
Lisesi);
o Vocational High School for the Educable Mentally Impaired (Eğitilebilir
Zihinsel Engelliler Meslek Lisesi).
All should be covered by the UOE data collection.
3.3.3.4 Specific cases
Science and Arts Center (for Talented and Gifted Childen)
Science and Arts Center (for Talented and Gifted Childen) (Bilim ve Sanat Merkezi
(Yetenekli ve Üstün Zekalılar)) are schools established for the gifted students at the age of
primary education and secondary education. From Eurydice it follows that “Gifted students
continue their education with their normal peers; however, these students are provided
education within Bilim ve Sanat Merkezi without hindering their education in the formal
education institutions (Directive for Science and Art Centers/Bilim ve Sanat Merkezleri
Yönergesi).”
As a result:
1. The students should already be counted in the formal education system at their level
of education (either primary or secondary education);
2. The student are currently classified in non formal education (Statistical book) which
avoid double counting;
3. In the list of school-type provide by Egitek, these schools are neither allocated to
formal and non formal. The consistency between the E-school system and the
‘decision’ made through the publication should be ensured. It is probable that the
Science and Arts Center (for Talented and Gifted Childen) (Bilim ve Sanat Merkezi
(Yetenekli ve Üstün Zekalılar)) should be allocated to non formal education in the IT
infrastructure.
Non formal education for special needs education pupils
As their peers, non formal education exist for special education needs children. Apart from
the Science and Arts Center (for Talented and Gifted Childen) (Bilim ve Sanat Merkezi
(Yetenekli ve Üstün Zekalılar)) mentioned in the above paragraph, the qualification of “non
formal” for these institutions should be challenged.
This is the case of the following institutions:

Mentally Impaired Capable of Learning (Vocational Training Center), Öğretilebilir
Zihinsel Engelliler (İş Eğitim Merkezi);

Vocational Training Center for Autistic Childen (Otistik Çocuklar İş Eğitim Merkezi).
Guidance and Research Centre (Rehberlik ve Araştırma Merkezi) are excluded from the
UOE data collection.
3.4
COVERAGE OF “ADULT EDUCATION ” AND “CONTINUING EDUCATION
All tables in ENRL, ENTR, GRAD, PERS, CLASS and FINANCE questionnaires include
adult and continuing education: “Students and personnel involved in adult education
programmes which are similar to initial (or "regular") education programmes should be
included (…). Since the 2005 data collection year, the specific tables ENRL-1_Adult and
ENRL-1a_Adult were introduced requesting separate reporting of data on students enrolled
in adult education programmes which are already reported in other tables.”20
Coverage of adult education and continuing education in Turkey raises the issue of formal
and non formal education21.
In Turkey, adult education and continuing education covers four categories of institutions22:
three of them are non formal education and one category is formal in the national
perspective:




Public non-formal educational institutions;
Open non formal education institutions;
Private non-formal education institutions;
Formal vocational and technical education institutions.
For all the above-mentioned categories, all of those listed in Eurydice (section 7.5) could be
screened and it should be decided which one should be covered by the UOE. It seems that
they are not covered currently.
3.5
COVERAGE OF VOCATIONAL AND TECHNICAL EDUCATION
All tables should report on students and personnel involved in vocational and technical
education. In Turkey, vocational and technical education exist both in formal education and
non formal education (in the national perspective).
20
UOE manual, vol.1, section 2.4.
21
Please see section 2.2 on formal and non formal education.
22
3.5.1 Vocational education in formal education
In secondary education, vocational institutions are23:








Teknik ve Endüstri Meslek Lisesi;
Kız Teknik ve Meslek Lisesi;
Sağlık Meslek Lisesi;
Otelcilik ve Turizm Meslek Lisesi;
İmam Hatip Lisesi;
Özel Eğitim Meslek Lisesi;
Çok Programlı Lise;
Mesleki ve Teknik Eğitim Merkezi.
Egitek provided a list of school type that include 74 school types that are vocational (public,
private and open) for upper secondary education. The discrepancy between the information
provided by Eurydice and Egitek is probably explained by the fact that from year 2009/2010
the number of school type has been decreased24.
The UOE data should cover all these institutions. It is advised to adapt the data collection
system to this new situation and add an additional aggregated level when listing the school
types.
3.5.2 Vocational education in non formal education
In Turkey, “non-formal education”, “adult education” and “continuing education” are clearly
inter-related and overlap. It seems that non formal education is always vocational education.
As a result, the decisions regarding formal and non formal education will probably impact the
UOE data in vocational upper secondary education. Once decisions have been made
regarding the allocation of non-formal Turkish programmes toward formal education in the
international perspective; current under-coverage of the UOE data collection could be solved
at least partially.
3.6
COVERAGE OF STUDENTS ENROLLED IN EDUCATIONAL INSTITUTIONS
ORGANISED BY MINISTRIES OTHER THAN THE MINISTRY OF EDUCATION
All tables from ENRL, ENTR, GRAD, PERS, CLASS and FINANCE questionnaires include
data on educational institutions organised by Ministries other than the Ministry of Education.
In Turkey, according to the data collection and dissemination report, the following categories
of institutions outside the Ministry of education exist:

Conservatories: information about primary education of the conservatories is
covered by the E-school module. Regarding secondary education provided by
conservatories, data are transmitted from YÖK. Data are covered and included in
Technical Secondary Education (Meslekî ve teknik lise (resmi));

Police College: Information is provided by the Ministry of Interior and included in
23
Eurydice section 5.5.2.
24
Eurydice section 5.5.2 paragraph 2.
Technical Secondary Education (Meslekî ve teknik lise (resmi);

Social Services and Child Protection Agency (SHÇEK): Data for pre-school
attendees is provided by General Directorate of SHÇEK. These data are covered by
Pre-Primary Education Statistics;

Education institutions under other Ministries established in the scope of Law
N°657 Art 191: the nature of these institutions as well as the level of education they
belongs to should be clarified in order to determine if the should be covered by the
UOE data collection;
3.7
COVERAGE OF FOREIGN AND MOBILE STUDENTS
All tables from ENRL, ENTR, GRAD, CLASS and FIN_ENRL2 questionnaires request data
on students that in all cases include foreign and mobile students25. It means that foreign
students enrolled in the Turkish education system should be covered by the UOE data
submission.
It should be specified that while all above-mentioned tables cover foreign pupils and
students, tables ENRL-7 and GRAD-1 ask data about foreign and mobile students and
especially at upper secondary level (i.e. Number of mobile and foreign students by level of
education, programme destination, EU/non EU/unknown membership and sex and Number
of graduates (ISCED 3 and 4) by level of education, programme destination, programme
orientation, type of institution, sex and by country of origin (usual residence or prior
education) and citizenship status).
Tables ENRL-6, ENRL-8, ENRL-9, and GRAD-3 ask for specific information on foreign
and/or mobile students at tertiary education.
The following specific cases should be considered distance learning, commuting students,
foreign campus and exchanges programmes.
3.7.1 DISTANCE LEARNING/E-LEARNING INVOLVING TWO COUNTRIES
In Turkey, distance education can be classified (as face to face education) in two
categories26:


Open High School (institutions offering general education) and
Vocational Open High School and Vocational and Technical Open High School
(institutions offering vocational education).
The courses and branches in these institutions are similar to curriculums in formal education.
Moreover, “Theoretical courses are executed by means of radio and TV broadcasts.
Furthermore, there are textbooks and visual educational materials drafted with the method of
25
For a definition of foreign and mobile students, see UOE manual vol.1 section 4.6. It should be mentioned
that Eurostat is currently working on improving the UOE mobility data for tertiary education. The outcome of
this work will probably imply a major change in the design of the UOE questionnaire as well as in the overall
methodology regarding learning mobility Statistics within the UOE framework.
26
distance study”. In addition “Education of applied courses is performed in designated
vocational institutions in the provinces during evening hours and weekends by means of
face-to face education”. This suggests that distance education (at primary and secondary
levels) does not involve or rarely involves student residing abroad.
However, at tertiary level27, the “Anadolu University conducts over 30 programs with three
faculties conducting distant education. More than about one third of the students who
continue to associate and bachelor’s degree programs in Turkey are students of these
faculties (about 800,000 students). Therefore distant education system has an important
place in supplying higher education demands within Turkish higher education system. Also
Turkish citizens that live in 6 Western European countries and citizens of Turkish Republic of
Northern Cyprus can benefit from these programs within these faculties.
It is clear from the UOE manual that “Students from country A who are enrolled with
institutions (distance learning) in country B (Turkey) but who remain residing in country A
should be reported in the Statistics of country B (Turkey) and not in the Statistics of country
A”.
For Turkey, it appears that beside those residing in Turkey and following distance education,
those “Turkish citizens that live in 6 Western European countries and citizens of Turkish
Republic of Northern Cyprus can benefit from these programs within these faculties”.
In addition non Turkish citizens who are enrolled in open higher education should also be
included in the UOE data.
It should be borne in mind that28 in the Eurostat REGIO tables “pupils/students should be
counted in the region in which they study and not in the region where they are resident”.
3.7.2
COMMUTING STUDENTS
As stated in the UOE manual commuting students (i.e. students who cross a national border
on a daily basis in order to follow an education in another country) enrolled in institutions in
Turkey but residing in country A should be reported in the Statistics of Turkey.
3.7.3
FOREIGN CAMPUS
“An institution in country A may have a campus or out-post in country B (i.e. a foreign
campus). Here country B should report the enrolments and finance for the foreign campus in
the same manner as it reports activities of its domestic educational institutions. The foreign or
mobile status of the students at these campuses should be determined as for all other
students.”29
In Turkey there are no foreign campuses (here, we do not consider international schools as
foreign campuses since institutional schools may not have an institutional link with an
institution abroad).
27
28
Eurostat - Data Collection on Foreign Language Learning and Regional Enrolment.
29
UOE manual, vol 1, section 2.7.
3.7.4
EXCHANGE PROGRAMMES
Students in exchange programmes that fulfil part of their studies at an educational institution
abroad but are credited at their home institution (i.e. Turkish institutions) should be excluded
from the enrolment Statistics of the host country and be reported only in the country of
original enrolment (i.e. Turkey).
Exchange programmes (or short-term postings) are characterised as normally lasting three
months (or one semester) and in all cases less than a full school year.
As a result:
 Students enrolled in Turkish institutions but being abroad through the Erasmus
programme should be included in the UOE data for Turkey;
 Students enrolled in institutions abroad but being in Turley through the Erasmus
programme should be excluded from the UOE data for Turkey.
3.8
COVERAGE OF PERSONNEL DATA
All tables from PERS-1, PERS-2 and Ad hoc Module questionnaires produce datasets
consist of data on the number of:

Instructional personnel (classroom teachers, teacher aides and teaching / research
assistants
 Professional support for students (pedagogical and academic support, and health
and social support)
 Management / quality control / administration (school level management, higher level
management, school level administrative personnel, and higher level administrative
personnel)
 Maintenance and operations personnel
There are two databases are used by the ministry to keep the records for the personnel.
Those databases are “e-staff public module” and “e-staff private module”. Both databases
are kept by the different units in the ministry and has its own roles.
In the production of UOE tables, following assumptions have been taken into consideration:

All personel recorded in the e-staff public module are assumed as fulltime personnel,

The personnel working in independent pre-primary schools will be assumed as full
time personnel in ISCED 0,

There are several assumptions regarding class teachers in accordance with their
codes in the databases,

There are also several assumptions for class teachers in schools for special needs
student.

There are also several assumptions used to seperate administrative personnel and
technical personnel in schools in the level of ISCED 1 and ISCED 2.
Furthermore, specific instructions relate to the coverage of personnel related to ISCED
levels please see technical documents provided along the project duration.
Data on personnel and on finance have in such cases are also adjusted according to the
same coverage. It means that the data on personnel should be compatible with data on
students.
3.9.
THE COVERAGE OF FINANCE DATA
Personnel involved in special education are also included in all tables of the ENRL, ENTR,
GRAD and PERS and (FIN_ENR2) questionnaires. Those data can be gathered through two
databases in which personnel records kept.
The preparation of the data on finance can be handled as a separate activity. Where finance
data refer to more than one ISCED level, or e.g. both general and vocationally oriented
programmes, the general recommendation is to allocate such costs to each ISCED category
proportionally to the number of students. Depending on data availability such estimations
can be made at the level of institution, but it would for UOE purposes be acceptable also to
apply the same distribution formula for the whole country. However, improved estimation
methods are always welcomed. For e.g. teacher costs the number of teachers or the
student/teacher ratio is probably a better base for distribution of the costs between ISCED
levels.
For the finance data it is important to review the coverage of each data source to avoid
duplication and verify that the coverage is consistent with the enrolment data. Otherwise if is
recommended to make a separate documentation of the differences between the ENRL1A
and FIN_ENRL2 tables.
3.9.1. FINANCE DATA IN UOE: OVERVIEW
In connection with lower levels of education (ISCED levels 0-3), FINANCE1 and FINANCE2
are the main UOE finance data tables to be filled in. Broadly speaking, FINANCE1 collect
data on funds while FINANCE2 relates to expenditure.
FINANCE1 collects data by source and type of transaction. As regards the source of
funding, four main sources are considered with a total of nine categories, each one with a
specific letter code:
F funds from international agencies and other Foreign sources /
G Governmental sources: expenditure of all levels combined /
C Central level
R Regional level
L Local level
P Private entities
H Households
E Enterprises and other private entities (including firms and religious institutions and other
non-profit organizations, but not educational institutions)
N: all sources (total)
Types of transaction are coded by a number. Both dimensions (source of funding and type of
transaction) are not fully crossed, that is not all transactions types have to be provided for all
sources (see Table 2).
FINANCE2 table covers expenditure on education. Letter codes are used to identify
educational institutions as follows:
A all types
X Public institutions
W Private institutions
Y Government-dependent (not in Turkey)
Z Independent
Table 2 – FINANCE1 UOE table: overview of requested data
Source of funds
Type of transaction
C
R
L G
Direct
expenditure
for
public
1
X
x
x
x
institutions
Direct expenditure for government2
X
x
x
x
dependent private institutions
Direct expenditure for independent
3
X
x
x
x
private institutions
Subtotal : Direct expenditure for
4
X
x
x
x
private institutions
Total: Direct expenditure for all types
5
X
x
x
x
of institutions
{of
which
direct
expenditure
5a
X
x
x
x
designated for capital}
{of
which
direct
expenditure
5b
x
designated for ancillary services}
{of which direct expenditure for R&D
5c
x
activities}
Intergovernmental
transfers
for
6
education
Transfers to regional governments
7
X
x
(net)
8
Transfers to local governments (net)
X
x
9
Total: Intergovernmental transfers
X
x
Scholarships and other grants to
10
X
x
x
x
students/households
{Of which: Public grants attributable
10a for tuition fees to educational
x
institutions}
{Of which: Public grants NOT
19b attributable for tuition fees to
x
educational institutions }
11
Student loans
X
x
x
x
12
Total: Financial aid to students
X
x
x
x
Transfers and payments to other
13
X
x
x
x
private entities
Total: Transfers and payments to the
14
X
x
x
x
private sector
Payments on goods requested directly
15
or indirectly by educational institutions.
F
H
E
P
N
x
x
x
X
x
x
x
x
X
x
x
x
x
X
x
x
x
x
X
x
x
x
x
X
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
16
17
18
20
(Purchasing IMPOSED by institutions.
)
Payments on goods not directly
needed for participation, purchasing
NOT
imposed
by
educational
institutions
Payments for private tutoring
Total: Payments for educational goods
and services other than to educational
institutions
Total: Central government expenditure
X
for education
x
x
x
x
x
x
x
x
x
X
x
Expenditure categories covered in FINANCE 2 are hierarchically organised as summarised
below (see also Table 3 for more details):
Total expenditure
 Capital expenditure
 Current expenditure
o Personnel expenditure
 Salary compensation
 Salaries
 Retirement
 Non-salary compensation
o Non-personnel expenditure
Table 3 – FINANCE2 UOE table: overview of requested data
Educational institutions type
A
X
W
Y
Z
x
x
X
Expenditure category
1
Compensation for personnel: Teaching staff
Compensation
for
personnel:
Other
5
pedagogical, administrative, and professional
personnel + support personnel
6
Total personnel compensation
x
Salaries (salary portion of amount shown on
7
6)
Expenditure
for
retirement
(pensions)
8
(retirement portion of amount shown on 6)
Other nonsalary compensation (portion of
9
amount on 6 expended for nonsalary benefits
other than retirement)
Total current expenditure other than for the
13
x
compensation of personnel
14
Total current expenditure
x
15
Total capital expenditure (excludes payments x
x
x
x
x
X
x
X
x
x
x
x
x
x
x
x
x
X
x
x
x
X
x
x
x
X
for debt service)
20
Total current and capital expenditure
x
x
x
x
X
21
Adjustments for changes in fund balances
x
x
x
x
X
22
Total funds: current and capital expenditure
PLUS Adjustments for changes in fund x
balances
30
of 20: Total expenditure for ancillary services
x
x
x
x
X
40
of 20: Total expenditure for R&D activities
x
x
x
x
x
3.9.2. DATA NEEDS IN ORDER TO OBTAIN UOE REPORTS
Necessary data in order to obtain UOE reports consists of the following items.
i.
Incomes of departments spend for education within the body of MoNE and
classification according to which income type.
ii.
Classification of transactions and payments for services acquired and goods (school
fee, registration fee etc ) for Departments spending for education within the body of
MoNE.
iii.
Classification of related expenditure transactions according to ISCED.
iv.
Classification, registration and matching of related expenditure transactions
according to ISCED, and which classification includes this matching according to
UOE reports.
Data mentioned above is necessary in order to obtain the UOE reports. First item is about
income transactions and second third and fourth items are about expenditure transactions.
Education expenses total, should include necessary classification information to be included
the related item. Collected data should be standard and it must be possible to compare with
the other countries.
Household contribution should included in UOE reports after matching transactions of
related income/expense of National Education Ministry classifications. Another module has
been generated within the scope of TEFBİS project in order to collect household data,
information to be collected by this module with sample surveys will be calculated for general
Turkey and classified then added to UOE reports.
UOE aims to determine the education expenses and finance. In this respect, distinguishes
the education finance according to type of institution who will supply the finance (exp:
government, private sector etc.) expensed are divided in to two pieces as direct education
expenditures and expensed made excluding the education institutions.
UOE finance types are grouped in four categories according to sources:
i.
Finance contributed to education by household and student
ii.
Finance supplied for education by public enterprises
iii.
Finance supplied for education by local and regional administrations
iv.
Finance supplied for education by private institutions
The truest data which MoNE can determine is the finance which was supplied by public
enterprises. But household, local administrations and private sector contributions are not
possible to determine now. Due to that reason the stipulated expense of general Turkey
Education and education finance values are less than their real values.
All the income and expenses of education institutions will be registered by the network
based central income / expense system which was developed within the scope of TEFBİS
project according to their sources.
Finances supplied by private institutions for education will be obtained by this system. By the
way determination of household expenses is also pro rate possible. Household expenses
obtained within the TEFBİS project will generate usable data. Finance supplied for education
by public enterprise and local administrations will be checked double and obtained the truest
net information by negotiating with Ministry of Finance and Ministry of Interior’s related
departments.
The important thing is not the data source but also the comparability of this information and
determination of list of service and goods related education. In this respect, how to classify
and match the UOE expenditures and finance are mentioned below.
3.9.3. STATISTICAL INFRASTRUCTURE AND COVERAGE IN RELATION TO THE
UOE DATA COLLECTION
The following table provide a more detailed presentation of the links between available
sources of information (in and outside TEFBİS) and the UOE questionnaires with their
dimensions.
TABLE
FIN_ENRL-2
CATEGORY





FINANCE-1




DATA SOURCES
TOTAL PUBLIC AND PRIVATE
INSTITUTIONS
PUBLIC INSTITUTIONS
ALL PRIVATE INSTITUTIONS
GOVERNMENT DEPENDENT
PRIVATE INSTITUTIONS
INDEPENDENT PRIVATE
INSTITUTIONS
e-school
CENTRAL GOVERNMENT
EXPENDITURE
REGIONAL GOVERNMENT
EXPENDITURE
LOCAL GOVERNMENT
EXPENDITURE
EXPENDITURE OF ALL LEVELS OF
TEFBİS, E-Bütçe, SAY2000
(MoF),
(Number of students with
coverage adjusted to Statistics
on educational finance by
level of education, programme
orientation, programme
destination, type of institution
and mode.)
(Education expenditures by





FINANCE-2








FINANCESUP-2



FINANCESUP-3


GOVERNMENT COMBINED
FUNDS FROM INTERNATIONAL
AGENCIES AND OTHER FOREIGN
SOURCES
PRIVATE EXPENDITURE
EXPENDITURE OF OTHER
PRIVATE ENTITIES
TOTAL PRIVATE EXPENDITURE
COMBINED PUBLIC, PRIVATE AND
INTERNATIONAL EXPENDITURE
EXPENDITURE IN PUBLIC AND
PRIVATE INSTITUTIONS (PUBLIC
AND PRIVATE SOURCES)
EXPENDITURE IN PUBLIC
INSTITUTIONS (PUBLIC AND
PRIVATE SOURCES) -CURRENT
EXPENDITURE
EXPENDITURE FOR ANCILLARY
SERVICES IN PUBLIC
PRIVATE SOURCES)
EXPENDITURE IN ALL PRIVATE
PRIVATE SOURCES)
EXPENDITURE IN GOVERNMENT
DEPENDENT PRIVATE
PRIVATE SOURCES)
SERVICES IN GOVERNMENT
DEPENDENT PRIVATE
PRIVATE SOURCES)
EXPENDITURE IN INDEPENDENT
SERVICES IN INDEPENDENT
GOVERNMENT EXPENDITURE FOR
DEBT SERVICE
INSTITUTIONAL EXPENDITURE
FOR DEBT SERVICE
TOTAL: EXPENDITURE FOR DEBT
SERVICE -- All payers combined
Expenditure for Research
Separation of expenditure on R&D
level of education and source
and type of transaction.)
TEFBİS, E-bütçe, SAY2000
(MoF),
(Education expenditures by
level of education, nature and
resource category.)
E-Bütçe, SAY2000, (MoF)
(Expenditure for debt service)
E- Bütçe, SAY2000, (MoF)
(Expenditure for research)
3.10. INTERNATIONAL STANDARD CLASSIFICATION OF EDUCATION 2011
(ISCED 2011)
3.10.1
OVERVIEW
On 10 November 2011, UNESCO’s General Conference adopted revisions to the
International Standard Classification of Education (ISCED), which is now the so-called
ISCED 201130. Since the adoption of the ISCED 2011, international organisation
(UNESCO-UIS, OECD and Eurostat) are piloting the implementation phase of the revised
classification. The implementation of ISCED 2011 will impact numerous Statistical sources:
social surveys (e.g. Labour force survey) and the data collection on education and training
systems (UOE data collection).
In various occasions, Eurostat has communicated on the organisation, the different steps
and the timetable of the implementation of ISCED 2011 in the European Statistical System
(ESS)31 as well as on what is expected from members of the ESS32. The implementation of
the ISCED 2011 will have a significant impact on the design and the content of the UOE data
collection since international data requesters take the opportunity of the implementation of
ISCED 2011 to reshuffle and streamline the UOE data collection33 34.
3.10.2
ISCED 2011: MAIN CHANGES
The purpose of this section is to present briefly the main changes between ISCED 1997 and
ISCED 2011. They are the following35:
 The new ISCED envisages a more formal process for overseeing the adoption of
ISCED including for example the possibility for countries to participate in peer review
processes – both as those reviewed and as those acting as ‘peers’ and providing
30
Available at: http://www.uis.unesco.org/Education/Pages/international-standard-classification-ofeducation.aspx
31
Numerous documents have been presented on this issue to the Education and Training Working Group (ETS
WG) organised by Eurostat.
32
ISCED 2011 is planned to be fully implemented in all ESS sources by 2014.
33
Eurostat, in cooperation with UNESCO-UIS and OECD has conducted a consultation of countries on proposals
to redesign the UOE data collection. Some issues have already been discussed during the INES Working Party
in Tallin in March 2012 and the ETS Working group held in Luxembourg in June 2012.
34
Eurostat proposals as well as prototypes for the design of the new UOE tables can be found on the CIRCA
network
35
This subsection is adapted from a presentation drafted by UNESCO-UIS which present an overview of the
main changes of the ISCED 2011 compared to the ISCED 1997 and the summary of the Expert Group meeting
on International economic and social classifications, New York, 18-20 May 2011
(http://unstats.un.org/unsd/class/intercop/expertgroup/2011/AC234-17.PDF).
advice to other countries. So far, Eurostat has already organised in December 2011
a workshop on the implementation of ISCED 2011 which was followed by a one day
peer review session36.

The final text includes a core glossary of around 70 terms.

ISCED 2011 has 9 levels which is two more than ISCED 1997:
o The coverage of ISCED is extended at the lower end (ISCED level 01) to
include programmes with an educational content designed for children
younger than 3 year olds, provided that the programme has an educational
content;
o The coverage of ISCED is more detailed at tertiary level which includes now 4
levels (ISCED 5 – Short cycle tertiary, ISCED 6 – Bachelor or equivalent,
ISCED 7 – Master or equivalent, ISCED 7 – Doctoral or equivalent). It is
considered that ‘Short-cycle tertiary’ is broadly equivalent to ISCED-97 5B
and ‘Doctoral and equivalent’ is broadly equivalent to ISCED-97 6. The former
ISCED-97 5A is sub-divided between ‘bachelor’ and ‘master’.

ISCED 2011 provides a more extensive definition of formal and non formal education
(§36 to 42);

The cross-classification variables that are used have been simplified compared to
ISCED 1997:
o Orientation (§53 to 55): the definition of vocational education is largely
unchanged (vocational content leading to a ‘labour market relevant
qualification recognised by the relevant national authorities’) and the
distinction between general and pre-vocational is dropped. For ISCED level 2
to ISCED level 5, the distinction is between ‘general’ versus ‘vocational’. In
addition, orientation applies to all tertiary programme (whereas it was not the
case in ISCED 1997) but with a different label: ‘academic’ versus
‘professional37’. The possibility of classifying ALL tertiary programmes (ISCED
6–8) by orientation (‘academic’ versus ‘professional’) is allowed for but not
specifically defined as we expect further inputs as a result of the revision of
the ‘fields of education’ classification - (to be undertaken in 2011-2013)
o Destination (§56 to 65): it has been replaced by the concepts of ‘level
completion’ and ‘access (to programmes at higher ISCED levels)’.

36
Educational attainment is now part of the classification and is directly related to the
concept of ‘successful completion’ of an educational programme and ‘completion’ or
‘partial completion’ of an ISCED level. Partial completion has been especially
considered to ease the classification of ‘sequential programmes’. The attainment
level is that of the highest ISCED level completed (and not of the highest programme
An additional workshop on the ISCED 2011 implementation is planned to be organised in December 2012.
37
At present, there is no internationally agreed definition of academic and professional orientations of
bachelor, master or equivalent programmes and qualification. Further input as a result of the revision of the
‘fields of education’ classification - (to be undertaken in 2011-2013) is expected.
successfully completed which may lead to qualifications which are insufficient to
count as level completion). Educational attainment levels are generally determined
by reference to the highest recognized (or formal) qualification obtained by an
individual. At levels where qualifications are not normally awarded (e.g. ISCED levels
0-2 and occasionally 3 or 4) other means need to be used to determine successful
completion of the programme (e.g. participation in all elements of the programme or
the right to access subsequent programmes). (§81 and alii.);

ISCED 2011 adopts a new coding system (§89 and alii.):
o The coding system distinguishes two parallel coding schemes: the coding of
programmes (ISCED-P) and the coding of educational attainment (ISCED-A);
o The coding systems is a 3-digit system:



Digit 1: ISCED level (0-8)
Digit 2: type/orientation
Digit 3: completion/access
3.10.3
38
CORRESPONDANCE TABLE BETWEEN ISCED1997 AND ISCED2011 38
Extracted from http://www.uis.unesco.org/Education/Documents/UNESCO_GC_36C-19_ISCED_EN.pdf (p 67-69).
3.10.4
TURKISH ISCED MAPPING
As detailed in section 2.1, the ISCED mapping plays a key role to assess the quality and the
international comparability of data on education and training systems and the comparability
of data in social surveys.
As mentioned, in the data collection and dissemination analysis report, “the role of the
ISCED classification is to classify programmes as clearly stated in the ISCED 199739 and
reinforced in the ISCED 2011 which declares “The basic units of classification in ISCED are
the national (and sub-national) educational programme and the related recognized
educational qualification” (paragraph 10).
The role of the ISCED mapping is reinforced in ISCED 2011. Indeed, paragraph 7 declares
that ‘ISCED 2011 rests on three components: (i) internationally agreed concepts and
definitions; (ii) the classification systems; and (iii) ISCED mappings of educational
programmes and related qualifications in countries worldwide.”
In addition the two subsequent paragraphs mention that “ISCED mappings are an essential
tool for organising information about national education systems, their programmes and
related qualifications in order to ensure the comparability of ISCED level information and to
support their interpretation for international Statistical purposes.” (paragraph 8) and that
“ISCED mappings ensure a transparent process of coding national educational programmes
and related qualifications into comparable categories for use in international Statistics by
linking the classification criteria to the properties of the educational programmes and their
related qualifications”(paragraph 9).”
Furthermore, the same report states that “It is thus clear that the ISCED mapping is an
essential tool to ensure the compliance toward the UOE methodology. It especially allows
documenting the transition (and the trans-codification) from datasets collected for national
purposes toward the UOE questionnaires. In addition the ISCED 2011 emphasised the link
between educational programmes and qualifications (above-mentioned paragraph 8),
suggesting that both components of the ISCED mapping (former ISCMAP-PROG and
ISCMAP-QUAL) are important”.40 41 42
39
Paragraph 17 of the ISCED97 classification clearly states that “The basic unit of classification in ISCED
remains the educational programme. Educational programmes are defined on the basis of their educational
content as an array or sequence of educational activities which are organized to accomplish a pre-determined
objective or a specified set of educational tasks. Objectives can, for example, be preparation for more
advanced study, qualification for an occupation or range of occupations, or simply an increase of knowledge
and understanding”
40
ISCMAP-PROG and ISCMAP-QUAL were the two components the ISCED mapping.
41
The UOE 2011 and UOE 2012 data collection adopted a transitory format for the ISCED mapping which differ
from the past versions.
42
Making the link between educational programme and qualifications would also allow clarifying national
information on educational attainment during the implementation phase of ISCED 2011. Indeed, Educational
attainment is a key variable in numerous social sample surveys (and especially the European Labour Force
Survey).
Some important work has been carried out by Turkstat in collaboration with the MoNE and
resulted in the following draft43 of the ISCED mapping of the Turkish education system
according to ISCED 2011.
43
The draft ISCED mapping will be changed after the 4+4+4 system will be applied in the education system.
010
not
applicabl
e
not
applicabl
e
Erken çocukluk dönemi
eğtimi (0-2 Yaş)
0
020
not
applicabl
e
not
applicabl
e
Okul öncesi eğitim (3-5 Yaş)
1
100
not
applicabl
e
G
İlköğretim (1-5)
1
100
not
applicabl
e
G
Müzik ve Bale İlköğretim
Okulu (1-5)
1
100
not
applicabl
e
G
2. Kademe Okuma-yazma
Kursu
2
244
not
applicabl
e
G
İlköğretim (6-8)
11
12
bis
No
0
14
14
bis
14ter
Programme specifically designed
for part-time attendance (Y/N)
Does the programme have a work based element?
(Y/N)
Programme specifically designed
for adults (Y/N)
17
18
1-2
1-2
N
o
No
No
Yes
No
Not compulsory
education.
22
No
not
applicable
35
1-3
1-3
N
o
No
No
Yes
No
Not compulsory
education.
0
2
not
applicable
100
6
5
5
N
o
No
No
Yes
Yes
Compulsory
education.
0
2
not
applicable
100
6
5
5
N
o
No
No
Yes
Yes
The programmes
are designed for
the students who
have talented
capabilities in
music and ballet.
Entrance
examination is
required.
Literacy
course
0
2
certificate
100
Yes
Yes
Primary
school
(grades 68)
1
3
Lower
secondary
education
school
diploma
244
No
No
Yes
Yes
Compulsory
education.
3
3
N
o
20
21
not
applicable
1
1
19
Enrolments
Theoretical starting age
ISCED-2011 level of qualification/educational
attainment
ISCED-97 level of qualification/educational
attainment
Code of credential in
ISCMAP-QUAL
Main diplomas, credentials and certifications
awarded
13
16
1
5
02
Early
childhood
education
(0-2 age)
PrePrimary
education
(3-5 age)
Primary
school
(grades 15)
Ballet and
Music
Primary
School
(grades 15)
1
2
0
Reported in the UOE
FINANCE tables (Y/N/P)
10
Reported in the UOE
data collection (Y/N/P)
5
Theoretical cumulative
years of education at
the end of the programme
4
Notes
Theoretical duration
of the programme
9
Minimum entrance requirement (ISCED level or
other) Please put 0 if no requirement
Access to higher educational level (NO/YES - if
yes, which level?)
Description name of the programme in English
National name of the programme
3bis
Notes on programmes
than span across ISCED
levels or sub-categories
ISCED-2011 level
3
2
Programme orientation (G/P/V)
ISCED-97 level
1
Programme destination (A/B/C)
Programme number (prog.<ISCEDlevel>.<number
within level>)
Year when the programme was created
2
3
24
2
244
not
applicabl
e
G
Açık İlköğretim (6-8)
Open
Primary
School
(grades 68)
1
3
Lower
secondary
education
school
diploma
244
1
5
3
3
N
o
Yes
Yes
Yes
No
2
244
not
applicabl
e
G
Konservatuar (6-8)
Conservat
ory
(grades 68)
1
3
Conservat
ory:
Lower
Secondar
y School
Diploma
244
1
1
3
3
N
o
No
No
Yes
?
2
244
not
applicabl
e
G
Müzik ve Bale İlköğretim
Okulu (6-8)
Ballet and
Music
Primary
School
(grades 68)
1
3
Ballet and
Music
Lower
Secondar
y School
Diploma
244
1
1
3
3
N
o
No
No
Yes
?
2
243
not
applicabl
e
G
Otistik Çocuklar Eğitim
Merkezi (6-8)
Education
Center for
Autistic
Children
(grades 68)
1
No
Diploma Education
Center for
Autistic
Children
243
1
1
3
3
N
o
No
No
Yes
?
2
243
not
applicabl
e
G
Eğitim ve Uygulama Okulu
(Orta veva Ağır Düzeyde
Zihinsel Engelliler)
(ilköğretim ) (6-8)
1
No
Diploma Education
and
Practice
School
243
1
1
3
3
N
o
No
No
Yes
?
Compulsory
education.
3
344
A
G
Genel Lise
Primary
School for
Educable
Mentally
Impaired medium
and severe
levels
(grades 68)
General
High
School
2
5,6
High
School
Diploma
344
1
4
4
12
N
o
No
No
Yes
Yes
The programmes
are designed to
prepare the
students for life
and tertiary
education.
Open lower
secondary
education school
programme is
the same as
primary
education.
Distance
education
techniques are
used.
The programmes
are designed for
the students who
have talented
capabilities.
Entrance
examination is
required
The programmes
are designed for
the students who
have talented
capabilities in
music and ballet.
Entrance
examination is
required
Compulsory
education.
3
344
A
G
Açık Öğretim Lisesi
Open High
School
2
5,6
High
School
Diploma
344
1
4
4
12
N
o
Yes
not
applicabl
e
Yes
No
3
354
A
V
Mesleki ve Teknik Lise
Vocational
and
Technical
High
School
2
5,6
Vocationa
l and
Technical
High
School
Diploma
354
1
4
4
12
Y
es
No
No
Yes
Yes
3
344 or
354
A
G or V
Çok Programlı Lise
MultiProgram
(Comprehe
nsive) High
School
2
5,6
MultiProgram
(Comrehe
nsive)
High
School
Diploma
344 or
354
1
4
4
12
Y
es
No
No
Yes
Yes
The programmes
are the same as
general high
school. Distance
and conventional
teaching
methods have
been used.
Educational
credits acquired
at the other high
school can be
assessed for
completing
credits
necessary to
graduate from
the open high
school.
The main
functions of the
school are to
train the students
to acquire
occupational
qualifications for
the labor market
and to prepare
them tertiary
education.
The schools offer
general and
vocational high
school
programmes.The
programmes
implemented at
the school are
the same as
general and
vocational high
school
programmes.The
schools are
located in small
communities to
give
opportunities to
the students to
select
appropriate high
school
programmes in
accordance with
her/his
capabilities.
3
354
A
V
Mesleki Açık Öğretim Lisesi
Open
Vocational
High
School
2
5,6
Vocationa
l High
School
Diploma
354
1
4
4
12
Y
es
Yes
Yes
Yes
Yes
3
353
A
V
İş Okulu (Hafif Düzeyde
Zihinsel Engelliler ve Görme
Engelliler)
2
No
Work
School
Diploma
353
1
4
4
12
Y
es
No
No
Yes
Yes
3
344
A
G
Müzik ve Sahne Sanatları
Lisesi
Work
School
(Vocational
Secondary
Education)
(Individual
s with mild
mental
retardation
)
Music and
Stage Arts
High
School
2
5,6
Music and
Stage
Arts High
School
Diploma
344
1
4
4
12
Y
es
No
No
Yes
Yes
The programmes
are the same as
vocational high
school. Distance
and conventional
teaching
methods have
been used.
Vocational
courses are
given on the job.
Educational
credits acquired
at the other high
schools can be
assessed for
completing
credits
necessary to
graduate from
the open
vocational high
school.
The programme
is designed to
prepare the
students who are
educable
mentally
impaired for life
and employment.
The programmes
are designed for
the students who
have talented
capabilities in
music and stage
arts. Entrance
examination is
required. The
schools are
affiliated with the
state
conservatories of
the universities.
4
5
544 or
554
5
645 or
655
5
655
5
645 or
655
5
756
B
A
A
V
Olgunlaşma Enstitüsü
???
3
5,6
???
G or V
Meslek Yüksek Okulu (Ön
lisans programları) (Açık
öğretime ait 2 yıllık okullar
dahil)
3
6
Associate’
s degree
diploma
A or P
Açık Öğretim Fakültesi
Vocational
Higher
Schools
(associate
degree)
(including
Vocational
Higher
Schools (2
years) of
Open
Education
Faculty)
Open
Education
Faculty
3
7
P
Konservatuar
Conservat
ory
3
7
A or P
4 Yıllık Programlar (Mesleki
veya Akademik)
3
7
P
Ortaöğretim Öğretmenliği
Eğitim Fakülteleri (Fizik,
Kimya, Biyoloji, Coğrafya,
Edebiyat, Matematik, Tarih
ve Felsefe Grubu)
Bachelor
programm
es (4 year)
(Academic
or
profession
al)
Education
Faculty for
Upper
Secondary
School
Teaching
(Physics,
Chemistry,
Biology,
Geography
,
Literature,
Mathemati
3
8
???
???
??
?
???
???
???
???
540 or
550
?
?
?
1
8
2
14
Y
es
No
No
Yes
??
Bachelor’
s degree
diploma
640 or
650
1
8
4
16
Y
es
No
No
Yes
??
Bachelors
degree of
arts
diploma
Bachelor’
s degree
diploma
650
1
8
4
16
Y
es
No
No
Yes
??
640 or
650
1
8
4
16
N
o
No
No
Yes
??
750
1
8
5
17
Y
es
No
No
??
??
Bachelor’
s degree
diploma
and
certificatio
n
???
???
cs, History
and
Philosophy
)
5
756
P
Diş Hekimliği, Eczacılık ve
Veterinerlik Fakülteleri
Dentistry,
Pharmacy
and
Veterinary
Faculties
3
8
5
756
P
Tıp Fakültesi
Medicine
Faculty
3
8
5
747or
757
A or P
Yüksek Lisans (Akademik ve
Profesyonel)
6
8
6
854
P
Tıpta Uzmanlık
6
844 or
854
A or P
Doktora (Akademik veya
Sanatta Yeterlilik)
Master Academic
and
profession
al
Specialisat
ion in
medical
science
Ph.D.
Academic
or Ph.D. in
arts
A
Bachelor’
s degree
diploma
and
certificatio
n
Bachelor’
s degree
diploma
and
certificatio
n
Master
Degree
7
Diploma
of
specialist
7
Ph.D
750
1
8
5
17
Y
es
No
No
??
??
750
1
8
6
18
Y
es
No
No
??
??
740 or
750
2
22
3
2
19-20
N
o
No
No
??
??
850
2
3
3-5
21-23
Y
es
No
No
??
??
840 or
850
2
3
3-5
21-23
Y
es
No
No
??
??
Section C.
1
UOE DATA SUBMISSION IN TURKEY
MAIN RESOURCES OF UOE IN TURKEY
1.1. ANALYSED AND EXAMINED ALL UTILISED STATISTICS RELATED REPORTS IN MONE
1.1.1. PUBLISHED STATISTICS
1.1.1.1.
NON-FORMAL EDUCATION STATISTICS
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Institution Type, Year
Number of Institution
Devlet Kurumları Module,
Öğretim Kurumları Module
Özel
Institution Type, Year, Gender
Number of Institution, Number of
Participant, Number of Teacher,
Number of Classroom
Öğretim Module, MEIS Module
Özel
Number of participants by Statistical
regions of Europe Level 1,2,3 and
educational institutions
NUTS, Institution Type, Year, Gender,
Age Group,Education Status
Number of Institution, Number of
Enrolled Participants, Number of
Attending Participants, Number of
Graduates, Number of Teacher,
Number of Classroom
Devlet Kurumları Module, Özel
Öğretim Kurumları Module ,Halk
Eğitim Merkezi Module, Özlük Module,
MEIS Module
Number of courses and participants
in maturation institutions by kind of
course
Course
Type,
Gender,Level
Education, Age Group
Number of Workshops, Number of
Enrolled Participants,
Number of
Attending Participants,
Number of
Graduates
Module, MEIS Module
Number of
institutions
Number of
classroom
non-formal
participant,
education
teacher,
of
Özlük
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of courses and participants of
practical trade schools for girls by kind
of course
Course Type, Gender
,Level
of
Number of Courses,
Graduates
Number of
Number of
Number of
Module, MEIS Module
Özlük
Number of courses and participants in
vocational courses by kind of course
Course Type, Gender,
Level
of
Number of Courses,
Graduates
Number of
Number of
Number of
Module
MEIS
public training centers by kind of
course
Level
of
Number of
Number of
Number of
Devlet Kurumları Module, Halk Eğitim
Merkezi Module, MEIS Module
Number of participants given literacy
certificate by kind of course
Level
of
Number of Courses,
Graduates
Number of Courses,
Number
of
Number of courses and participants of
tourism education centers by kind of
course
Level
of
Number of
Graduates
Courses,
Number
of
Number of courses and candidate
apprentices by kind of vocation
Occupation Type, Gender, Level of
Number of
Candidates
Courses,
Number
of
Number of
vocation
apprentices by kind of
Number of apprentices
Number of participants grante rank
certificate by kind of vocation
Number of participants
Graduates
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of participants granted rank
and foremanship certificate by kind of
vocation
Occupation Type, Certificate Type,
Gender, Level of Education, Age
Group
Number of participants
Number of ranks by kind of vocation
Number of Courses, Number of Ranks
Number of person obtained certificate
to open a business by kind of vocation
and non-formal education instituations
Occupation
Type,Non-formal
Education Institution, Gender
Number of Senior Teacher
Merkezi
Module,
Özel
Okullar
Module,MEIS Module
Number of participants who obtained
sertificate to establish work by kind of
vocatior
Number of Participants
MEIS Module
Number of courses, participants and
teachers of Koran Courses by SRE
Level 3
NUTS, Gender (Sucesfull finishers),
Gender (Teacher), Education Level,
Age Group
Number of Courses, Number of
Graduates,Number
of
Attending
Students, Number of Teachers
Devlet Kurumları
Module
special education and rehabilitation
centers by kind of educational
institution
Institution Type, Gender, Level of
Number of Participants
Özürlü Birey Module, Devlet Kurumları
Module, Özel Okullar Module,MEIS
Module
Module,
MEIS
1.1.1.2.
FORMAL EDUCATION STATISTICS
Education Indicators
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Schooling ratio by educational year
and level of education
Year, Education Level,
Age Group,NUTS,Gender
Gross Schooling Ratio, Net Schooling Ratio
e-okul
Sex ratio by educational year and
level of education
Year, Education Level
Sex Ratio
e-okul
Number of schools/units, teachers,
students and graduates by type of
school and educational year
Year, School Type
Number of School/Unit, Number of Teacher, Number of
Student, Number of Graduate
e-okul, Özlük Module, Devlet
Kurumları Module
Number
of
schools,
teachers,divisions, students and
graduates by type of school and
educational year
Year,
School
Gender
Number of School, Number of Teacher, Number of
Division, Number of Student, Number of Graduate
Kurumları Module
Number of applicants and appointed
to tertiary education programs by
school type and educational status
Year,
School
Type,
Undergraduate/Associate
Number of Applicants, Number of Appointed Students
Provided by YÖK
Number of students per school,
division, teacher and classroom by
level of education according to
Statistical Regions Levels
Year, Education
NUTS, Gender
Division, Number of Classroom
Kurumları Module
Type,
Level,
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of graduates by settlement
place and level of education
according to Statistical Regions
Levels
NUTS,
Gender,
Settlement Place
Number of Graduate Students
e-okul
Number of new entrants by
settlement place and level of
education according to Statistical
Regions Levels
NUTS,
Gender,
Settlement Place
Number of New Entrants
e-okul
Number of schools, students,
teachers and classrooms in special
education institutions
Year, Education
Gender
Level,
Classroom
Kurumları Module, Özürlü
Birey Module
teachers and classrooms in private
education institutions
Year, Education
Gender
Level,
Classroom
e-okul,
Özel
Kurumları Module
teachers
and
classrooms
in
education institutions by level of
education
Gender
Permanent/Contractual
Classroom, Number of Students
Kurumları Module
Öğretim
Pre-Primary Education
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number
of
schools,
students,
teachers and classrooms by level of
education in pre-primary education
institutions
Gender
Number of School, Number of Teacher, Number
of Classroom, Number of Students
e-okul, Özlük Module,
Kurumları Module
Devlet
Number
of
schools,
divisions,
students and teachers in public and
private
pre-primary
education
institutions by settlement place
Year, NUTS, Settlement
Place, Gender of Student,
Birth Year, Gender of
Teacher
of Division, Number of Students
e-okul, Özlük Module,
Kurumları Module
Devlet
Statistics Group: Primary Education
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of schools, students, teachers
and classrooms in primary education
institutions by level of education
Gender
Kurumları Module, Özel Öğretim
Kurumları Module
Number of schools, divisions, students
and teachers in public and private primary
education institutions by settlement place
Place, Gender, Birth Year,
Class
of Division, Number of Students
Kurumları Module
Number of transporting and transported
primary schools and students by
Statistical Regions
Year, NUTS, Gender
Number of Transporting Central Schools,
Number of Transported Settlement Places
Without a School, Number of Transported
Schools, Number of Transported Students
Kurumları Module
Statistics Group: Secondary Education
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number
of
schools,
students,
teachers
and
classrooms
in
secondary education institutions by
school type
Gender
Permanent/
Contractual, School Type
Kurumları Module
Number
of
schools,
divisions,
students and teachers in public and
private primary education institutions
by settlement place according to
Statistical Regions
Place, Gender, Birth Year,
Class, Public/Private
of Classroom, Number of Students, Number of
Division
Kurumları Module
Statistics Group: Scholarship Students and Student Boarding House
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of scholarship students by
General Directorate/Department
Year,
General
Directorate/Department
Number of Scholarship Students
e-burs
Number of scholarship students in
primary and secondary education
institutions
Year,
General
Directorate/Department,
Gender
e-burs
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of student boarding houses,
their capacities and students in boarding
houses
by
General
Directorate/
Department
Year,
General
Directorate/Department,
Gender
Number of Boarding Houses, Capacity of Boarding
Houses, Number of Boarding Students Exempt From
Payment Number of Boarding Students Subject to
Payment, Number of Students in Boarding Houses
e-burs
Number of private dormitories and
students in dormitories for secondary
and tertiary education
Year , Education Type,
Gender
Number of
Dormitories
in
e-burs
Number of private dormitories, their bed
capacity and students in dormitories
Year, Dormitories Type
Number of Dormitories, Bed Capacity, Number of
Students in Dormitories, Vacant Bed Capacity
e-burs
Number of public dormitories, their
capacities
and students in public
dormitories by Statistical Region
Year, NUTS, Gender
Number of Schools with Boarding Houses, Capacity of
Boarding Houses, Number of Boarding Students
e-burs
Number of private dormitories, their
capacities
and students in private
dormitories by Statistical Region
Year, NUTS
Number of Dormitories, Capacity, Number of Students in
Dormitories, Vacant Capacity
e-burs
Sources and capacities of secondary
education student boarding houses
Year, Boarding Source
Number of Sources, Bed Capacity, Number of Boarding
House, General Budget of MoNE, Individual General
Budget
e-burs
Number of private
settlement place
Year, Province-DistrictSmall Town/Village
Number of Dormitories
e-burs
Year-Month
Scholarship Indicator, Coefficient of Civil Servant's
Salary, Monthly Amount
e-burs
dormitories
by
Domestic study grants of students in
primary and secondary education
Dormitories,
Number
of
Students
Statistics Group: Higher Education Loans and Dormitories Institutions and Their Capacity (from Higher Education Loans)
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Number of students receiving study grant and
loan from Higer Education Loans and Dormitories
Institutions and the amount of loan
Education Type
Number of Students for Study Grant ,Number
of Students for Getting Loan, Amount of Loan
Data
gets
from
Education Loans
Higher
Number of dormitories dependent on Higer
Education Loans and Dormitories Institutions and
their capacities
Education,
Gender
Number of Dormitories, Capacity
Data
gets
from
Education Loans
Higher
Number of students in dormitories on on Higer
Education Loans and Dormitories Institution and
the capacity of dormitories by province and district
Year,
District
Number of Dormitories, Capacity, Number of
Students, Vacant Capacity
Data
gets
from
Education Loans
Higher
Year,
Province,
Statistics Group: Education Abroad
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Statistics on Schools and Turkish Training
Centers at Central Asian Republic
Year, Country-School, Gender, Nationality
(Republic of Turkey/Other)
Number of Students, Number of
Personnel, Number of Teacher,
Number of Manager
YDSIS Module
Statistics on Scholarship students in
Turkey coming Central Asian Republic
Year, Country, Education Level (Associate
programs, Bachelors Programs, Master
Degree Programs, Doctorate Programs,
Turkish Training Center)
Number of Students
DISIS Module
Scholarship students studying abroad by
country,
level
of
education
and
programme
Year, Country,Gender,
Education Area
Level,
Number of Students
YDSIS Module
Private students and public scholarship
students studying aborad by level of
education and programme
Year, Status, Education Level, Education
Area
Number of Students
YDSIS Module
Private students studying abroad by
country,
level
of
education
and
programme
Year, Country, Gender, Education Level,
Education Area
Number of Students
YDSIS Module
Education
Statistics Group : Application Hotels and Teachers Houses
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
CONCEPT
Youth and
facilities
scouting
educational
Tourism training centers
Schools with practice
Statistical Region Levels
hotels
by
Teacher's guest houses and clubs by
Statistical Region Levels
DIMENSIONS
MEASURES
RELATED MODULEES
Year, Province, District,
Name of Institution
Number of Institutions, Bed Capacity
Beden Eğitimi, Spor ve Izcilik
Module
Year, Province, District,
Name
of
Institution,
Gender
MEIS Module
Year,
NUTS,
District,
Name of Institution
MEIS Module
Year, NUTS
Number of Teacher's Guest House , Total Bed
Capacity, Number of Teacher's Club
MEIS Module, Devlet Kurumları
Module
Statistics Group: Budget
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Allocation of the budget of MoNE by
economic classification and it's ratio to net
budget appopriation to previous year
Year,
Type
Appopriation
of
Budget of Year,Increase Ratio of last two years
e-budget
Allocation of the budget of MoNE by
functional classification
Year,
Type
Appropriation
of
Budget of Year, Portion in Total Budget of MoNE
e-budget
Budget of MoNE
Year,
Type
Appropriation
of
Budget of Year, Increase Ratio of last two years
e-budget
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Ratio of MoNE's Budget in GDP and
Consolidated/Central Government Budget
Year
e-budget
Ratio of budgets of Higher Education
Council, universities and high technology
institutes to previous year budget
Year,
Type
Appropriation
GDP, Consolidated Budget, Budget of MoNE, Ratio
of MoNE's Budget in GDP, Ratio of MoNE's Budget
in Consolidated Budget
Budget of Year, Increase Ratio
Proportions of Budgets of MoNE and
HEC+Universities
in
GDP
and
Consolidated/Central Government Budget
Year
MoNE's Budget Appropriation, Budgets of HEC
+Universities, Proportion of Total Education Budget
in
Consolidated/Central
Government
Budget,
Proportion of Total Education Budget in GDP
e-budget
Budget of HEC, universities
technologies
institutes
by
classification
Year,
University/
Institution,
Economic
Classification
Budget Amount
e-budget
and high
economic
of
e-budget
Statistics Group: Investment
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Proportion of MoNE's Investments
in
Consolidated
Budget
Investments
Year
Consolidated
budget
investment
appropriation,Investment Appropriation of MoNE,
Proportion of MoNE's investments in consolidated
budget investments
e-investment
Ratio of investment budget of
MoNE in GDP and Consolidated
budget
Year
GDP, Consolidated Budget, Investment Budget of
MoNE,Ratio of MoNE's Budget in GDP, Ratio of
investment budget of MoNE in consolidated budget
e-investment
CONCEPT
DIMENSIONS
MEASURES
RELATED MODULEES
Proportion of investments in the
budget of MoNE
Year
Budget of MoNE, Investment Budget of MoNE,
Proportion of investments in the budget of MoNE
e-investment
Classrooms built with in the last
eight years
Year,
Classroom
Group
(Kindergarten, Primary Education,
Secondary Education, Non-formal
Education, Classrooms built within
the context of 100% support for
education campaign)
Number of classrooms
e-investment
Provincial Private Administrations
and
Individuals
Support
to
Education
Year, Support of Individuals/
Support of Provincial Private
Administrations
Amount in year in which it was provided, Amount of
year DPT Deflator
e-investment
Investment
appropriations
foreseen to be allocated
Year, Department
Construction facility, Equipment, Restorations,
Nationalization, Research project, External Loan,
Capital Transfer
e-investment
Allocation
of
completed
investments of MoNE by projects
Year,
Departments,
Province,
District, Project Type (Additional
Classroom,
School,
Boarding
House, Apartment For Staff,
Gymnasium,
Conference
Hall,
Kindergarten)
Number of Project, Total Numbers Related to
Project Type
e-investment
1.1.1.3.
HIGHER EDUCATION STATISTICS (PROVIDED BY ÖSYM)
Summary Tables
CONCEPT
DIMENSIONS
Number of Students
Year, Gender,
Education Type
Number of Teaching Staff
Year,
Title,
Education Type
Number of Students &Teaching Staff According
To Educational Institutions
Year, Educational Institutions, Education Type
(Voc.Tng.Sch, Undergrad. ,Graduate, Master,
Dr.,Medical Interns), Title of Teaching Staff, Gender
Number of New Admissions, Total Number of
Students, Academic Year Graduates, Number of
Teaching Staff
Number of
Provinces
Students
MEASURES
Universities/Other
Universities/Other
Institutions,
Students, Academic Year Graduates
Institutions,
&Teaching
Staff
By
Year, Province, Education Type (Voc.Tng.Sch,
Undergrad., Graduate, Master, Dr. Medical Interns),
Title of Teaching Staff, Gender
Students, Academic Year Graduates, Number of
Teaching Staff
Training
School
&
Year, Universities, Units(Faculty, Higher Education
Schools With Four Year Program, Two Year
Vocational Training Schools), Gender
Number of Newly Registered/Students/Graduate
Students By Age
Year, Age Groups, Education Type (Voc.Tng.Sch,
Undergrad., Graduate , Medical Interns), Formal
Ed./Open Ed., Master/Doctorate, Gender
Number of Newly Registered/Students/Graduate
Students
Number of Graduates With Pre-Licentiate
Diploma From UnderGraduate Programs By Age
Year, Age Groups, Gender, Formal Ed./Open Ed
Number of Students
Number of Vocational
UnderGraduate Students
CONCEPT
DIMENSIONS
MEASURES
Number of Teaching Staff By Academic Title
Year, University, Title, Gender
Number of Teaching Staff By Working Status
Year,
University,
Gender,
Tenured/Contract
Basis/Course-PD Basis, Full-Time/Part-Time, Arts
Instr./Retired/Others,
Public
Sector/Private
Sector/Lib.Prof.
The Number of Students
CONCEPT
DIMENSIONS
MEASURES
Year, University-Faculties, Gender
Number of Undergraduate Students According to
Field of Study
Year, Field of Study, Gender
Number of Vocational Training School Students
According to Field of Study
Year, Field of Study, Gender
Number of Graduates With Pre-Licentiate Diploma
From Undergraduate Programs
Number of Students
Number of Undergarduate/Vocational Training
Students According to International Standard
Classification of Education
Year, Classification of Education, Gender
Number of Vocational
Undergraduate Students
Training
School
And
CONCEPT
DIMENSIONS
MEASURES
Number of Foreign Students By Nationality
Year, Country, Universities/Other Institutions,
Gender
Number of Graduate Students in the Various
Graduate chools
Year, University-Institute,
Gender
Master/Doctorate,
Number of Graduate Students According to Field
Of Study
Year, Field of Study,
Master/Doctorate, Gender
University-Institute,
Number of Persons Doing Medical Specialist
Training&Graduate Work in Various Institutions
Year, Universities-Faculties, Other InstitutionsHospitals, Gender
Students, Number of Students Receiving a Graduate
Degree
Students, Number of Students Receiving a Graduate
Degree
Number of New Admissions, Number of Residents,
Number of Residents Receiving Specialist Degree
Number of Persons Doing Medical Specialist
Training&Graduate Work According to Field of
Medical Science
Year, Field of Medical Science, Gender
Number of Foreign Students
Institutions
in Educational
Number of New Admissions, Number of Residents,
Number of Residents Receiving Specialist Degree
Teaching Staff
CONCEPT
DIMENSIONS
MEASURES
Number of Teaching Staff By Academic Title
Year, University, Academic Title, Title,Gender
CONCEPT
DIMENSIONS
MEASURES
Number of Teaching Staff In Undergraduate Programmes
According to Fields of Teaching
Year, Fields of Teaching, Title, Gender
Number of Teaching Staff In The Programmes of Vocational
Training School According to Fields of Teaching
Number of Teaching Staff In Graduate Schools&Centers For
Application&Research According to Fields of Teaching
Number of Foreign Teaching Staff By Academic Title
Year, University, Academic Title, Title, Gender
Number of Teaching Staff By Working Status
Year,University-Faculty/Vocational Training School,
Tenured/Contract Basis/Course-PD Basis, FullTime/Part-Time, Arts Instr./Retired/Others, Public
Sector/Private Sector/Lib.Prof., Gender
1.1.2. MEIS QUERY STATISTICS
Meis Query is the information system implemented to provide all the Statistical needs of
indicators/reports for Strategy Department and Provincial and District National Education
Directorates.
There are about 150 Statistics reports/indicators in Meis Query to show current situation in
MoNE as shown below.
Formal Education Statistics Reports/Indicators (#117)
Government Institutions (#76)
Private Institutions (#41)
Student
Statistics
Report/
Indicators
Personnel
Statistics
Report/
Indicators
Buildings
Statistics
Report/
Indicators
Student
Statistics
Report/
Indicators
Personnel
Statistics
Report/
Indicators
Buildings
Statistics
Report/
Indicators
(#50)
(#13)
(#13)
( #25)
(#9)
(#7)
Informal Education Statistics Reports/Indicators (#7)
MoNE General Statistics Reports/Indicators (#24)
All the reports have been reviewed and examined in terms of their concepts,
National/International Level, dimensions, measures, related modules (data received from) and
explanation (if any) and all these information has been reported as follows
This study is very crucial for BI design stage since it allows to access most of the National
Indicators utilizing by MoNe. This study also allows the elimination of any useless indicators
and/or addition of some extra ones with the collaborative efforts of Strategy Department.
Common Parameters in MEIS Query










Publication Date
City
District
Related Unit
Institution Type
Institution Name
Institution subsidary type
Period (yearly)
Settlement place
Education Type
GOVERMENT INSTITUTION
STUDENT STATİSTİCSS
CONCEPT
DIMENSIONS
MEASURES
RELATED
MODULES
Number of students
Gender
Total Number of students
e-okul
Number of Students by grades
Birth Year, Gender
Total Number of Students
e-okul
The Number of Students in Fields
and Departments
Department, Class ,
Gender
e-okul
Number of students by year of
birth
Grade, Birth Year,
Gender
e-okul
Number of International Students
Nationality, Grade,
Gender
e-okul
Number of New Registered
Students in Secondary Education
Grade, Birth Year,
Gender
e-okul
Number of New Registered
Students in Primary Education
Gender
e-okul
Number of Students in PrePrimary Education
Age (3,4,5, 5+)
Total Number of Students,
Number of Class
e-okul
Number of Graduated Students in
Primary Education
Gender
e-okul
Number of Graduated Student by
Year of Birth
Birth Year, Gender
e-okul
Number of Graduated Students
(Field Department)
Name of department,
Gender
e-okul
The Number of Students that
takes Compensation Education
Gender
3308 The Number of
th
Students by 3308 item of
regulation, The Number of
Students that are outside
th
of the content of 3308
item of regulation, The
Number of Students in
Vocational High Schools,
in General High Schools,
in Journeyman and
Mastery
e-okul
Total Number of Students(Primary
Education) that takes inclusive
education
The type of disablement,
Gender
Number of Classes, Total
Number of Students
e-okul
Total Number of
Students(Secondary Education)
that takes inclusive education
The type of disablement,
Classes(9,10,11,12),
Gender
Number of Classes, Total
Number of Students
e-okul
e-okul
Number of Students by Language
Number of Students by Success
Status
Success Status, Total
number of students who
pass a grade being
responsible for
secondary education
level , Class, Gender
e-okul
Total Number of Students by
Talents
The type of talent
(General Cognitive
Skills, Music, Painting),
Gender
e-okul
Total Number of Students that
takes Management Vocational
Education
Number of Students in Boarding
Houses in Secondary Education
NA
-
Class, The type of
boarder (At school-paid,
at schools-free, another
place-paid, another
place-free),
Gender
NA
Total Number of Students Using
Library
Beneficiary-The ones
that borrows, Gender
e-okul
Number of Students who pass to
Technical High School
Gender
e-okul
Number of Students in Boarding
Houses in Primary Education
-
Number of Students who takes
vocational education in companies
Department, Class, The
ones that should go –
The ones that have
gone.
e-okul
The Number of Students in Child
Clubs
Gender
e-okul
Total Number of Students who
break off
Class, The reason of
break off, Gender
e-okul
Total Number of Students in
Application of vocational open
education
Name of Department,
Gender
e-okul
The course information of The
Practical Trade School for Girls
The type of Course , The
kind of course, The
name of course, Gender
Meis
The Courses
Department, Gender,
Educational Status
Meis
The number of trainees in
vocational courses
The type of course,
Gender, Educational
Status
Number of Courses, Total
Number of Students
Meis
Total Number of Students in MYO
that pass a grade without
examination
Gender, Department
Meis
Vocational Higher Schools
NA
-
Multigrade Classes
Multigrade, Gender
e-okul
Closed Schools
Gender
e-okul
The number of special education
trainees (According to Fields)
Department, Gender
Meis
The Number of Trainees in
Tourism Education Centers
The field of Profession,
The type of course, The
number of courses, The
type of Schools, Gender
Meis
The ones in waiting
Gender
Meis
The ones that studies elective
courses (Primary Education)
Course, Class, Gender
e-okul
Non-Formal Education Activities
of PKSO Advanced Technical
Schools for Girls
The Type of Activity,
Activity, Item Number,
Term(1-2), Gender
Meis
in Secondary Education
Class, Gender
e-okul
in Primary Education
Class, Gender
e-okul
The number of trainees in Special
Education Guidance (Education
Status)
Gender, Educational
Status
Özürlü Birey
Modulü
Advanced Technical Schools for
Girls
Department, Field, The
Number of Workshops,
Class
Meis
Mentally Impaired Capable of
Learning Vocational
The type of course,
Gender
Özürlü Birey
Modulü
Number
Students in
Training of
Centers
Departments and Fields
Department, Field,
Class, Gender
e-okul
Number of Homeschooling
Students
Type, Number of
Classes, Gender
e-okul
The Number of Students in FullTime Schooling
Gender
e-okul
Number of Students in
Transporting and Transported
Education
Gender
e-okul
Reward – Punishment Information
(Primary Education)
Class, Type, Reason,
Gender
e-okul
Reward – Punishment Information
(Secondary Education)
Class, Type, Reason,
Gender
e-okul
Second Foreign Languages
Students
Foreign Language,
Class, Gender
e-okul
PERSONNEL STATİSTİCS
RELATED
MODULES
CONCEPT
DIMENSIONS
MEASURES
The Number of Teachers
according to branches (According
to duties)
Branch, Gender
Total number of teachers
Özlük
Modulü
The Number of Personnel
(According to duties)
Duty, Gender
Total Number of Teachers
Özlük
Modulü
The Number of Teachers by Birth
Years (Title)
Birth Year, Gender
Özlük
Modulü
The number of directors according
to duties
Duty, Gender
Number of Directors
Özlük
Modulü
The Number of Teachers by types
The name of kind, The
Name of Type(teaching
two classes in the same
classroom, teaching
three classes in the
same classroom etc.),
Gender
Özlük
Modulü
Number of Personnel (According
to titles)
Title, Gender
The number of personnel
Özlük
Modulü
Branch Teachers According to
educational status
The type of personnel,
Educational status,
Branch, Gender
Özlük
Modulü
Number of Contracted Teachers
Branch, The type of
personnel, Gender
Özlük
Modulü
The number of directors
(According to educational status)
Duty, Educational Status
Total Number of Manager
Özlük
Modulü
The number of directors
(According to branches)
Duty, Branch
Total Number of Manager
Özlük
Modulü
The number of teachers according
to branches (According to titles)
Branch, Gender,
Specialty
Özlük
Modulü
The number of students in
Nursery Schools
The type of personnel,
Branch, Gender
The number of teachers in
Multigrade Classes
Class(teaching two
classes in the same
classroom, teaching
Özlük
Modulü, eokul
Özlük
Modulü, eokul
three classes in104
the| F I N A L P R A C T I C A L G U I D E L I N E
same classroom etc.),
Gender
BUILDING STATİSTİCS
CONCEPT
DIMENSIONS
MEASURES
RELATED
MODULES
The Number of Classrooms
Class
The Number of
Classrooms
Devlet
Kurumları
Building Usage Form
Usage Field
Number (Archive, Bath,
Advisory, Storage etc.)
Devlet
Kurumları
Building Usage Area
Building Status,
Ownership Status,
Entrance Date to Service
Building Area, Garden
Area
Devlet
Kurumları
Building Heating Status
Rent Status, Heating
Status, The type of fuel
The number of
institution
Devlet
Kurumları
Computer Status
Purchase Source
The Number of
Computers
Devlet
Kurumları
Number of Computer Labs
Entrance Date to
Service, Purchase
Source
The Number of
Computers, The
Number of Labs
Devlet
Kurumları
Status of Housing
The type of houses
(Centrally heated, stoveheated)
Number
Devlet
Kurumları
Building Allocation Status
Allocated Institution
Total Number of
Classroom
Devlet
Kurumları
The Capacities of Hostels
Gender
Number
Devlet
Kurumları
IT, Internet and Ecological
Sciences
Group (Ecological
Sciences etc.) Element
(Data show, computer)
Number
Devlet
Kurumları
Library Materials
The type of Material
Number
Devlet
Kurumları
The Number of Beds
Devlet
Kurumları
The Number of
Classrooms
Devlet
Kurumları
The Bed Capacity of Schools
The number of classrooms of
Nursery School
Usage Area
STUDENT STATİSTİCS
CONCEPT
DIMENSIONS
MEASURES
Number of Students in PrePrimary Schools
Number of Students
RELATED
MODULES
Number of Classes
e-okul
Gender
e-okul
Number of Students by Year of
Birth
Class, Year of Birth,
Gender
Number of Students by Grade
Class, Gender
e-okul
e-okul
According to Success Status
Success Status, Class,
Gender
Total Number of Students who
break off
The Reason of Break
Off, Class, Gender
Number of Graduated Students
Department, Gender
e-okul
e-okul
e-okul
The Number of Students that take
education for free
Gender
The Number of New Registered
Students (Secondary Education)
Class, Year of Birth,
Gender
The Number of New Registered
Students (Primary Education)
Gender
(Field/Department)
Department, Gender
Total Number of International
Students
Nationality, Class,
Gender
The Number of Students that
uses Library
Beneficiary-The one
that borrows, Gender
Total Number of
Students
The Number of Students of MTSK
The Type of Course,
Age Groups, Educational
Status, Gender
Total Number of Students,
The Number of Course
Groups
e-okul
e-okul
e-okul
e-okul
e-okul
e-okul
MTSAS
Modulü
The Number of Students in
various courses
The Type of Course,
Gender
The Number of Courses,
Meis
The Number of Students in
Private Teaching Institutions
The Type of Course,
Age Groups, Gender
Meis
Number of Graduated Students by
Year of Birth
Year of Birth, Gender
The number of trainees of Private
etude training centers
The type of Course,
Gender
Meis
The number of trainees of
The type of course,
Gender
Special Education and
Rehabilitation
The
Number ofCenters
Students of
Foreign Language
Özürlü Birey
Modulü
Language, Class,
Gender
The Number of Students of
Second Foreign Language
Language, Class,
Gender
CONCEPT
DIMENSIONS
MEASURES
The Number of Teachers (Private
Teaching Institution)
(On Permanent Staff,
Paid, Other), Gender
The Number of Teachers (MTSK)
The Name of Course,
On Permanent StaffPaid, Instructor-Teacher
Number
Total Number of Teachers of
Special Courses (According to
Educational Status)
Educational Status, On
Permanent Staff-Paid,
Instructor-Teacher,
Gender
Number
The Number of Branch Teachers
(Private Teaching Institution)
Branch, On Permanent
Staff-Paid, Gender
The Number of Branch Teachers
(Schools)
Branch, TeacherDirector, Gender
According to Duties
Duty (Cook, Watchman),
Gender
Özel Öğretim
Kurumları
Modülü
The Number of Special
Teachers/Instructors
Educational Status, On
Permanent Staff-Paid,
Instructor-Teacher,
Gender
Number
Özel Öğretim
Kurumları
Modülü
e-okul
Meis
e-okul
PERSONNEL STATİSTİCS
RELATED
MODULES
Meis
Meis
Meis
Meis
e-okul
The Number of Teachers/Masters
Instructors by types
The Name of Kind, The
Name of Type, Gender
Number
CONCEPT
DIMENSIONS
MEASURES
The Forms of Building Usage
Usage Form
(Classroom, Bath,
Archive etc.)
Number
Building Status, Building
Status, Rent Status
Number
Heating, Fuel
The Number of Buildings
Özel Öğretim
Kurumları
Modülü
BUILDING STATİSTİCS
Building Status
Building Heating Status
RELATED
MODULES
Meis
Meis
Meis
Building Usage(Area)
Status of Housing
Building Allocation Status
The Number of IT Labs and
Computers
Entrance Date to
Service, Area of
Building, Area of Garden
Meis
Centrally heated - stove
heated
Number
The Name of Institute
The Number of
Classrooms
Entrance Date to
Service, Purchase
Source
Meis
The Number of
Computers, The Number
of Labs
Meis
Meis
NON-FORMAL EDUCATION
APPRENTICESHIP EDUCATION CENTER STATİSTİCS
CONCEPT
DIMENSIONS
MEASURES
The Numbers of Apprentices
Field of Occupation
(Gardening etc.),
Occupation (Florist etc.),
Classes, Educational
Status,
Range,
Field of Age
Occupation,
Gender
Occupation, Educational
The Numbers of
Apprentices
The Number of Candidate
Apprentices
The Number of Journeymen
Status, Age Range,
Gender
Field of Occupation,
Occupation , Classes,
Educational Status, Age
Range, Gender
The Numbers of
Apprentices
RELATED
MODULES
e-yaygın
e-yaygın
The Number of
Journeymen
e-yaygın
e-yaygın
The Ones who take journeyman
and mastery certifications
The Ones that take
certification
(Journeyman
Certification, Mastery
Certification), The Type
of Certification , The
Occupation, Educational
Status, Age Range,
Gender
Number
The ones who take master of
instructiveness certification
Occupation, Gender
Number
The ones who take Set Up a
Business Document
Occupation, Age Range,
Gender
Number
e-yaygın
e-yaygın
GENERAL REPORTS
PUBLIC INSTITUTIONS
CONCEPT
DIMENSIONS
MEASURES
The Entrance Years of Institute to
Service
The Entrance Year to
Service
The Number of Institutes
The Contact Information of The
Institute
RELATED
MODULES
Devlet
Kurumları
Devlet
Kurumları
Closed Schools
The Reason of Closure
The Number of Schools
Devlet
Kurumları
The Number of Closed Schools
The Reason
Devlet
Kurumları
Number
Devlet
Kurumları
Number of Classes
Devlet
Kurumları
Course Information Opened to
Public
The Number of Trainees
Devlet
Kurumları
Devlet
Kurumları
Institutes that have application
hotels
The Number of Classes According
to Courses That Gives ComputerAided Education
Courses
Field/Department
The Name of Field, The
Name of Department
Devlet
Kurumları
Independent Institutions
The number of Institute,
Gender
Number
Devlet
Kurumları
Summer/Mobile Nursery School
Type, Age(3,4,5),
Gender
Devlet
Kurumları
The Number of Institutions that
have Nursery Class
Education Type
The Number of
Classrooms, Total
Number of Students
The Number of Transporting and
Transported Schools
The Reason, Classes
Number
Devlet
Kurumları
According to Education Type
Education Type
Devlet
Kurumları
Devlet
Kurumları
RELATED
MODULES
CONCEPT
DIMENSIONS
MEASURES
The Entrance Years of The
Institute to Service
The Entrance Date to
Service
Number
Schools in The Institutes
The Type of School
The Number of Library/Material
Material
Meis
IT/Computer
Purchase Source
IT, Internet and Ecological
Sciences
Ecological Sciences
The Amount of Material in
Last Year , The Number of
Input Material in Year, The
The
Number
of
Number
of Output
Material
Purchases,
The
Number
in Year
of Computers
Number
according to Education Type
Education Type
Meis
The Number of Classes
Class
The Number of Classes
Meis
Meis
The Number of Institutes that
have Nursery Class
The Contact Information Of The
Institute
Özel Öğretim
Kurumları
Modülü
Özel Öğretim
Kurumları
Modülü
Meis
Meis
Meis
1.1.3. ORACLE DISCOVERER STATISTICS (SAMPLE)
One of the main reasons of the implementation of Meis Query is to assist a Strategy
Department in order to prepare National Publications for both Formal and Informal Education.
It is understood that Strategy Department canot utilise Meis Query System all the time for this
purpose. They prefer querying reports from Oracle Discoverer System to get data from MoNE
databases because they can easily customize/revise the format of the reports by drop and
drugs methods as requested. These reports are not already prepared report like those of Meis
query system, they can reform by their demands.
For this defined activity, several meetings were handled with the related key contacts from
Strategy Department to work on Oracle Discoverer Reports and to examine the available
reports and also their existing problems.
During the examination of the reports in Oracle Discoverer, We were informed that the data
from these existing reports are different than Meis Query but at the end these two systems
reaches to the same data and same indicators but with the different format.
PRIMARY EDUCATION
CONCEPT
DIMENSIONS
MEASURES
The Number of Schools(Public)
City, County, The Type of School,
Settlement, The Name of School
The Number of
Schools
The Number of Schools (Private)
City, County, The Type of School,
Settlement, The Name of School
The Number of
Schools
3.Total Number of Students (by
Classes) Official
City, County, The Type of School, The
Name of School, The Code of Institute,
Settlement, The Name of School, Gender,
Classes (1,2,3,4,5,6,7,8 Special
Education Classes )
Total Number of
Students
Total Number of Students (by
Classes) Private
Settlement, The Name of School, Gender,
Classes (1,2,3,4,5,6,7,8 Special
Education Class)
Total Number of
Students
Total Number of Students by Birth
Years (Public)
Settlement, The Name of School, Year of
Birth, Gender
Total Number of
Students
Total Number of Students by Birth
Years (Private)
City, County, The Type Of School, The
Name of School , The Code of Institute,
Settlement, The Name of School, Year of
Birth, Gender
Settlement
Total Number of
Students
The Number of Classes (Private)
Settlement
The Number of
Classes
Total Number of New Registered
Students (Public)
Settlement, Gender
Total Number of
Students
The Number of Classes (Public)
The Number of
Classes
Total Number of New Registered
Students (Public)
Settlement, Gender
Total Number of
Students
Total Number of Alumni (Public)
City, County, The Type Of School The
Settlement, Gender
Total Number of
Students
Total Number of Alumni (Private)
Settlement, Gender
Total Number of
Students
Building Information (Public)
Settlement, The Type of
Room(classroom, lab, library etc.)
Number
Building Information (Private)
Settlement, The Type of
Room(classroom, lab, library,etc.)
Number
Success Status (Public)
Settlement, Success Status of Last Year
(Passing a Grade, Repeating), Gender
Total Number of
Students
Success Status (Private)
City, County The Type of School, The
Settlement Success Status of Last Year
(Passing a Grade, Repeating), Gender
Total Number of
Students
The Number of Teachers (Public)
Settlement, Branch , Gender
The Number of
Teachers and
Personnel
The Number of Teachers and
Other Personnel (Private)
Settlement, Branch , Gender
The Number of
Teachers and
Personnel
General Report (Official)
Classroom, Nursery Class, New
Registered Student, Alumni, Class,
Gender On the Basis of School
Number
Inclusive Education (by
disablement)
Name of School, The Code of Institute ,
Settlement, Gender
Total Number of
Students
Multigrade Classes
Settlement, Gender
Total Number of
Students
Education Opportunities
Settlement, Gender
1.2. REVIEWING EXISTING MONE MODULES
1.2.1. E-SCHOOL (E-OKUL)
The E-School module started functioning in 2009. The E-school is a system through which
the transactions related to students and management in schools/institutions dependent on
the Ministry of National Education are electronically managed and through which the data
are stored. Data are collected at the institutional level (first sub-module) and at an individual
basis for all students from pre-primary to the upper secondary level (second main module).
From the student perspective, it allows to collect information about capacity management
(buildings, number of classes and classroom, etc.) and individual information related to the
specific student/pupils (timetable, learning achievements and outcomes).
The main content of the E-school database is designed for administrative purposes. The
data needs for international reporting of Statistics may not have been always known and
taken into account in the design of the data collections.
1.2.2. E-STAFF MODULE (ÖZLÜK MODÜLÜ)
The E-Staff module has been set up on the request of the General Directorate of Personnel
and started functioning in 2002. The aim of the E-staff module (Özlük Modülü) is to provide a
system to manage and follow the information of identification, education, occupation,
depended family member, in house courses etc of all MEB personnel.
The staff module contains comprehensive data for each employee in the educational
institutions dependent on the MEB. The data on personnel of MEB keeps individual data on
personnel of MEB. It consists of administrators, teachers and other personnel as well as
instructional and non-instructional institutional discriminations. The data are validated by the
institution. Essential information for management (e.g. workplace and working hours) are up
to date but less frequently used information and variable might be outdated.
Information about type of teacher training for teachers is available. There is now facility for
locking the databases; however, historical data are not available. A data warehouse system
for storage of historical data is under development.
1.2.3. TEFBIS
The TEFBIS module has been set up on the request of the Strategy Development
Presidency and started functioning in 2011. Data are currently not available but the purpose
of the TEFBIS module is to gather information on current and capital expenditures as well as
on resources for all sources of funding. The final purpose is clearly to get expenditure data
for all educational sectors, to evaluate (at national level) the cost per students and to support
policy makers in ‘performance budgeting’ and monitor strategic performance plan. The
TEFBIS module is also aligned to the UOE methodology in order to provide Statistical data
to fill in UOE finance tables.
1.2.4. DEVLET KURUMLARI MODÜLÜ (E-PUBLIC)
The Devlet Kurumları Modülü has been set up on the request of the MEB and started
functioning in 2003. This module mainly provides information on the demography of public
educational institutions (e.g. follow up opening and closing operations of the public
institutions under the responsibility of MEB).
1.2.5. ÖZEL ÖĞRETIM KURUMLARI MODULU (E-PRIVATE - ÖÖK)
The ÖÖK module has been set up on the request of the General Directorate of Private
Education Institutions and started functioning in 2008. This module provides a system to
follow up procedures of the private educational institutions and their personnel. For instance,
the purpose of the module is to provide information on the situation of all institutions under
the responsibility of the General Directorate of Private Education Institutions and especially
data on their demography (opening of new institutions, closing of institutions, their personnel,
the fees that are collected, etc.).
1.2.6. E-NON FORMAL (OUTSIDE MEBBIS INFRASTRUCTURE)
The E-non formal module has been set up on the request of the General Directorate of
Apprenticeship and Non-Formal Training and started functioning in 2008. It may considered
as a counterpart of the E-School system for non formal education as it gather information on
students, courses and certifications (graduates) for non-formal education course
information44.
1.2.7. E-BUTCE (E-BUDGET) (OUTSIDE MEBBIS INFRASTRUCTURE)
The E-budget module has been set up on the request of the Ministry of Finance and its
purpose is to collect information on the budgeting system and functioning of all public
institutions. It usually provides its annual report every July and record information about all
public spending. This allows setting up finance accounts.
1.2.8. HIGHER EDUCATION DATA COLLECTION (OUTSIDE MEBBIS INFRASTRUCTURE)
The data collection routines for higher education are not in the scope of the project. For the
UOE data collection there is cooperation between MEB and the Council for Higher Education
(YÖK). YÖK fills out the UOE questionnaires. YÖK and MEB verify that the data are
consistent.
The Student Selection and Placement Center (ÖSYM) collect Statistical information about all
universities under the Higher Education Council (YÖK) jurisdiction as well as about all higher
education institutions which are outside the jurisdiction of the Higher Education Council.
YÖK collects information from HE institutions in paper format and enter the information in a
central Data base (manually), and prepare and publish the paper report on Higher
Education. These data on higher education are provided by YÖK to MEB in electronic
format; indeed, YÖK completes the UOE questionnaire directly and sends the raw data used
to produce the UOE tables. However, in the near future, YÖK will also collect information
through web-based modules under-development.
44
It should be mentioned here that non formal education follow the definition as detailed in section 1.
1.2.9. EDUCATION PROGRAMMES/SCHOOL UNDER THE RESPONSIBILITY OF OTHER MINISTRIES
(OUTSIDE MEB DIRECT RESPONSIBILITY)
Besides the available data in MEB and those available outside the MEBBIS infrastructure
(please see sections above), it was also understood that Strategy Department utilizes some
hard-copy paper templates to get the required data for some type of schools as briefly
explained in the following paragraphs; Meaning: modules are not used to collect the data but
use some forms. Thus the scope of the modules is not exhaustive.

Conservatories: e-school provides all information for Primary Education of the
Conservatories but not for Secondary Education. Strategy Department requests the
data of Conservatories’ Secondary Education form Then Council of Higher Education
(YÖK) annually by sending sample attached form shown in the following page. This
information is then added to Technical Secondary Education sum in Formal
Education Statistics. (see the details in the Formal Education Publication)

Police College: The same paper form is utilized annually to get required data from
Ministry of Interior for Police Colleges and then the gathered data is added into
Technical Secondary Education which is then detailed within Formal Education
Statistics. (see the details in the Formal Education Publication)

Social Services and Child Protection Agency (SHÇEK): The required data for preschool attendees is requested annually from General Directorate of SHÇEK and then
all the gathered data is reflected to the Pre-Primary Education Statistics.

Pupils with special educational needs (i.e. SEN pupils) are also out of the scope of
the modules but are collected once a year (by other than the MEB) and send every
year.

Role of preparatory year is for language already in secondary schools
2
GENERAL PROCEDURES
PROCESS IN TURKEY
ON
UOE
DATA
SUBMISSION
The purpose of this section is to detail the general procedure that should be followed when preparing
the Turkish UOE data submission to international data requesters. The content of this section is an
adaptation of the ‘Generic Statistical Business Process Model’ (henceforth GSBPM) developed by
45
Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS) in 2009 .
More practically the current section will identify the different phases of the UOE Statistical business
process and the sub-processes at stake within each phase and their description.
As outlined by UNECE, and according to the process modelling theory, ‘each sub-process should
have a number of attributes’ including:



Input(s);
Output(s);
Purpose (value added);
45
Generic Statistical Business Process Model, Version 4.0 – April 2009, prepared by the UNECE Secretariat. The
text in italic and between “” is extracted from this version of the GSBPM.




Owner;
Guides (for example manuals and documentation);
Enablers (people and systems);
Feedback loops or mechanisms.
Whenever relevant, these attributes will be described in the context of the Turkish UOE data
submission process. In this section, an additional attribute (i.e. timetable) has been added. It
specifies, in cooperation with MoNE, the time when each sub-process should preferably be
performed.
GENERAL PRESENTATION
This section provides the overall description of level 1 and 2 of the GSBPM. It should be borne in
mind that such process should not be considered as linear: sub-processes do not have to be followed
in a strict order; there are many possible paths, including iterative loops within and between phases;
some iterations of a regular process may skip certain sub-processes.
Level 1 and 2 of the Generic Statistical Business Process Model: Adaptation for the Turkish
UOE submission
Quality management / Meta data management
1
2
3
4
5
6
7
8
9
Specify needs
Design
Build
Collect
Process
Analyse
Disseminate
Archive
Evaluate
1.1
Determine
needs for
information
1.2 Consult
and confirm
needs
2.1 Design
outputs
3.1 Build data
collection
instrument
2.2 Design
variables
description
3.2 Build and
enhance
process
components
1.3 Establish
output
objectives
2.3 Design
data
collection
methodology
1.4 Identify
concepts
2.4 Design
statistical
processing
methodology
1.5 Check
data
availability
1.6 Prepare
business case
2.5 Design
production
systems &
workflows
3.3 Configure
workflow
4.1 Set up
collection
4.2 Run
collection
4.3 Finalise
collect
5.1 Integrate
data
5.2 Classify
and code
5.3 Review,
validate &
edit
3.4 Test
production
system
5.4 Estimate
3.5 Test
statistical
business
process
5.5 Derive
new variables
& statistical
units
3.6 Finalise
production
system
5.6 Calculate
aggregates
6.1Prepare
draft output
7.1 Update
output
systems
6.2 Validate
outputs
7.2 Produce
6.3 Scrutinise
and explain
7.3 Manage
6.4 Apply
disclosure
control
6.5 Finalise
outputs
dissemination
products
release of
dissemination
products
8.1 Define
archive rules
9.1 Gather
evaluation
output
8.2 Manage
archive
repository
9.2 Conduct
evaluation
8.3 reserve
data and
associated
metadata
9.3 Agree
action plan
7.4 Promote
dissemination
product
7.5 Manage
user support
5.7 Finalise
data files
2.1. PHASE 1: SPECIFY NEEDS
Specify Needs
1.1
Determine
needs for
information
1.2
Consult and
confirm
needs
1.3
Establish
output
objectives
1.4
Identify
concepts
1.5
Check data
availability
1.6
Prepare
business
case
This phase is usually performed ‘when a need for new Statistics is identified, or feedback about current
Statistics initiates a review. It determines whether there is a presently unmet demand, externally and / or
internally, for the identified Statistics and whether the Statistical organization can produce them’.
2.1.1. DETERMINE NEEDS FOR INFORMATION
In the UOE framework, the need for information is expressed by international data requesters through
the UOE questionnaires. MoNE does not have to investigate and identify what Statistics are needed for
international purposes. Nonetheless, MoNE should regularly monitor and disseminate at national level
the revisions and adaptation of the needs of information expressed at international level.
In this section, emphasis on the UOE data collection is given, however, MoNE could use this framework
46
to define the national needs for information that could be fulfilled by the UOE data or otehr data . Such
definition could be performed in parallel to the one that is described.
1.1.
Determine needs for information
UOE questionnaires as sent by data requesters
Knowledge of international data needs
Understanding at national level of data requested by
the UOE data collection
Owner
MoNE Strategy Development Presidency
Head of Statistics Department
Guides (for example manuals
UOE manuals (available on EU Circa website)
and documentation)
Enablers (people and systems)
Experts responsible for UOE
All related departments in MoNE
Feedback loops or mechanisms
Despite, UOE data requesters wish to make the UOE
data collection more stable over time; it should be
borne in mind that adaptation of the UOE data
collection may happen every year. It is thus relevant
to perform this step at least every year to have an
understanding of the data needs at international
Input(s)
Output(s)
Purpose (value added)
46
For instance, it could be considered as certain that the implementation of the 4+4+4 structure in the Turkish
education system would raise new needs of Statistical information.
level.
Moreover, following the ongoing implementation of
the ISCED 2011, the UOE in currently under revision
and revised UOE tables will probably be set up by
2014. This will also have an impact on the
Commission Regulation 88-2011 as regards
Statistics on education and training systems which
will be part of the acquis
March
Timetable
2.1.2. CONSULT AND CONFIRM NEEDS
As detailed by UNECE; “this sub-process focuses on consulting with the stakeholders and
confirming in detail the needs for the Statistics. A good understanding of user needs is
required so that the Statistical organization knows not only what it is expected to deliver, but
also when, how, and, perhaps most importantly, why. For second and subsequent iterations of
this phase, the main focus will be on determining whether previously identified needs have
changed. This detailed understanding of user needs is the critical part of this sub-process.”
In the UOE framework, there is not need for such consultation as Statistical needs are already
defined at international level. However, two specific issues should be considered:


International organisations (OECD and European Union) also work as fora where
members express their national concerns about education Statistics and international
comparison. This step could be used as a mean to raise the awareness of national
policy makers about international discussion and as a mean for national policy-makers
and Statisticians to express their view to international data requesters and other
countries.
At national level, policy-makers or other stakeholders may express needs for Statistics
that could be fulfilled by data collected in the UOE framework47.
1.2.
Input(s)
Output(s)
Owner
Consult and confirm needs
Documents and minutes of international meetings at
EU and OECD levels
Documents and minutes of national consultations and
requests.
Documenting the current and future needs at
international and national level
Improving and assessing the matching between
international and national needs for data comparison
on education
47
A pre-requisite would be to create and maintain a list of regular users of Statistics on education within and
outside MoNE.
and documentation)
Timetable
MoNE IT Department
MoNE Legal Experts
International meetings are held on a regular schedule
as well as national consultation and requests. Each
meeting and request should be considered
March
2.1.3. ESTABLISH OUTPUT OBJECTIVES
This sub-process identifies the Statistical outputs that are required to meet the user needs
identified in sub-process 1.2 (Consult and confirm need).
In the framework of the UOE data collection, the output objective are the full completion of all
compulsory UOE tables as defined in the Commission Regulation 88-2011 as regards
Statistics on education and training systems. In case national needs have been identified,
MoNE should establish if the information collected through the UOE data collection meets
national needs. When the UOE data collection does not meet national needs, then MoNE
should identify which output objectives should be reached. Such identified Statistical output
should be considered as suitable and of sufficient quality by users.
1.3.
Establish output objectives
Input(s)
Empty UOE tables as defined for the data collection
of the year
National needs as expressed in step 1.2
Output(s)
Plan and document the necessary steps to collect
raw data48 in line with:
 The evolution of the UOE data collection;
 The improvement of data availability in the
framework of the UOE;
 The new national policy needs
The purpose of this step is to plan (on a yearly basis)
the new data that should be collected or the existing
data which quality should be improved.
Owner
When new policy needs are identified (in terms of
and documentation)
indicators and/or data), a review of existing
methodologies as provided by UIS, OECD and
Eurostat should be conducted.
48
From the Monestat datawarehouse. It could be envisaged to collect new data through the MEBBIS system, but
it goes beyond this report.
Timetable
The emergence of sudden policy needs suggests that
such steps could be performed more frequently than
the frequency of the UOE data collection itself.
March
2.1.4. IDENTIFY CONCEPTS
This sub-process clarifies the required concepts to be measured by the business process from
the point of view of the user. At this stage the concepts identified may not align with existing
Statistical standards.
Despite the need for clarifications on some issues, concepts required are well defined in the
UOE manual (vol.1) and the ISCED classification. It is essential that MoNE keeps monitoring
the conceptual differences between what could be called ‘international concepts’ and ‘national
concepts49’ and document such differences. When national users express some needs, it is
possible that the concepts identified may not align with the UOE standards or other
international Statistical standards. This is for instance the case when national users wish to
have data on dropout rates whereas OECD mainly focuses on completion rate and Eurostat
on “early leavers from education and training”.
This alignment, and the choice or definition of the Statistical concepts and variables to be
used, takes place in sub-process 2.2.
1.4.
Input(s)
Output(s)
Owner
and documentation)
Timetable
Identify concepts
 UOE data collection on education systems
Volume1, Manual, Concepts, definitions and
classifications
 National needs as expressed in step 1.2
Identification of concepts to be measured as
expressed by international and national users
Needs are clarified in terms of Statistical concepts.
Existing methodologies as provided by UIS, OECD
and Eurostat but also research reports available at
national level.
This phase should take place each time new
requests are defined within the UOE framework (e.g.
credit mobility) or each time new needs are
expressed by users.
April
49
The different definitions of non-formal education between international organisations and Turkey is an
example.
2.1.5. CHECK DATA AVAILABILITY
This sub-process checks whether current data sources could meet user requirements, and the
conditions under which they would be available, including any restrictions on their use.
Within MoNE there is no Statistical source that could provide data for the UOE questionnaire.
However, it exist a large administrative data source (i.e. MEBBIS system) that could be/is used
for Statistical purposes. Other reports of this project and other sections of the practical
guideline outline the way the MEBBIS system could be used for Statistical purposes.
If it comes that some gaps in the UOE data requirement still exist, a strategy for filling these
gaps in the data requirement should be prepared50. This strategy has somehow already been
performed in the UOE framework: the TEFBIS project has been implemented to serve
administrative financial management but also to help providing data for the UOE finance
tables. In the course of this project, the information available has been assessed in order to
draft reports from the Monestat datawarehouse and then filling in the UOE tables. Such
process should still be performed when new UOE requirements are set up by international
organisation: for instance, it is planned that citizenship will probably no more be used to collect
data on learning mobility (country of prior education would replace it).
1.5.
Input(s)
Output(s)
Owne
and documentation)
Timetable
Check data availability
Documentation on data available through the
MEBBIS system
Assessment of existing data sources
Strategy for filling remaining data gaps
Improvement of data availability with a focus on UOE
data submission
Statistics Department
Updates of UOE methodology as documented in the
relevant manuals
MoNE IT Department
expressed by users.
April
2.1.6. PREPARE BUSINESS CASE/DOCUMENTATION
As already mentioned in the data collection and dissemination analysis report drafted during
the project, it is essential that all steps of the generic Statistical process are documented. This
50
In addition, as detailed by UNECE: ‘This sub-process also includes a more general assessment of the legal
framework in which data would be collected and used, and may therefore identify proposals for changes to
existing legislation or the introduction of a new legal framework.’
sub-process documents the findings of phase 1, this should serve as a basis to get approval to
implement the new or modified Statistical business process within MoNE (i.e. adaptation of the
Monestat datawarehouse) when new UOE needs or national needs are expressed. As detailed
in the UNCE document, the documentation should include:



“A description of the “As-Is” business process (if it already exists), with information on how
the current Statistics are produced, highlighting any inefficiencies and issues to be
addressed;
The proposed “To-Be” solution, detailing how the Statistical business process will be
developed to produce the new or revised Statistics;
An assessment of costs and benefits, as well as any external constraints.”
1.6.
Prepare business case/Documentation
Input(s)
All information produced during sub-processes 1.1 to
1.5
Output(s)
Documentation of phase 1
Capability to meet new user needs
Owner
and documentation)
expressed by users. A summary on a yearly basis
could be an option
Timetable
April
2.2. PHASE 2: DESIGN
Design
2.1
Design
outputs
2.2
2.3
Design
variables
description
Design data
collection
methodology
2.4
2.5
Design
statistical
processing
methodology
Design
production
systems and
workflow
In the UOE framework, this phase has somehow already been performed before the current
project was launched (Turkey submitted UOE data in the past) and was largely improved and
automated (thanks to the Monestat datawarehouse) during the project.
2.2.1. DESIGN OUTPUTS
In the UOE framework, the design of the Statistical outputs to be produced is already available
(see UOE tables). It is therefore needed to set up the bridge (i.e. Monestat datawarehouse)
between the original data output of the MEBBIS system and the UOE requirements. This
process calls for a strong cooperation between those who manage and develop the MEBBIS
system (Egitek), those who maintain the Monestat datawarehouse and those who are
responsible of the UOE submission (Strategic Departement) to guarantee the sustainability (at
least for international purpose) of the UOE submission process.
2.1.
Input(s)
Output(s)
Owner
and documentation)
Timetable
Design outputs
Design of the UOE tables51
Design of the BI output reports from the MEBBIS
system
Preparation of the ‘bridging’ between MEBBIS BI
reporting system and final UOE tables
MoNE IT Department
expressed by users.
May
2.2.2. DESIGN VARIABLE DESCRIPTIONS
As stated by UNECE, this sub process usually defines ‘the Statistical variables to be collected
via the data collection instrument, as well as any other variables that will be derived from them
in sub-process 5.5 (Derive new variables and Statistical units), and any classifications that will
be used”.
The design of the variable covered by the UOE submission is described by the different UOE
manuals and especially the volume 1. The main classifications are also defined, namely the
ISCED classification and the FOET classification.
The MEBBIS system also already collects administrative information that should be used for
UOE Statistical purpose. The matching of concepts and variables between the MEBBIS
systems and the UOE variable requirements should be continuously assessed especially to
take into account any changes either arising from international data requesters (UOE
perspective) or arising from any change in the variable collected through the MEBBIS system.
51
Please note that a major revision of the design of the UOE table will take place by 2014.
2.2.
Input(s)
Output(s)
Owner
Design variable descriptions
UOE variables
International classifications (e.g. ISCED, FOET)
MEBBIS variables
Design which and how MEBBIS variables are used to
provide UOE variables
Defining the mapping between MEBBIS variables
and UOE variable will allow identifying the final
quality of the UOE submission as well as
documenting the deviation of the Turkish UOE
submission from the international standards
and documentation)
Timetable
MoNE IT Department
expressed by users.
May
2.2.3. DESIGN DATA COLLECTION METHODOLOGY
The UOE data submission is based on administrative data. In Turkey these administrative data
are provided through the MEBBIS system for ISCED levels below tertiary education. One
feature of the Turkish information infrastructure is that it should integrate, for the purpose of
the UOE submission, various administrative data coming from different modules (see sections
4.1) or different institutions (YÖK for information on tertiary education). This step could also
include improvements of the way data is collecting through the MEBBIS system in order to
improve the final UOE Statistical output.
This sub-phase could be more developed when some specific ad-hoc data collection (for
national or international purpose) are set up (e.g. survey on household private expenditure on
education or UOE ad hoc module) to meet some specific needs. In such case, it would be
relevant to design appropriate data collection method(s) and instrument(s).
2.3.
Design data collection methodology
Input(s)
Existing MEBBIS infrastructure
Output(s)
Update data collection methodology
Assess that the data collection methodology is in line
with UOE needs.
Owner
and documentation)
IT Staff Responsible for UOE/Education Statistics
expressed by users.
Timetable
May
2.2.4. DESIGN STATISTICAL PROCESSING METHODOLOGY
The purpose of this sub-process is to draft the specifications of routines of the Monestat
datawarehouse (e.g. routing for coding, editing, imputing, estimating, integrating, validating
and finalising the data sets) when processing the MEBBIS data in phase 5 and phase 6:
A. From the MEBBIS system to the Monestat datawharehouse,
B. From the Monestat datawharehouse reports to the UOE tables.
This sub-process is necessary to guarantee the sustainability of the overall UOE submission
every year. The attributes of the sub-phase should be clearly defined for A and B mentioned
above.
2.4. Design Statistical processing methodology – From MEBBIS to the
Monestat datawharehouse
Input(s
Existing MEBBIS and BI infrastructure
Output(s)
Statistical processing methodology
Describe the Statistical processing that is needed to
complete each of the Monestat datawharehouse
reports from MEBBIS.
Owner
and documentation)
expressed by users.
Timetable
May
The design of the Statistical processing from Monestat datawharehouse reports to UOE tables
means assigning to specific information included in the Monestat datawharehouse reports:
 A specific UOE table52
 A specific cell (within each UOE table). At present cells in the UOE table could be
referenced by the combination of a column label and a row label.53
Whenever necessary, the computation processed to fill in a cell in the UOE table should be
detailed and documented: aggregation of information, specific treatments (e.g. conversion to
Full time equivalent unit), etc.
2.4. Design Statistical processing methodology – Form Monestat
datawharehouse report to UOE
Input(s)
Monestat datawharehouse reports
Output(s)
Description of the computations needed to complete
each UOE table
Describe the Statistical processing that is needed to
complete each of the UOE tables from the Monestat
datawharehouse reports.
Owner
52
This is already done for the current UOE submission thanks to this project but would need to be adapted when
the UOE tables are redesigned.
5353
At this stage, this could not be considered as a unique identifier of the cell. In the ongoing revision for
UOE2014, it is plan that the UOE tables will be redesigned and that each cell will be identified by a unique
identifier.
and documentation)
Timetable
expressed by users.
May
2.2.5. DESIGN PRODUCTION SYSTEMS AND WORKFLOW
As detailed by UNECE, ‘this sub-process determines the workflow from data collection to
archiving, taking an overview of all the processes required within the whole Statistical
production process, and ensuring that they fit together efficiently with no gaps or
redundancies. Various systems and databases are needed throughout the process”.
In the framework of the UOE submission and the specific situation within MoNE, two separate
workflows should be considered and coordinated:
A. Workflow from the MEBBIS system to the Monestat datawharehouse54 which could be
the responsibility of Egitek
B. Workflow from the Monestat datawharehouse to the UOE tables which could be the
responsibility of Strategic department.
One key issue when designing the production system and the workflow is to coordinate both
workflows especially when new developments of the UOE questionnaire are foreseen or
effective.
When designing the overall workflow, it is important to recall that the MEBBIS system (event
driven system) and the UOE have a different timescales55. It is thus neccessary to document
the routines (and timescale) that extract the necessary data that will be pertinent for the
reference date of the UOE.
2.5. Design production system and workflow
Input(s)
Usual workflow within the MEBBIS system
Timescale of the UOE submission as planned by
UOE data requesters
Output(s)
Description of the two workflows (MEBBIS and UOE)
and planning the coordination of the two workflows
Assess that the timetable of the two workflows are
compatible and managing the archived data to take
into account the time lag between the availability of
data through the MEBBIS system and the use of data
for the UOE submission.
54
Togla, I don’t specify here since it should come from the BI side.
55
please see section 4.4.2 of the DPG for more details
Owner
and documentation)
Timetable
On a yearly basis after each UOE submission.
May
2.3. PHASE 3: BUILD
Build
3.1
Build data
collection
instrument
3.2
Build or
enhance
process
components
3.3
Configure
workflows
3.4
3.5
3.6
Test
production
system
Test statistical
business
process
Finalise
production
system
The purpose of this phase is to build and test the production system of Statistics that will be
relevant for the UOE submission. The Monestat datawharehouse has been set up to retrieve
administrative data from the MEBBIS infrastructure to reports that will serve as inputs to the
UOE questionnaires and thus the Turkish UOE submission. As a result, it could be considered
that the data collection instruments is already set up. In the framework of the GSBPM, this
phase occurs at the first iteration. However, it could also occur following a review of the UOE
or a change in the UOE methodology. MoNE will be confronted to such change in the coming
years. Indeed, as presented by international data requesters56, the data collection on
education and training system will impacted by the following in the coming years:


The implementation of ISCED 2011;
A review of the UOE data collection: data requesters have agreed to streamline the
UOE data collection and to adapt it (by 2014)
As a result, this phase will mainly focus on the implementation of a revision of the UOE
methdodology and thus the adaptation of the data collection instrument (i.e. Monestat
datawharehouse).
2.3.1. BUILD DATA COLLECTION INSTRUMENT
The data collection instruments that will be set up by activities during this sub-process will be
used during phase 4 (Collection) and will be created according to the specifications designed
during phase 2 (Design)57. In the framework of the preparation of the UOE submission, data
56
The UOE revision has been discussed during the last Education and Training Working Group held in
Luxembourg in June 2012
57
We recall that data collection should be understood here as the process that will transform raw data available
in the MEBBIS system to ‘raw data’ to be used to complete the Turkish UOE submission. It is however possible
extraction routines (Monestat datawharehouse) are used to gather data from exising
administrative data sets (MEBBIS infrastructure). New UOE methodological developments or
requests would probably lead to build new routines that extract the necessary data from the
MEBBIS infrastructure.
In addition, UNECE points out that “it is recommended to consider the direct connection of
collection instruments to the Statistical metadata system, so that metadata can be more easily
captured in the collection phase. Connection of metadata and data at the point of capture can
save work in later phases. Capturing the metrics of data collection (paradata) is also an
important consideration in this sub-process”.
3.1. Build data collection instruments
UOE methodological changes
Existing Monestat datawharehouse routines
Output(s)
New extraction routines
Meeting new UOE requirements
Owner
and documentation)
Yearly
Timetable
March-April
Input(s)
2.3.2. BUILD OR ENHANCE PROCESS COMPONENT
As detailed by UNECE, “this sub-process describes the activities to build new and enhance
existing software components needed for the business process, as designed in Phase 2
(Design). Components may include dashboard functions and features, data repositories,
transformation tools, workflow framework components, provider and metadata management
tools”. In the framework of the UOE submission, this sub-process would adapt the Monestat
datawarehouse to the new UOE needs expressed by data requesters or changes in
methodology.
that new demands from data requesters would imply the MEBBIS system to collect new raw data, this situation is
not considered here as it goes beyond the scope of this section.
3.2. Build or enhance process component
Input(s)
Output(s)
New extraction routines in Monestat datawharehouse
Owner
and documentation)
Yearly
Timetable
March-April
2.3.3. CONFIGURE WORKFLOWS
As presented by the UNECE, “this sub-process configures the workflow, systems and
transformations used within the Statistical business processes, from data collection, right
through to archiving the final Statistical outputs. It ensures that the workflow specified in subprocess 2.6 (Processing system and workflow) works in practice”. Within the UOE framework,
the purpose of this sub-process is thus to adapt the existing workflow of the Monestat
datawarehouse system to the methodological changes that will occur in the UOE framework.
3.3. Configure workflow
Input(s)
Output(s)
Owner
and documentation)
Yearly
Timetable
May-June
2.3.4. TEST PRODUCTION SYSTEM
In this sub-process, MoNE should test the new routines that have been to implement the
methodological changes or improvement as requested by UOE data requesters. As detailed,
by UNECE: “This sub-process is concerned with the testing of computer systems and tools. It
includes technical testing and sign-off of new programmes and routines, as well as
confirmation that existing routines from other Statistical business processes are suitable for
use in this case.(...) This sub-process also includes testing of interactions between
components, and ensuring that the production system works as a coherent set of
components”.
Input(s)
Output(s)
Owner
and documentation)
Timetable
New extraction routines in Monestat datawharehouse
Testing the new routines in Monestat
datawharehouse
Yearly
May-June
2.3.5. TEST STATISTICAL BUSINESS PROCESS
Once the Monestat datawarhouse has been adapted, new routines should be tested and the
data that are produced should be processed and analyse to ensure that the produced data are
in line with the expected results and the new UOE methodology. As stated by UNECE, “(...)
typically it includes a small-scale data collection, to test collection instruments, followed by
processing and analysis of the collected data, to ensure the Statistical business process
performs as expected”.
2.3.6. FINALISE PRODUCTION SYSTEM
When the tests of the new routines within the Monestat datawarehouse have been performed
successfully, the activities of this sub-process aim at putting the modified and new-built
component of the Monestat datawarhouse in the production environment. As suggested by
UNECE, it includes:



“Producing documentation about the process components, including technical
documentation and user manuals
Training the business users on how to operate the process
Moving the process components into the production environment, and ensuring they
work as expected in that environment (this activity may also be part of sub-process 3.4
(Test production system)).”
Input(s)
Output(s)
Owner
and documentation)
Timetable
Update of the Monestat datawarhouse
Implementing new routines in the production
environment
Yearly
June
2.4. PHASE 4: COLLECT
Collect
4.1
4.2
4.3
Set up
collection
Run
collection
Finalise
collection
As detailed by UNECE, “this phase collects all necessary data, using different collection
modes (including extractions from administrative and Statistical registers and databases), and
loads them into the appropriate data environment. It does not include any transformations of
collected data, as these are all done in phase 5 (Process). For Statistical outputs produced
regularly, this phase occurs in each iteration”.
In the framework of the UOE submission the collection of data means extracting from
administrative register (MEBBIS) the needed information and load them in the appropriate
environment (Monestat datawarhouse) to then complete the UOE tables (Excel).
Despite the MEBBIS infrastructure collects data on a event-driven basis, it is not the case for
the UOE data wich only needs aggregated data once a year. It could then be considered that
the ‘pure’ UOE data collection (through the Monestat datawarhouse) is performed once a
year58.
58
If one considers data collection for specific national needs, then it could be considered that the data collection
run at a higher frequency.
2.4.1. SET UP COLLECTION
This sub-process should ensure that the people (from MoNE), processes (Monestat
datawarhouse) and technology are ready to collect data. Since, the Monestat datawarhouse
has already been set up, this sub process will focus on the update of the Monestat
datawarhouse when UOE data requests changes (or when new national needs that could not
be fulfilled by the current system are expressed).
The Monestat datawarhouse should be sustainable over time and this sub-process should
organise the adaptations that are required by the new development of the UOE data collection.
Indeed, in the near future, the implementation of the ISCED 2011 classification and the
redesign of the UOE tables will call for some adaptations of the Monestat datawarhouse.
Input(s)
Output(s)
Owner
and documentation)
Timetable
4.1. Set up collection
Changes of the content or UOE tables requested by
data requester UOE data requesters
Adaptation of the Monestat datawarhouse in setting
up de data collection
Ensure the sustainability of the data collection system
and comply with possible new requirement as
expressed by international (or national) data
requesters.
Statistics Department and UOE Staff
Monthly basis
2.4.2. RUN COLLECTION
“This sub-process is where the collection is implemented, with the different collection
instruments being used to collect the data. For administrative data, this process is brief: the
provider is either contacted to send the data, or sends it as scheduled”. In the framework of
the UOE submission, it could be considered that running the collection means basically to
process the Monestat datawarhouse reporting system. This assumes that the ‘administrative
data collection’ through the MEBBIS system is completed.
Due to the nature of the MEBBIS system, a good coordination is needed to determine the best
timetable to extract the data through the Monestat datawarhouse. The time lag between the
time when the MEBBIS system is fully completed and the time when data should be sent to
UOE data requesters should be considered with caution and need a proper archiving of the
data for each specific reference year.
4.2. Run collection
Changes of the content or UOE tables requested by
data requester UOE data requesters
Data in the UOE format
Collect the data through Monestat datawarhouse
reports in UOE format.
Input(s)
Output(s)
Owner
and documentation)
Timetable
Monthly basis
2.4.3. FINALISE COLLECTION
This sub-process includes loading the collected data and metadata into a suitable electronic
environment for further processing in phase 5 (Process). This phase is performed through the
Monestat datawarhouse infrastructure.
In the framework of the UOE submission, it also includes converting the formats of data files
received from other organizations (e.g. YÖK for data on tertiary education) in an appropriate
format for further processing. This task is out of the scope of the Monestat datawarhouse but
should still be performed in the framework of the UOE submission.
2.5. PHASE 5 – PROCESS
Process
5.5
5.1
5.2
Integrate
data
Classify
and code
5.3
Review,
validate
and edit
5.4
Estimation
Derive
new
variables
and
statistical
units
5.6
Calculate
aggregates
5.7
Finalise
data files
As described by UNECE, this phase “describes the cleaning of data records and their
preparation for analysis. It is made up of sub-processes that check, clean, and transform the
collected data, and may be repeated several times. For Statistical outputs produced regularly,
this phase occurs in each iteration.” In addition, the sub-processes in this phase can apply to
data from both Statistical and non-Statistical sources (except sub-process 5.6 (Calculate
weights) in the framework of the UOE submission.
2.5.1. INTEGRATE THE DATA
As detailed by UNECE; “this sub-process integrates data from one or more sources”. This is
performed by the Monestat datawarhouse which integrates data from various modules of the
MEBBIS systems. However, the UOE submission has to integrate data from the Monestat
datawarhouse (for data from ISCED level 0 to ISCED level 4) but also from YÖK (for data on
tertiary education: ISCED level 5 and 6), and from the e-non formal module and TEFBIS
module (for finance data).
Data integration typically includes:

“matching / record linkage routines, with the aim of linking data from different sources,
where those data refer to the same unit;
 prioritising, when two or more sources contain data for the same variable (with potentially
different values).”
The result is an harmonized data set.
Input(s)
Output(s);
Owner
and documentation)
Timetable
5.1. Integrate data
Monestat datawarhouse reports
YÖK data (tertiary education)
Harmonized data set
Integrate all data that are relevant for the UOE
submission
June-July-August
2.5.2. CLASSIFY AND CODE
In this sub-process, the new routines of Monestat datawarhouse should ensure that data are
properly classfied and coded according to international classifications (mainly ISCED and
FOET) . To this end, the Turkish ISCED mapping (see section 3.8) should be used in order to
guaranty that all records are properly classified. It should be borne in mind that if this process
is automated in the Monestat datawarhouse (and thus for ISCED level 0 to 4)59, it is not for
data on tertiary education.
2.5.3. REVIEW, VALIDATE AND EDIT
As noted by UNECE, “this sub-process (...) looks at each record to try to identify (and where
necessary correct) potential problems, errors and discrepancies such as outliers, item nonresponse and miscoding. It can also be referred to as input data validation. It may be run
59
However, the implementation of ISCED 2011 will have an impact on this sub-process since the UOE data
collection will use ISCED 2011 by 2014.
iteratively, validating data against predefined edit rules, usually in a set order. It may apply
automatic edits, or raise alerts for manual inspection and correction of the data. Reviewing,
validating and editing can apply to unit records both from surveys and administrative sources,
before and after integration”.
Despite such sub-process is applies to micro data (that are not collected through the Monestat
datawarhouse but the MEBBIS system, this phase could apply as an intermediate steps before
reporting to the UOE tables.
2.5.4. ESTIMATION
For UNECE, “Where data are missing or unreliable, estimates may be imputed, often using a
rule-based approach”. This sub-process could then be considered as the one where
estimations are processed when some data are missing.
The specific steps when performing estimation in the framework of the UOE submission would
typically include:





the identification of data gaps (or potential errors identified in the data provided by the
MEBBIS and other related systems) in the past and present UOE submission;
the selection of data to include or exclude from estimation routines;
estimation using one or more pre-defined methods (see section 7);
writing the estimated data back to the data set, and flagging them as estimated;
the production of metadata on the estimation process;
Input(s)
Output(s)
Owner
and documentation)
Timetable
5.4. Estimation
Monestat datawarhouse reports
YÖK data (tertiary education)
Harmonized data set with less missing data
Remove data gaps
June-July-August
2.5.5. DERIVE NEW VARIABLES AND STATISTICAL UNITS
As describes by UNECE, “this sub-process derives (values for) variables and Statistical units
that are not explicitly provided in the collection, but are needed to deliver the required outputs.
It derives new variables by applying arithmetic formulae to one or more of the variables that
are already present in the dataset. This may need to be iterative, as some derived variables
may themselves be based on other derived variables. It is therefore important to ensure that
variables are derived in the correct order.”
This stage is performed by the Monestat datawarhouse. When the UOE submission changes
due to new data requests (from international organisations); it should be investigated if new
variables could be derived from existing ones. In this sub-process, MoNE Strategy
Development Presidency will lead the process of detaling and transmitting the new
international requests to MoNE IT department.
2.5.6. CALCULATE AGGREGATES
The UNECE specifies that “this sub process creates aggregate data and population totals from
micro-data. It includes summing data for records sharing certain characteristics, determining
measures of average and dispersion (…)”.
This step is performed by the Monestat datawarhouse. In case, new aggregates are requested
by international data requesters, it should be determined if this new request can be performed
manually or should be better performed thanks to an adaptation of the Monestat
datawarhouse.
When aggregate have to be performed for all ISCED levels (i.e. from ISCED level 0 to ISCED
level 6), data from the Monestat datawarhouse and from YÖK should be aggregated after the
Monestat datawarhouse reports have been produced. It should be borne in mind that,
currently60, sub-totals and totals are automatically performed in the UOE tables that are
provided by UOE data requesters.
Input(s)
Output(s)
Owner
and documentation)
Timetable
5.6. Calculate aggregate
Data from Monestat datawarhouse
Data from YÖK
Aggregated data
June-July-August
2.5.7. FINALISE DATA FILES
In the GSBPM, “This sub-process brings together the results of the other sub-processes in this
phase and results in a data file (usually of macro-data), which is used as the input to phase 6
(Analyse). Sometimes this may be an intermediate rather than a final file, particularly for
60
This would probably change with the UOE2014 since it is planned to avoid including total and subtotals in the
UOE tables.
business processes where there are strong time pressures, and a requirement to produce both
preliminary and final estimates.”
In the framework of the UOE submission, this sub-process could consist of a “preliminary UOE
submission file” that would serve as input for a more analytical phase (phase 6) but also (when
the validation of output – sub process 6.2 is performed) to produce the final UOE submission
to be sent to international data requesters.
Input(s)
Output(s)
Owner
and documentation)
Timetable
5.7. Finalise data files
Results of sub-processes 5.1, 5.4, 5.5 and 5.7
Pre (?) final UOE submission
Preparing a pre-final UOE submission for analysis
August
2.6. PHASE 6 – ANALYSE
Analyse
6.4
6.1
6.2
6.3
Prepare draft
output
Validate
output
Scrutinize and
explain
Apply
disclosure
control
6.5
Finalize
output
The purpose of the UOE data collection is to provide comparable data to international
organisations. One of the final purposes of the exercise is to compare education systems
across the World. As such, in this framework, it could be argued that the analytical phase
(comparative analysis) should be/is performed by international organisations. Nonetheless, it
could also be argued that the UOE data submission provide data that are also relevant for
national purposes and should be used as such.
2.6.1. PREPARE DRAFT OUTPUT
UNECE states that “this sub-process is where the data collected are transformed into
Statistical outputs. It includes the production of additional measurements such as indices,
trends or seasonally adjusted series61, as well as the recording of quality characteristics”.
61
This latter is not relevant in the UOE framework.
These components are not part of the UOE data submission which does not include Statistical
indicators as such. However, MoNE could use the data that are included in the UOE data
submission for calculating trends and indices for national purposes and as the preparation of
the national Statistical validation of the UOE data.
Input(s)
Output(s)
Owner
and documentation)
Timetable
6.1. Prepare draft output
Results of preceding phase, especially phase 5 and
pre-final UOE submission
Finalised UOE submission
Validating the pre-final UOE submission
September
2.6.2. VALIDATE OUTPUT
UNECE states that “this sub-process is where Statisticians validate the quality of the outputs
produced, in accordance with a general quality framework and with expectations. This subprocess also includes activities involved with the gathering of intelligence, with the cumulative
effect of building up a body of knowledge about a specific Statistical domain. This knowledge
is then applied to the current collection, in the current environment, to identify any divergence
from expectations and to allow informed analyses”.
In the framework of the UOE, validation activities can include:
• Checking that the population coverage is as required by the UOE methodology;
• Comparing the Statistics with previous cycles of the UOE submission (to detect
potential break in series, outliers, etc.);
• Confronting the Statistics against other relevant data (both internal and external);
• Investigating inconsistencies in the Statistics (e.g. population of students of unexpected
ages in some ISCED levels, unpossible age groups, number of enrolled students higher
that the total population of the age group, etc.);
• Performing macro editing;
• Validating the Statistics against expectations and domain intelligence.
Such validation phase is important to guaranty the Statistical quality of the UOE sumbission. It
should be mentioned that UOE questionnaires already contain in-built checking procedures
that help validating the output.
Input(s)
Output(s)
Owner
and documentation)
Timetable
6.2. Validate output
Results of preceding phase, especially phase 5 and
sub-process 6.2
Validated output
Validating the pre-final UOE submission
IT Staff Responsible for UOE/Education
StatisticsMoNE All Related Departments
Legal Experts
September
2.6.3. SCRUTINIZE AND EXPLAIN
AS detailed by UNECE, “this sub-process is where the in-depth understanding of the outputs
is gained by Statisticians. They use that understanding to scrutinize and explain the Statistics
produced for this cycle by assessing how well the Statistics reflect their initial expectations,
viewing the Statistics from all perspectives using different tools and media, and carrying out indepth Statistical analyses”.
The purpose of this sub-process when preparing the Turkish UOE submission is to sctrutinize
the data that have been gathered through the MEBBIS infrastructure and the Monestat
datawarhouse and to check the consistency of data through time and with regard the UOE
methodology. When deviations from the UOE methodology are identified (but could not
immediately be solved thanks to an adaptation of the Monestat datawarhouse), they should be
explained and their impact should possibly be assessed. Finally, they should be documented
in the quality report (as metadata) that is due to Eurostat62.
Input(s)
Output(s)
Owner
6.3. Scrutinize and explain
Validated output
Report explaining the Statistics that are produced,
their consistency over time and their compliance with
the UOE methodology
Guarantee and report on the quality of the UOE
submission
62
As part of the regulation 88/2011 Member States will be asked to provide a quality report on the UOE data
submission.
and documentation)
Timetable
September
2.6.4. APPLY DISCLOSURE CONTROL
As specified by the UNECE, “This sub-process ensures that the data (and metadata) to be
disseminated do not breach the appropriate rules on confidentiality. This may include checks
for primary and secondary disclosure, as well as the application of data suppression or
perturbation techniques.”
This part is not relevant in the framework of the UOE submission include agregated data.
However, for some specific cases, confidential issue could be raised. This could be for
instance when the number of incoming mobile students (tertiary education) by country of origin
is requested. For some country of origin, the number could be very low and could raise some
confidentiality issue.
2.6.5. FINALIZE OUTPUTS
In the UOE framework, this sub-process aims at finalising the Turkish UOE submission an to
send it to the international data requesters according to the international timetable.
As specified by UNECE, this sub-process “ensures the Statistics and associated information
are fit for purpose and reach the required quality level, and are thus ready for use”.
Regarding the Turkish UOE submission, it includes:
•
“completing consistency checks;
•
collating supporting information, including interpretation, briefings, measures of
uncertainty and any other necessary metadata”;
If it is decided that the UOE submission serves as a basis for disseminating data at national
level and through national channels, then, the following items could be included in this subprocess:
•
“determining the level of release, and applying caveats;
•
producing the supporting internal documents;
•
pre-release discussion with appropriate internal subject matter experts;
•
approving the Statistical content for release.”
This sub-process should ensure that all the UOE in-build checks are performed and don’t raise
any alert.
Input(s)
Output(s)
Owner
and documentation)
Timetable
6.4. Finalize outputs
Validated output and reports under tasks 6.3
Final UOE questionnaires
Comply with international requirements
September
2.7. PHASE 7 – DISSEMINATE
Disseminate
7.1
7.2
Update
output
system
Produce
dissemination
products
7.3
Manage
release of
dissemination
products
7.4
Promote
dissemination
products
7.5
Manage user
support
As detailed by UNECE, “this phase manages the release of the Statistical products to
customers. For Statistical outputs produced regularly, this phase occurs in each iteration”. In
the framework of the UOE submission, this phase could be understood in two ways:
1. Dissemination could be understood as the sending to the 3 international “customers”
i.e. the three data requesters namely the UNESCO-UIS, OECD and Eurostat. In this
case, dissemination is thus limited to the sending of the UOE submission to these
international organisation. OECD and Eurostat will then disseminate the Turkish data
through their dissemination channels63.
2. Dissemination could be understood as the dissemination of the UOE data (i.e. the data
that are produced for UOE purpose are disseminated along with the data that are
usually disseminated by MoNE every year64. In this case, the following sub-processes
may be considered. In Turkey, the main dissemination channel is made up of the two
63
For more information on them, please see “Data Collection and Dissemination Analysis Report”, section 3.4.
64
For more information on them, please see “Data Collection and Dissemination Analysis Report”, section 3.3.
yearly reports65: National Education Statistics – Formal education and National
Education Statistics – Non-formal Education, that are prepared by the Ministry of
National Education (MEB) with the contribution of the Turkish Statistical Institute within
the framework of Official Statistics Programme. A second dissemination channel is
provided by TUÏK through its website66. TUÏK disseminates a selection of fixed tables
from the above-mentioned reports on formal and non formal education under in
spreadsheet format.
The following sub-sections briefly describe the sub-processes at stake if MoNE decides to
develop the dissemination of UOE data at national level. The following sub-process are
provided here for information since the definition of the content of each of them and the
owners and enablers will depend on the type of dissemination supports that are preffered by
MoNE (web database, additional paper reports, etc.)
2.7.1. UPDATE OUTPUT SYSTEM
As specified by UNECE, “This sub-process manages the update of systems where data and
metadata are stored for dissemination purposes, including:
 formatting data and metadata ready to be put into output databases;
 loading data and metadata into output databases;
 ensuring data are linked to the relevant metadata67”.
2.7.2. PRODUCE DISSEMINATION PRODUCTS
As presented by UNECE, “this sub-process produces the products, as previously designed (in
sub-process 2.1), to meet user needs. The products can take many forms including printed
publications, press releases and web sites”. Typical steps include:
 preparing the product components (explanatory text, tables, charts etc.);
 assembling the components into products;
 editing the products and checking that they meet publication standards”.
2.7.3. MANAGE RELEASE OF DISSEMINATION PRODUCTS
As specified by UNECE, “This sub-process ensures that all elements for the release are in
place including managing the timing of the release. It includes briefings for specific groups
such as the press or ministers, as well as the arrangements for any pre-release embargoes. It
also includes the provision of products to subscribers”.
65
This mention is only provided in the report on Formal education.
66
Please see: http://www.TUÏK.gov.tr/VeriBilgi.do?tb_id=14&ust_id=5
67
UNECE notes that “formatting, loading and linking of metadata should preferably mostly take place in earlier
phases, but this sub-process includes a check that all of the necessary metadata are in place ready for
dissemination.”
2.7.4. PROMOTE DISSEMINATION PRODUCTS
As specified by UNECE, “Whilst marketing in general can be considered to be an over-arching
process, this sub-process concerns the active promotion of the Statistical products produced
in a specific Statistical business process, to help them reach the widest possible audience. It
includes the use of customer relationship management tools, to better target potential users of
the products, as well as the use of tools including web sites, wikis and blogs to facilitate the
process of communicating Statistical information to users”.
2.7.5. MANAGE USER SUPPORT
As specified by UNECE, “this sub-process ensures that customer queries are recorded, and
that responses are provided within agreed deadlines. These queries should be regularly
reviewed to provide an input to the over-arching quality management process, as they can
indicate new or changing user needs”.
Input(s)
Output(s)
Owner
and documentation)
Timetable
7. Disseminate
Publication of the UOE data in various formats
(Statistical book, analytical report for internal (i.e.
MoNE) or external purposes, database, etc.)
Develop knowldege on Turkish education system
MoNE IT Department
January - April
2.8. PHASE 8 – ARCHIVE
Archive
8.1
Define
archive rules
8.2
Manage
archive
repository
8.3
Preserve data
and
associated
metadata
As detailed by UNECE, “this phase manages the archiving and disposal of Statistical data and
metadata. Given the reduced costs of data storage, it is possible that the archiving strategy
adopted by a Statistical organization does not include provision for disposal, so the final sub-
process may not be relevant for all Statistical business processes. In other cases, disposal
may be limited to intermediate files from previous iterations, rather than disseminated data.
For Statistical outputs produced regularly, archiving occurs in each iteration, however defining
the archiving rules is likely to occur less regularly. This phase is made up of four subprocesses, which are generally sequential, from left to right, but can also occur in parallel, and
can be iterative”.
2.8.1. DEFINE ARCHIVE RULES
As detailed by UNECE, “this sub-process is where the archiving rules for the Statistical data and
metadata resulting from a Statistical business process are determined. The requirement to archive
intermediate outputs such as the sample file, the raw data from the collect phase, and the results of the
various stages of the process and analyse phases should also be considered. (...) The rules should
include consideration of the medium and location of the archive, as well as the requirement for keeping
duplicate copies. They should also consider the conditions (if any) under which data and metadata
should be disposed of.”
At present, it seems that there was no commonly agreed archiving rule within the SDP, for the
Statistical data used to prepare the Turkish UOE submission. The archiving rule for the UOE
Statistical business process should fully or partially follow the more general archiving policy at
stake in MoNE or in the Turkish government sector. However, in this phase, MoNE should
define the archiving rules for the Statistical data and metadata resulting from the UOE
Statistical business process. It means that during this phase, MoNE (SDP) should define:

Which Statistical output should be archived: it is suggested to consider archiving:
o the ‘raw’ data that are provided by the Monestat datawarhouse (from the
MEBBIS and TEFBIS infrastructures);
o the final data that are used to complete the UOE questionnaire;
o the steps and intermediary results of the data processing that occured, if any,
after the Monestat datawarhouse provided the data (phase 5);
o the necessary metadata that were identified during phase (phase 6).
 Which medium and where, MoNE archive the above mentioned archived elements;
 Which duplication are necessary.
8.1. Define archive rules
Input(s)
Final UOE questionnaires and by-products from any
intermediate steps from the Monestat datawarhouse
Output(s)
Properly organised archive of the Statistical business
process
Sustainability of the UOE data collection process
Owner
and documentation)
Timetable
January
2.8.2. MANAGE ARCHIVE REPOSITORY
As detailed by UNECE, “this sub-process concerns the management of one or more archive
repositories. These may be databases, or may be physical locations where copies of data or
metadata are stored. It includes:




maintaining catalogues of data and metadata archives, with sufficient information to ensure
that individual data or metadata sets can be easily retrieved;
testing retrieval processes;
periodic checking of the integrity of archived data and metadata;
upgrading software-specific archive formats when software changes.”
As mentioned in the previous section (sub-process 8.1), the “raw” data that are archived
during this sub-process are the one provided through the Monestat datawarhouse (and used
to complete the UOE submission). Thus, this sub-process covers the specific UOE Statistical
business process but could follow the standardised management of the archive repository of
MoNE if existing.
Input(s)
Output(s)
Owner
8.2. Manage archive respository
Final UOE questionnaires and by-products from any
intermediate steps from the Monestat datawarhouse
process
and documentation)
Timetable
March
2.8.3. PRESERVE DATA AND METADATA
As presented by UNECE, “this sub-process is where the data and metadata from a specific
Statistical business process are archived. It includes: identifying data and metadata for
archiving in line with the rules defined in 8.1; formatting those data and metadata for the
repository; loading or transferring data and metadata to the repository; cataloguing the
archived data and metadata and verifying that the data and metadata have been successfully
archived”.
This sub-process is of paramout importance to allow keeping track of all data and meta data of the
successive Turkish UOE submissions and exist in the Monestat datawarehouse. It would help
guaranteeing the sustainability of the overall UOE submission process through the years and help
disseminating the ‘UOE knowledge’ to new stakeholders within MoNE.
Input(s)
Output(s)
Owner
8.3. Preserve data and meta data
process
and documentation)
Timetable
March
2.9. PHASE 9 – EVALUATE
Evaluate
9.1
Gather
evaluation
inputs
9.2
9.3
Conduct
evaluation
Agree action
plan
As specified by UNECE, this phase “manages the evaluation of a specific instance of a
Statistical business process”; the purpose of the.phase is thus for MoNE to evaluate each of
the specific instances of the UOE submission process in order to determine if any
improvement should be implemented before the next UOE submission. As the UOE is a
regular data collection, “evaluation may not be formally carried out for each iteration. In such
cases, this phase can be seen as providing the decision as to whether the next iteration
should start from phase 1 (Specify needs) or from some later phase (often phase 4 (Collect))”.
2.9.1. GATHER EVALUATION INPUT
Gathering evaluation material (such as comments from international data requesters,
suggestion from MoNE staff, etc.) could be processed at each phase or each sub-process of
the UOE submission process. Eurostat usually informs countries68 about how the UOE
deadlines were met during each data collection process. As stated by UNECE, “evaluation
material can be produced in any other phase or sub-process. It may take many forms,
including feedback from users, process metadata, system metrics and staff suggestions.
Reports of progress against an action plan agreed during a previous iteration may also form
an input to evaluations of subsequent iterations. This sub-process gathers all of these inputs,
and makes them available for the person or team producing the evaluation”.
Input(s)
Output(s)
Owner
and documentation)
Timetable
9.1. Gather evaluation input
Process at each phase and each sub-process
Compendium of evaluation material
Improve the next UOE data collection process
March
2.9.2. CONDUCT EVALUATION
Once MoNE has gathered the relevant materials (sub-process 9.2), it should appoint a person
or a group of persons to conduct the evaluation and make the relevant materials available to
them. As detailed by UNECE, “this sub-process analyzes the evaluation inputs and
synthesizes them into an evaluation report. The resulting report should note any quality issues
specific to this iteration of the Statistical business process, and should make recommendations
for changes if appropriate. These recommendations can cover changes to any phase or subprocess for future iterations of the process, or can suggest that the process is not repeated”.
Input(s)
Output(s)
Owner
and documentation)
68
9.2. Conduct evaluation
Evaluation report and recommendation for
improvement
Usually during the yearly Education and Training Working Group (ETS WG) in Luxembourg
Timetable
March
2.9.3. AGREE ACTION PLAN
Once the recommendations aiming at improving the UOE submission process have been drafted,
MoNE should agree on an action plan that will implement these recommendations. As presented by
UNECE, “this sub-process brings together the necessary decision-making power to form and agree an
action plan based on the evaluation report. It should also include consideration of a mechanism for
monitoring the impact of those actions, which may, in turn, provide an input to evaluations of future
iterations of the process”.
Input(s)
Output(s)
Owner
and documentation)
Timetable
9.3. Agree action plan
Evaluation report and recommendation for
improvement
March
2.10. QUALITY MANAGEMENT AND METADATA MANAGEMENT
The quality management process is linked to the evaluation phase (phase 9). The quality
management process of the UOE submission should take place in the specific quality
framework in place in MoNE.
As detailed by UNECE, ‘quality management can take several forms, including:
 Seeking and analysing user feedback;
 Reviewing operations and documenting lessons learned;
 Examining process metadata and other system metrics;
 Benchmarking or peer reviewing processes with other organizations.
In the framework of the UOE submission, feedback could come from international
organizations that ask for checks and clarifications about the UOE data submitted by Turkey.
Feedback from users could also be national if UOE data are disseminated (phase 7) at
national level. It is advised to review regularly (every year) the operation that were processed
during all the phases and sub-processes that took place for a UOE submission in order to
document the lessons learned during its preparation.
Within the European Statistical System, data providers also have to report on the quality of the
Statistical data they provide to Eurostat (see section 10) which suggests a good metadata
management. As stated by UNECE, “metadata are present in every phase, either created or
carried forward from a previous phase”. Furthermore, “the emphasis of the over-arching
process of metadata management is on the creation and use of Statistical metadata”. As for
any institution, the key challenge for MoNE (and especially SDP) “is to ensure that these
metadata are captured as early as possible, and stored and transferred from phase to phase
alongside the data they refer to. Metadata management strategy and systems are therefore
vital to the operation of this model”.
Section D. TECHNICAL PROCEDURES ON UOE DATA
SUBMISSION PROCESS IN TURKEY
1
BUSSINES INTELIGENCE
SUBMISSION PROCESS
PROCEDURES
ON
UOE
DATA
1.1. STATISTICS SUBJECT AREAS





Public & Private Institutions
Formal Education Student Data
o Preprimary
o Primary
o Secondary
Formal Education Teachers Data
Formal Education Finance Data
Non-Formal Course&Student Data
The Statistical subject areas are listed above. During the 2.7. activities TAT IT team
started BI work from the prioritized subject which was "Public & Private Institutions". After
the completion of one selected subject, IT team continued to work on the next Statistical
subject area. Acording to time and working man-days, subject areas was choosen with
SDP and IT department candidates and harmonized into BI system. Each subject area
has many sub-subject areas. According to their priorities, IT team was jointly work with IT
experts within the Ministry during the analyse and pre-design phase.
1.2. STATISTIC FLOW, NETWORK AND BI ARCHITECTURE
FIGURE 2 Statistics Flow Within the Ministry
The main source for Statistics is MEIS Querying System for MoNE. By using MEIS Querying
System and some additional queries from Discoverer (when needed) , MoNE experts prepared
national publication data. By using referenced data into publications, UOE data tables are
prepared by the experts.
FIGURE 3 Source and Target of BI Architecture
The main modules for the Statistics especially in national publications and UOE data tables
will be used as a source in the BI workflow. But, TAT can not have direct access to the original
sources because of the data security within the Ministry. The summary tables are defined by
IT experts within the Ministry and put into staging area for TAT access. This flow was
described on Figure 3. Data warehouse design and ETL transform packages were done by
TAT during the project. The data warehouse platform will be used as a source in the report
development phase, and dashboard reports will be the main target of BI workflow.
Even some tables are used directly from the staging area, most of the data structures created
for BI applications are stored in MONESTAT schema. Tables, views and materialized views
are created in this schema and the summary data in the staging area is transformed and
transferred into this objects due to the project’s requirements. The structures of the summary
tables are determined in collaboration with the MoNE experts, but the responsibility of
developing the queries producing these results belong to MONE IT experts.
FIGURE 4 BI Network Flow
1.3. BI WORKFLOW
 Prioritizing Subject Areas
 For Each Subject;
 Requirement Analysis &Target Database Design
 Data transfer process (ETL)
 Reaching source database(s)
 Extracting and transforming dat
 Loading data into destination storage
 Data warehouse design
 Data warehouse table design
 Design of dimensions, hierarchies and measurements
 Preparing reports
 Preparing reports for presenting Statistics by using designed data
warehouse objects
 Using OracleBI Analysis development platforms
 Preparing dashboards
 Authorization and authentication
FIGURE 5 Design & Development Life Cycle
1. "Prioritized Sub-Subject Area" was choosen by MoNE
2. Study choosen sub-subject with IT department of MoNE and clarify source tables,
target tables and structure, ETL contraints, BI dimensions&measures and possible
reports(outputs)
3. A pre-design document for the choosen subject was prepared by TAT
4. Pre-design document content was discussed with SDP and relevant General
Diroctoriates.
5. After getting confirmation of the pre-design phase, design, ETL and report development
phase can be started.
1.4. ETL CONSTRAINTS OF PUBLIC AND PRIVATE INSTITUTIONS
A. Source Tables:
The source environment for the ETL process is the data warehouse server. This server will be
used as a staging area and the target database for the BI application is based upon the types
and scopes of the data located in this area. The all source tables are under the ILSISWEB
schema.
DK_KURUM_ANA: The definitions of the all public institutions are recorded in this table.
Institution name, province, district, location of residence, type of institution and the general
directorate responsible for the institution are some attributes which are located in this table.
DK_HIZMETE_GIRIS : The entrance of service records including the type and year
information for the for public institutions are recorded in this table.
DK_KURUM_ACMA_ISTEK : The applications made for the openings of the public institutions
are recorded into this table. The opening dates of the institutions are derived from this table.
DK_KURUM_HAREKETLERI : The changes in the definitions for the public institutions are
recorded in this table. The former knowledge such as the name, province or district information
about the public institutions will be supplied from this table.
DK_BINA_BILGILERI : The number of buildings of public institutions by means of ownership
status, heating type, rental information and fuel types are recorded into this table. In addition
to this; the building and garden areas are also derived from this table.
DK_BINA_KULLANIM : The number of usage areas for the public institutions due to usage
area type are located in this table.
DK_KUTUPHANE_MATERYAL : The number of materials located in the libraries of public
institutions and the number of beneficiary students for these materials are recorded in this
table.
OK_KURUM_ANA: The definitions of the all private institutions are recorded in this table.
Institution name, province, district, location of residence, type of institution and the general
directorate responsible for the institution are some attributes which are located in this table.
OK_KURUM_HAREKET : The changes in the definitions for the private institutions are
recorded in this table. The former knowledge such as the name, province or district information
about the priavate institutions will be supplied from this table.
OK_BINA_BILGILERI : The number of buildings of private institutions by means of ownership
status, heating type, rental information and fuel types are recorded into this table. In addition
to this; the building and garden areas are also derived from this table
OK_BINA_KULLANIM : The number of usage areas for the private institutions due to usage
area type are located in this table.
B. Target Tables:
The ETL process for the Institutions application uses the source tables enlisted above and
inserts the data into the target tables after making approriate transformations. The target
tables that are determined by TAT and confirmed by IT Group Presidency experts are defined
below..
ST_KURUM_TUR : The institution type definitions and the auxiliary attributes which are used
in concept hierarchies are recorded in this dictionary table. This table is designed as a
dimension table. The name of the institution type, public/private/open discrimination, level of
education, formal/non-formal status, domestic/foreign data, general/vocational and education
institutions/Administrative institution data are located in this table.
FIGURE 6 - Table Description of ST_KURUMTUR
ST_KURUMLAR : The all dictionary information about the institutions of MoNE regardless of
being public or private is recorded in this table. In some circumstances for both ; the name, the
type or location of residence columns may be changed without changing its institution code.
Because of this fact, a need for an historical dimension is raised. In order to meet this
requirement a column namely “ISLEM_TARIHI” is added into the definition and the primary
key. As a result of this design choice, all foreign key references to ST_KURUMLAR table
should include a column referencing this date information.
The type code of the institution is also added into primary key, while vocational schools may
have more than one sub type. Finally the primary key of the ST_KURUMLAR table included
the columns ISLEM_TARIHI, KURUM_KODU and KURUM_TURU, which refers processing
date, institution code and type code respectively.
FIGURE 7 Table Description of ST_KURUMLAR
FACT_KURUMLAR : The all measure information related with public and private information is
located in this table. Unlike ST_KURUMLAR; this table is organized as a fact table. The most
important function of the table is providing the number of institutions information for the
requesting BI applications. The number of institutions can be queried by means of their status,
levels of education, location of residence, institution types etc. by using ST_KURUMLAR and
ST_KURUMTUR dimensions. In addition to this; the table also holds information about the
pension capacities, public house numbers, number of beneficiary student from libraries.
FIGURE 8 Table Description of FACT_KURUMLAR
FACT_KURUM_BINA : The number of buildings that belong to public and private institutions
by means of ownership, heating type, fuel type and rental situation is stored in this table. In
addition to this, the building and garden areas of each building is also recorded into this table.
FIGURE 9 Table Description of FACT_KURUM_BINA
FACT_KURUM_KULLANIM_ALAN : The number of usage areas for each institution by means
of usage area type is stored in this table. The “usage area” term refers to all types of divisions,
such as classrooms, laboratories, ateliers etc. which can be a part of the physical capacity of
an educational institution. By using this table; the knowledge about all usage areas can be
queried also in a historical view. Besides, these queries may also be issued by means of
location of residence and type of institution hierarchies.
FIGURE 10 Table Description of FACT_KURUM_ KULLANIM_ALAN
FACT_KURUM_KUTUPHANE_MATERYAL : This table stores information about the library
materials by means of material types. The information includes the stock by the end of last
year, the incoming and the out coming amounts for the current year of the library materials for
all public institutions.
FIGURE 11 Table Description of FACT_KURUM_KUTUPHANE_MATERYAL
C. ETL Constraints:
a. ST_KURUM_TUR table consists of the institution type records used in various
applications of the MoNE and located in ILSISWEB schema. In addition to current
attributes, some attributes which will be used in Business Intelligence application will
be added into this table. The inserts and updates to the original table should be
reflected to the table used for BI applications and this mechanism should be under
control of experts of the Data Processing Group Presidency.
b. The data transfer to ST_KURUMLAR table will be according to the processing date
(namely ISLEM_TARIHI) As a result of the developed ETL approach, the data transfer
period can be daily or monthly. The transfer will cover the organization types which
come into service before the processing date. The situation of the organization will be
recorded by the tags “Open”, “Closed” and “Transferred”. The cause of being closed
will also be registered for each “Closed” institution.
c. The
transaction
tables,
namely
DK_KURUM_HAREKETLERI
and
OK_KURUM_HAREKET will be used for the data transfer to be accomplished for the
ST_KURUMLAR table. These transaction tables include the unmodified data of the
institution before a change has been held. If any problem about this recording phase
has been occurred due to some known or unknown error, there will be no possibility for
accessing previous information about the institution. The usage of the transaction table
will be regarded in the scope only during the transfer of institutions data of previous
dates, and this situation will be controlled by of P_HRKDRM parameter of the related
ETL procedure.
d. The data transfer for FACT_KURUMLAR table will be also due to processing date. The
all capacity data about the institutions which has been already recorded into
ST_KURUMLAR table will be transferred. The selection of the related record in
ST_KURUMLAR table will be accomplished by querying the most recent tuple which is
before the processing date having the same institution and institution type codes.
e. The bed capacities of Tourism and Hotel Business Applications Hotels will be provided
from the bed capacities of Building Usage Areas data.
f.
The capacities of school pensions will be taken from the definition table of institutions.
The pension capacities of Public Institutions can be derived on a gender basis, but
while the Private Institutions definition table lacks of this discrimination, only the total
capacity for them can be provided.
g. Institution Code and Institution Name will be returned together as a result of queries
when hierarchical columns are used.
h. More than one building may be within one institution and attributes of each building
such as ownership or heating status may differ from one building to another.
Originating from this situation, the total numbers derived from building data can be
different from the total number of institutions. For example, if an institution has
buildings that have different ownership status, the institution will be counted in each
category of ownership, and the total number according to ownership types will be
different from the total number of institutions.
i.
The institution records which have 300,301,302 and 305 values in "Institution Type"
attribute will not be reflected into the Statistics, since these attributes are only used for
the students applying for examinations. The data about these types will not be
transferred to either ST_KURUMLAR not FACT_KURUMLAR tables.
1.5. ETL CONTRAINTS OF FORMAL EDUCATION STUDENT DATA
1.5.1. PRIMARY SCHOOL EDUCATION LEVEL OF ACTIVE&PASSIVE STUDENTS (INCLUDES ALSO PREPRIMARY)
A. Source Tables:
and scopes of the data located in this area. The all source tables are under the OKULSIS
schema.
BI_ILK_OGRENCI_BILGILERI: Active students data of active semester in primary education
level with school, school type, semestre, class, class_level, division, gender, birth year and
nationality are taken in this source table.
BI_ILK_OGRENCI_PASIF: Passive students data of active semester in primary education
level with school, school type, semestre, class, class_level, division, gender, birth year,
nationality, reason of passiveness (Parent Decision, Death, Go Abroad etc.) are taken in this
source table.
BI_ILK_OGRENCI_GECMIS_DURUM: All students data of passive semesters in primary
education level of with school, school type, semestre, class, class_level, division, gender, birth
year, nationality and status (Active, Graduate, Death etc.) are taken in this source table.
BI_ILK_SINIF_TEKRAR: The data of students repeating a grade level at passive semesters
end in primary education level with school, school type, semestre, class, class_level, division,
gender, birth year, nationality, pass-fail status (Passed, Passed by Teachers Council’s
Decision (Ş.Ö.K.K), Made-Up Student, Repeater) are taken in this source table.
BI_ILK_AKTIF_SINIFTA_KALAN: All students data of active semester in primary education
level with school, school type, semestre, class, class_level, division, gender, birth year,
nationality and pass-fail status (Passed, Passed by Teachers Council’s Decision (Ş.Ö.K.K),
Repeater) are taken in this source table. No extra table will be added for different passive
semesters. All passive semesters data will be included in this table..
B. Target Tables:
The ETL process for the Primary Education application uses the source tables enlisted above
and inserts the data into the target tables after making appropriate transformations. The target
below.
FACT_IO_OGRYIL_BASI_BILGILERI: Within the scope of primary education, active students
data at the beginning of education year with semester, school, school type, class, class level,
division, birth year, age, gender, nationality, ISCED level, student status (Registered,
Repeater, New), pass status (Passed, Passed by Teachers Council’s Decision), nursery class
educated are transferred to this target table by using the source tables
BI_ILK_OGRENCI_BILGILERI, BI_ILK_AKTIF_SINIFTA_KALAN. This table does not contain
the information about graduation and pass-fail status because this information is obtained only
at the end of education year.
FIGURE 12Table Description of FACT_IO_OGRYIL_BASI_BILGILERI
FACT_IO_OGRYIL_SONU_BILGILERI: Within the scope of primary education, active students
data at the end of education year of passive semesters with semester, school, school type,
claas, class level, division, birth year, age, gender, nationality, ISCED level, student status
(Registered, Repeater, New, Graduate), pass status (Passed, Passed by Teachers Council’s
Decision), pass status at the end of semester (Passed, Passed with Teachers Council,
Repeater), nursery class educated are transferred to this target table by using the source
tables BI_ILK_SINIF_TEKRAR, BI_ILK_OGRENCI_GECMIS_DURUM. This table will be
updated for only passive semesters and will not contain active semester data.
FIGURE 13Table Description of FACT_IO_OGRYIL_SONU_BILGILERI
FACT_IO_OGRENCI_PASIF: Within the scope of primary education, passive students data
with school, school type, ISCED level, semester, claas, class level, division, gender, birth year,
age, nationality, reason of passiveness are transferred to this target table by using the source
tables BI_ILK_OGRENCI_PASIF and BI_ILK_OGRENCI_GECMIS_DURUM.
FIGURE 14Table Description of FACT_IO_OGRENCI_PASIF
C. ETL Constraints:
a. Related to processing date, the data will be transferred for all semesters. For acquiring
the number of students at a specific semester, a reference date and semester code are
needed. In this way, the transactions in a specific semester are observed monthly.
b. For each transport, the data of all semesters is transferred, so passive semester data
could be observed and the difference between annual data and database is revealed.
c. For the source tables BI_ILK_OGRENCI_BILGILERI, BI_ILK_OGRENCI_PASIF,
BI_ILK_OGRENCI_GECMIS_DURUM, BI_ILK_SINIF_TEKRAR and
BI_ILK_AKTIF_SINIFTA_KALAN the column ‘Processing Date’ data must be the
same.
d. The active students data of active semester (BI_ILK_OGRENCI_BILGILERI,
BI_ILK_AKTIF_SINIFTA_KALAN) will be transfered to the target table
(FACT_IO_OGRYIL_BASI_BILGILERI). This table contains data related to 30th
semester and later.
e. The passive students data of active semester (BI_ILK_OGRENCI_PASIF,
BI_ILK_OGRENCI_GECMIS_DURUM) will be transfered to the target table
(FACT_IO_OGRENCI_PASIF).
f.
By using the source table BI_ILK_OGRENCI_GECMIS_DURUM, the data related to
past semesters is transferred to the target table FACT_IO_OGRYIL_SONU_BILGILERI
for active students, to the target table FACT_IO_OGRENCI_PASIF for passive
students. The number of graduates related to the semesters will be obtained from
status column of these tables. At the end of the education year, also the number of
registered, repeater from previous semester, passed from previous semester, passed
by teacher council’s decision from previous semester, graduate, passed to next
semester, passed by teacher council’s decision from next semester, repeater to next
semester coluld be queried from these tables.
g. At the end of education year, after updating the source table
BI_ILK_OGRENCI_GECMIS_DURUM by using the status column, related measuring
column in FACT_IO_OGRYIL_SONU_BILGILERI will be calculated.
h. The Experts of IT Group Presidency notifies that the status data does not exist before
25th semester. Also for the semesters (22, 23, 24) student status (Active or Passive)
cannot be reached. So in the meetings with experts, it was decided that data of 25th
semester and later will be taken.
i.
The students of nursery class and first grade will be considered as new records. In
primary school the experts notify that there is no exception about this matter.
j.
On the basis of data hierarchy, the number of students in nursery class will be added to
the
source
tables
BI_ILK_OGRENCI_BILGILERI
and
BI_ILK_OGRENCI_GECMIS_DURUM as a column. So this data will be used in the
target
tables
FACT_IO_OGRYIL_BASI_BILGILERI
and
FACT_IO_OGRYIL_SONU_BILGILERI.
k. For the calculation of age both birth year and birth month was used. For pre-primary
students ages, 36-48 months are considered as 3 year, 49-60 months are considered
as 4 year and 61-72 months considered as 5 year.
l.
For accessing pass-fail information related to previous semester of the registered
active students, the source table BI_ILK_AKTIF_SINIFTA_KALAN will be used. By this
transport, the status of “Decision to Repeat the Class” as “TEKRAR_SAYI”, “Passed by
Teacher Council’s Decision” as “SOKK_GECMIS_SAYI”, “Passed”, “Make-Up” and
Null as “DOGRUDAN_GECMIS_SAYI” columns will be filled with the data of active
semester.
m. At the end of education year, to update pass-fail status of registered active students the
source table BI_ILK_SINIF_TEKRAR will be used. The number of students at the
status Passed, Passed by Teacher Council’s Decision, Repeater will be transferred to
the target table FACT_IO_OGRYIL_SONU_BILGILERI from the source table.
1.5.2. UPPER SECONDARY SCHOOL EDUCATION LEVEL OF ACTIVE&PASSIVE STUDENTS
(INCLUDES ALSO PRE-PRIMARY)
A. Source Tables:
schema.
BI_LISE_OGRENCI_BILGILERI: Active students data of active semester in upper secondary
education level with school, school type, semestre, class, class_level, division, gender, birth
year and nationality are taken in this source table.
BI_LISE_OGRENCI_PASIF: Passive students data of active semester in upper secondary
year, nationality, reason of passiveness (Parent Decision, Death, Go Abroad etc.) are taken in
this source table.
BI_LISE_OGRENCI_GECMIS_DURUM: All students data of passive semesters in upper
secondary education level of with school, school type, semestre, class, class_level, division,
gender, birth year, nationality and status (Active, Graduate, Death etc.) are taken in this
source table.
BI_LISE_SINIF_TEKRAR: The data of students repeating a grade level at passive semesters
end in upper secondary education level with school, school type, semestre, class, class_level,
division, gender, birth year, nationality, pass-fail status (Passed, Repeater, etc.) are taken in
this source table.
BI_LISE_AKTIF_SINIFTA_KALAN: All students data of active semester in upper secondary
year, nationality and pass-fail status (Passed, Repeater, Passed From the Average, etc.) are
taken in this source table. No extra table will be added for different passive semesters. All
passive semesters data will be included in this table.
BI_LISE_AKTIF_OH_KULLANMAYAN: Students data who didn't use his education right in the
previous period, but attend school in the active education period in upper secondary education
are taken in this table. The student record in this table will be considered ad 're-entered
students' for UOE.
B. Target Tables:
The ETL process for the Upper Secondary Education application uses the source tables
enlisted above and inserts the data into the target tables after making appropriate
transformations. The target tables that are determined by TAT and confirmed by IT Group
Presidency experts are defined below.
FACT_IO_OGRYIL_BASI_BILGILERI: Within the scope of upper secondary education, active
students data at the beginning of education year with semester, school, school type, class,
class level, division, birth year, age, gender, nationality, ISCED level, student status
(Registered, Repeater, New), pass status (Passed,Repeater etc.), nursery class educated are
transferred to this target table by using the source tables BI_LISE_OGRENCI_BILGILERI,
BI_LISE_AKTIF_SINIFTA_KALAN. Enrolled students, new-entrants, re-entrants and continous
students can be queried in this table. This table does not contain the information about
graduation and pass-fail status because this information is obtained only at the end of
education year.
FIGURE 15Table Description of FACT_IO_OGRYIL_BASI_BILGILERI
FACT_IO_OGRYIL_SONU_BILGILERI: Within the scope of upper secondary education,
active students data at the end of education year of passive semesters with semester, school,
school type, claas, class level, division, birth year, age, gender, nationality, ISCED level,
student status (Registered, Repeater, New, Graduate), pass status (Passed, Repeater etc.),
pass status at the end of semester (Passed, Passed From Average, Repeater etc), nursery
class educated are transferred to this target table by using the source tables
BI_LISE_SINIF_TEKRAR, BI_LISE_OGRENCI_GECMIS_DURUM. This table will be updated
for only passive semesters and will not contain active semester data, as the data can be
available at the end of the semester.
FIGURE 16Table Description of FACT_IO_OGRYIL_SONU_BILGILERI
FACT_IO_OGRENCI_PASIF: Within the scope of upper secondary education, passive
students data with school, school type, ISCED level, semester, claas, class level, division,
gender, birth year, age, nationality, reason of passiveness are transferred to this target table
by
using
the
source
tables
BI_LISE_OGRENCI_PASIF
and
BI_LISE_OGRENCI_GECMIS_DURUM.
FIGURE 17Table Description of FACT_IO_OGRENCI_PASIF
C. ETL Constraints:
a. Related to processing date, the data will be transferred for all semesters. For acquiring
the number of students at a specific semester, a reference date and semester code are
needed. In this way, the transactions in a specific semester are observed monthly.
b. For each transport, the data of all semesters is transferred, so passive semester data
could be observed and the difference between annual data and database is revealed.
c. For the source tables BI_LISE_OGRENCI_BILGILERI, BI_ LISE _OGRENCI_PASIF,
BI_ LISE _OGRENCI_GECMIS_DURUM, BI_ LISE _SINIF_TEKRAR, BI_
LISE_AKTIF_SINIFTA_KALAN and BI_ LISE _OH_KULLANMAYAN, the column
‘Processing Date’ data must be the same.
d. The active students data of active semester (BI_ LISE _OGRENCI_BILGILERI, BI_
LISE _AKTIF_SINIFTA_KALAN) will be transfered to the target table
(FACT_IO_OGRYIL_BASI_BILGILERI). This table contains data related to 30th
semester and later.
e. The passive students data of active semester (BI_LISE _OGRENCI_PASIF, BI_ LISE
_OGRENCI_GECMIS_DURUM) will be transfered to the target table
(FACT_IO_OGRENCI_PASIF).
f.
By using the source table BI_ LISE _OGRENCI_GECMIS_DURUM, the data related to
past semesters is transferred to the target table FACT_IO_OGRYIL_SONU_BILGILERI
for active students, to the target table FACT_IO_OGRENCI_PASIF for passive
students. The number of graduates related to the semesters will be obtained from
status column of these tables. At the end of the education year, also the number of
registered, repeater from previous semester, passed from previous semester, passed
by teacher council’s decision from previous semester, graduate, passed to next
semester, passed by teacher council’s decision from next semester, repeater to next
semester coluld be queried from these tables.
g. At the end of education year, after updating the source table BI_ LISE
_OGRENCI_GECMIS_DURUM by using the status column, related measuring column
in FACT_IO_OGRYIL_SONU_BILGILERI will be calculated.
h. The Experts of IT Group Presidency notifies that the status data does not exist before
25th semester. Also for the semesters (22, 23, 24) student status (Active or Passive)
cannot be reached. So in the meetings with experts, it was decided that data of 25th
semester and later will be taken.
i.
The students of nursery class, first grade and preparation grade will be considered as
new records.
j.
On the basis of data hierarchy, the number of students who was attend a nursery class
added
to
the
source
tables
BI_LISE_OGRENCI_BILGILERI
and
BI_LISE_OGRENCI_GECMIS_DURUM as a column. So this data will be used in the
target
tables
FACT_IO_OGRYIL_BASI_BILGILERI
and
FACT_IO_OGRYIL_SONU_BILGILERI.
k. For the calculation of age both birth year and birth month was used. For pre-primary
students ages, 36-48 months are considered as 3 year, 49-60 months are considered
as 4 year and 61-72 months considered as 5 year.
l.
For the number of new-entrants;
i. Enrolled students in prep classes except repeaters
ii. Enrolled students in first grade except repeaters
was calculated as new-entrants.
m. For the re-entrants, as it was stated in UOE manual, students who gave up his
education at least 1 year and return back school have to be taken as re-entrant. From
e-school system, the BI_LISE_AKTIF_OH_KULLANMAYAN table was used for the
calculation of re-entrants.
n. For accessing pass-fail information related to previous semester of the registered
active students, the source table BI_LISE_AKTIF_SINIFTA_KALAN will be used. By
this transport, the status of “Decision to Repeat the Class” as “TEKRAR_SAYI”,
“Passed by Average” as “ORTALAMA_ILE_GECMIS_SAYI”, “Passed”, “Make-Up” and
Null as “DOGRUDAN_GECMIS_SAYI” columns will be filled with the data of active
semester.
o. At the end of education year, to update pass-fail status of registered active students the
source table BI_LISE_SINIF_TEKRAR will be used. The number of students at the
status Passed, Passed by Average, Repeater will be transferred to the target table
FACT_IO_OGRYIL_SONU_BILGILERI from the source table.
1.6. ETL CONTRAINTS OF DISABLED STUDENTS
A. Source Tables:
BI_ILK_OZUR_HIZMET: Disabled students data in primary education level with school, school
type, class, division, birth year, gender, nationality, disabled group and suggested service
group attributes are taken in this source table.
B. Target Tables:
FACT_IO_ENGELLI_OGR: By extacting data from the source table ' BI_ILK_OZUR_HIZMET',
number of unique disabled students and total disabled students with disable type can be
aggregated in this target table with age and ISCED additional attributes. A disabled student
can have more than one disable type, by querying this target table end user can reach total
student number in disable types and also unique disabled students number with suggested
service groupes.
FIGURE 18 Table Description of FACT_IO_ENGELLI_OGR
C. ETL Constraints:
a. The data transform procudures have to be run with a reference date and semester.
b. For disabled students content, a student have more than 1 disable group. For each
disable group the student have to be count in the Statistics. A student have to be count
twice, if this student have two different disable. On the other hand, queries without
disbled group have to give unique student number.
c. For inclusion student numbers, disabled students have to be queried by suggested
service groups.
1.7. ETL CONTRAINTS OF OPEN PRIMARY SCHOOL STUDENTS
A. Source Tables:
AIO_STRATEJI_ISTATISTIK : Open Primary School students data have to be taken from this
source table with referance date, education year like '2009-2010 Öğrenim Yılı', gender, birth
year, nationality, province and district of examination center, domestic/foreign, foreign country
attributes. This source table covers active students in one of the semester in the education
year. If a student active in one the semester in the education year, that student data have to
be put into this table.
B. Target Tables:
FACT_AIO_OGRENCI_YENI : For open primary school student data, this target table have to
be used with education year , age, gender, ISCED level, nationality, province and district of
examination center, domestic/foreign, foreign country attributes. The number of open primary
school students should be queried by this table. Enrolled, new-entered and graduate students
data was calculated in this table for the education year. This table only covers active students
FIGURE 19 Table Description of FACT_AIO_OGRENCI_YENI
C. ETL Constraints:
a.
The data transform procudures have to be run with a reference date and education
year.
b.
Open primary school have at least 3 semesters within an education year. The source
table have to contain yearly based active student data.
c.
Transformation have to be done after clarifying students status in examinations at the
end of the education year.
1.8. ETL CONTRAINTS OF OPEN HIGH SCHOOL STUDENTS
A. Source Tables:
BI_AOL_STRATEJI_ISTATISTIK : Open High School students data have to be taken from this
source table with referance date, education year, gender, birth year, nationality, province and
district of examination center, domestic/foreign, foreign country, school type (General Open
Lise, Vocational Open Lise) attributes. This source table covers active students in one of the
semester in the education year. If a student active in one the semester in the education year,
that student data have to be put into this table.
B. Target Tables:
FACT_AOL_OGRENCI_YENI : For open high school student data, this target table have to be
used with education year, age, gender, ISCED level, nationality, province and district of
examination center, domestic/foreign, foreign country attributes. The number of open high
school students should be queried by this table. Enrolled, new-entered, re-entrants and
graduate students data was calculated in this table for the education year. This table only
covers active students
FIGURE 20 Table Description of FACT_AOL_OGRENCI_YENI
C. ETL Constraints:
a.
The data transform procudures have to be run with a reference date and education
year.
b.
Open high school have at least 3 semesters within an education year. The source table
have to contain yearly based active student data.
c.
Transformation have to be done after clarifying students status in examinations at the
end of the education year.
d.
School type column covers AOL value for general open high school, MAOL value for
vocational open high school and IHL value for open religion high school..
e.
For the 2. programme of re-entrants, new-entrants of Open High School system whose
graduated from any other upper secondary institution before have to be considered as
re-entrants.
f.
For the second time gradute students,source table has a column named
'IKINCI_KERE_MEZUN_SAYISI' which covers number of graduates of re-entrant
students.
1.9. ETL CONTRAINTS OF SUMMER SCHOOL PRE-PRIMARY STUDENTS
A. Source Tables:
DK_ANAOKULU : Number of schools, number of classrooms, number of boys in age 3,
number of girls in age 3, number of boys in age 4, number of girls in age 4, number of boys in
age 5, number of girls in age 5 measures are hold into this source table for summer preprimary schools with district administration level of MoNE.
B. Target Tables:
FACT_DIS_KURUM_OGR_OGRETMEN: This target table have to be used both for summer
pre-primary school students, mobile pre-primary students, other institutions pre-primary
students and SHCEK institutions pre-primary students. This table should be queried for
summer pre-primary schools with school type attribute value 2.
FIGURE 21 Table Description of FACT_DIS_KURUM_OGR_OGRETMEN
C. ETL Constraints:
a. Data have to put into target table with school type column value 2.
b. The rows which "d_ao_turu kolonu" attribute of " DK_ANAOKULU "source table have
value '0' have to be taken as summer pre-primary students.
c. The data have to be taken from the source table in province and district administrative
levels.
d. There isn't any source columns for number of divisions and teachers in the source
table. So, the relevant columns in the target rows have value '0'.
1.10. ETL CONTRAINTS OF MOBILE PRE-PRIMARY STUDENTS
A. Source Tables:
DK_ANAOKULU : Number of schools, number of classrooms, number of boys in age 3,
number of girls in age 3, number of boys in age 4, number of girls in age 4, number of boys in
age 5, number of girls in age 5 measures are hold into this source table for mobile pre-primary
schools with district administration level of MoNE.
B. Target Tables:
C. ETL Constraints:
b. The rows which "d_ao_turu kolonu" attribute of " DK_ANAOKULU "source table have
value '1' have to be taken as summer pre-primary students.
levels.
1.11. ETL CONTRAINTS OF OTHER INSTITUTIONS PRE-PRIMARY STUDENTS
A. Source Tables:
DK_ILCE_BAGIMSIZ_KURUMLAR : Number of schools, number of classrooms, number of
female teachers, number of male teachers, number of boys in age 3, number of girls in age 3,
number of boys in age 4, number of girls in age 4, number of boys in age 5, number of girls in
age 5 measures are hold into this source table for pre-primary education of other public
institutions with district administration level of MoNE.
B. Target Tables:
C. ETL Constraints:
a. The other institutions pre-primary students data have to be put into source table with in
accordance to law number 657 , 191. clause.
b. Data have to put into target table with school type column value 1.
levels.
d. There isn't any source columns for number of divisions and teachers in the source
table. So, the relevant columns in the target rows have value '0'.
1.12. ETL CONTRAINTS OF SHCEK STUDENTS
A. Source Tables:
The data for number of preprimary students of SHCEK institutions was taken from Excel files
which was provided by SDP.
B. Target Tables:
SHCEK institutions pre-primary schools with school type attribute value 4.
C. ETL Constraints:
b. The data under Excel worksheets are inserted into 'T_GECICI_SHCEK_BILGI' tables
before data transformation first. By using 'GECICI_SHCEK_ILCEMEM_EKLE' function
under PKG_ETL_KURUM package, the institution codes (district administrative offices)
was tried to identify. For some row, manually matching was done for clarifying
institution code.
c. Some of the district names couldn't find in the provinces, so those records couldn't
transfered .
d. After the manuel data transformation of SHCEK data, the T_ GECICI_SHCEK_BILGI
table should be truncated.
e. SHCEK students data considered as 'Private Institution' for UOE.
1.13. ETL CONTRAINTS OF SCHOOLARSHIP STUDENTS
A. Source Tables:
BI_AKTIF_BURS_OGR_BILGILERI: The data about the active scholar students are recorded
in this table by means of the four semesters in the education year.
BI_BURS_MIKTAR : The scholarship rates for each semester are recorded in this table.
BI_BURSU_IPTAL_OGR_BILGILERI : The data of students whose scholarships are cancelled
by means of semesters and reasons of cancellation is stored in this table.
BI_BURS_SINAV_ONAY_OGR: The data about the students which passed the scholarship
examination is recorded in this table.
B. Target Tables:
The ETL process for the application uses the source tables enlisted above and inserts the data
into the target tables after making approriate transformations. The target tables that are
determined by TAT and confirmed by IT Group Presidency experts are defined below.
FACT_AKTIF_BURS_OGR_BILGILERI: The data about the active scholar students in formal
education due to the scholarship semesters is stored in this table. The table can be used for
querying the active scholar students by means of semester, institution, institution type, class,
class level, branch, date of born, gender, ISCED level, nationality, quota type, scholarship
acceptance type and scholarship acceptance date attributes.
FIGURE 22 Table Description of FACT_AKTIF_BURS_OGR_BILGILERI
FACT_BURS_MIKTAR : Scholarship Indicators, Officer Payroll Coefficients and Scholarship
Rates can be derived from this table due to scholarship semesters.
FIGURE 23 Table Description of FATCT_BURS_MIKTAR
FACT_BURSU_IPTAL_OGR_BILGILERI: The data of students whose scholarships are
cancelled by means of scholarship semesters and reasons of cancellation is stored in this
table. The table can be used for querying the cancelled scholar students by means of
semester, institution, institution type, class, class level, branch, date of born, gender,
nationality, quota type, and scholarship cancellation type attributes.
FIGURE 24 Table Description of FACT_BURSU_IPTAL_OGR_BILGILERI
FACT_BURS_SINAV_ONAY_OGR: The acceptance data about the students which passed
the scholarship examination due to the e-school semester information is recorded in this
table. The table can be used for querying the students whose scholarship exams are approved
by means of semester, institution, institution type, class, class level, branch, date of born,
gender, nationality, quota type and the acceptance situation attributes.
FIGURE 25 Table Description of FACT_BURS_SINAV_ONAY_OGR
C. ETL Constraints:
a. The transfer of Scholarship Students data will contain the all semesters located in the
staging area and will be labeled with the processing date. In order to reach any data
set, the declaration of the processing date and the semester will be sufficient and the
transactions in a specific semester for each date can be observed.
b. BI_AKTIF_BURSLU_OGRENCI and BI_BURS_MIKTAR should contain the same
processing date and semester data. In the contrary, the transformation and
construction of FACT_AKTIF_BURS_OGR_BILGILERI target table cannot be
performed.
c. FACT_BURS_MIKTAR will be constructed by using the data that will be obtained from
Scholarships Department while there is no data about the Officer Payroll Coefficient
and Scholarship Indicator in the current e-scholarship system.
1.14. ETL CONTRAINTS OF BOARDING STUDENTS
A. Source Tables:
BI_YATILILIK_DURUM_OGR : The data about the boarding students which pay fee or not, is
stored in this table due to the active semesters in e-school module.
B. Target Tables:
FACT_YATILILIK_DURUM_OGR: The data about the boarding students which pay fee or not,
is stored in this table due to the active semesters in e-school module. The table can be used
for querying the active boarding students by means of semester, institution, institution type,
class, class level, branch, date of born, gender, ISCED level, nationality, payment situation
(Paralı/Parasız Yatılı), used institution and use type (Global exams, local exams etc)
attributes.
FIGURE 26 Table Description of FACT_YATILILIK_DURUM_OGR
C. ETL Constraints:
a. The transfer of Boarding Students data will contain the all semesters located in the
staging area and will be labeled with the processing date. In order to reach any data
set, the declaration of the processing date and the semester will be sufficient and the
transactions in a specific semester for each date can be observed.
1.15. ETL CONTRAINTS OF PRIVATE DORMITORIES
A. Source Tables:
BI_OZEL_YURT_KAPASITE: The data about the private dormitories in e-dormitory module is
stored in this table. The education level (Secondary/High Education), ownership type (Private,
Foundation, Association), Gender, Place of Residence, Payment Type, Date of Opening, Date
of Closure, Total Student Capacity, Used and Empty Student Capacity are the main attributes
for this table. The source table was taken from the "ilsis" schema. The province and district
codes of this system is different from other modules, so for NUTS hierachy and provincedistrict information ST_ILCE from ILSIS schema source look-up tables are used.
B. Target Tables:
FACT_OZEL_YURT_KAPASITE: The capacity data about the private dormitories that supply
service for secondary and high education levels is stored in this table. The table can be
queried by using Province/District, Place of Residence, Education Level, Ownership Type,
Gender, Payment Type, Current Situation (Open/Closed/Temporarily Closed), Date of
Opening, Date of Closure and Reason of Closure attributes.
FIGURE 27 Table Description of FACT_OZEL_YURT_KAPASITE
C. ETL Constraints:
a. The data transfer for the private dormitories will be on a monthly basis and will be
accomplished in the last date of each month.
1.16. ETL CONTRAINTS OF FOREIGN LANGUAGE FOR FORMAL EDUCATION
A. Source Tables:
schema.
BI_ILK_YABANCIDIL: The number of primary and lower-secondary students by level of
education, number of foreign languages studied are located in this table.
The attributes that the source table contains;
a. Reference Date
b. Institution Number
c. Institution Type
d. Period
e. Class
f. Class Level
g. Desk
h. Gender
i.
Birth Year + Birth Month
j.
Language Code
k. Language Definition
l.
Nationality
m. Other Foreign Language Studied (English)
n. Other Foreign Language Studied (French)
o. Other Foreign Language Studied (German)
p. Number of Students
BI_LISE_YABANCIDIL: The number of upper secondary students by level of education,
number of foreign languages studied are located in this table.
a. Reference Date
c. Institution Type
d. Period
e. Class
f. Class Level
g. Desk
h. Gender
i.
Birth Year + Birth Month
j.
Language Code
k. Language Definition
l.
Nationality
m. Optional Foreign Language Studied
n. Secondary Foreign Language Studied
o. Secondary Optional Foreign Language Studied
p. Number of Students
B. Target Tables:
The ETL process for Foreign Languages application uses the source tables enlisted above
below:
FACT_YABANCI_DIL: The number of students is stored in this table after assigning their
ISCED levels due to their institution types. This table will be feed from both source tables.
FIGURE 28 Table Description of FACT_YABANCI_DIL
FACT_YABANCI_DIL_UOE: Number of students by number of foreign languages studied,
ISCED levels and institutions are stored in this table which will be reference to UOE reports.
FIGURE 29 Table Description of FACT_YABANCI_DIL_UOE
C. ETL Constraints:
a. For the reference date in the target tables, source tables reference date will be used.
b. For each foreign language except for primary foreign language, a new record will be
created and the student will be count in each record (ENRLLANG1).
c. When it comes to calculating the number of foreign languages being studied by each
student, the unique student number will be the basis (ENRLLANG2).
1.17. ETL CONTRAINTS OF STAFF DATA
A. Source Tables:
schema.
BI_KAMU_PERSONEL_BILGILERI: The number of active personnel in public institutions are
located in this table.
q. Reference Date
r. Institution Number
s. Institution Type
t. Employment Type (Permanent, Contractual, Temporary etc)
u. Staff Title
v. Job Title
w. Branch/Speciality
x. Service Class
y. Birth Year + Birth Month
z. Gender
aa. Last Education Level
bb. Asigning Types
cc. Labour Region
dd. Labour Area
ee. Number of Active Personnel
BI_ÖZEL_PERSONEL_BILGILERI: The number of active personnel in private institutions are
a. Reference Date
c. Institution Type
d. Employment Type (Permanent, Lesson Based etc)
e. Job Title
f. Branch/Speciality
g. Birth Year + Birth Month
h. Gender
i.
Last Education Level
j.
Number of Active Personnel
B. Target Tables:
inserts the data into the target tables after making appropriate transformations. The target
below..
FACT_PERSONEL_BILGILERI: Each staff in both public and private institutions are stored in
this target table. Personel category and ISCED levels will be identified during the data
processing phase and transformed data will be put in this table. Some of the categories ISCED
levels can not be identified during populating this table, those records will be transformed in
UOE tables.
FIGURE 30 Table Description of FACT_PERSONEL_BILGILERI TABLE
FACT_PERSONEL_UOE : Number of public and private institutions saff data will be
transformed into ISCED levels and categories for Ad-Hoc-Module-Pers UOE data table. The
transformation results will be stored in this table. SHCEK, other pre-primary institutions and
mobile schools teacher data also put in this table.
FIGURE 31 Table Description of FACT_PERSONEL_UOE
FACT_PERS_UOE12 : Number of public and private institutions teachers an school level
managers data will be transformed into this target table containing age and sex information
with ISCED levels. SHCEK, other pre-primary institutions and mobile schools teacher data
also put in this table.
FIGURE 32 Table Description of FACT_PERS_UOE12
FACT_PERS_ENRL : Number of students in schools whose teacher numbers are populated in
FACT_PERS_UOE12 table will be stored in this table. Open primary school and open high
school students data won't be stoıred in this table.
FIGURE 33 Table Description of FACT_PERS_ENRL
C. ETL Constraints:
Both public and private staff data have the same reference dates. Otherwise, all staff
data can not be combined in the BI system.
b. All staff for public and private sector will be put into UOE tables as full time.
c. The staff in independent pre-primary school (teacher + manager) will be considered as
ISCED 0 level.
d. If the branch of teacher in primary schools is 4439- pre-primary school teacher than the
ISCED level will be registered as ISCED 0.
e. If the branch of teacher in secondary high schools is 4439- pre-primary school teacher
than the ISCED level will be registered as ISCED 0.
f.
The branch of teacher in primary schools:
2403- School Teaching
2632- School Teaching for Children with Mental Disabilities
2647- School Teaching for the Visually Impaired
2651- School Teaching for Hearing Impaired
Will be registered in ISCED level 1.
g. Teachers in primary school with other branches will be registered in the level of ISCED
2.
h. Staff having the branch of counselor will be involved in the group of “Pedagogical
Support Staff”.
i. The counselor will not be included in UOE as a teacher .
j.
k.
l.
m.
n.
o.
p.
q.
r.
s.
All qualified instructor and qualified instructor staff will be considered as teachers but
only if the institution type is pre-school, staff having concerned title will be considered as
teacher aides.
The branch of manager will be used for the ISCED level of school level management
staff in primary schools. If manager has branch of pre-primaryschool, ISCED 0 will
appoint; if it has branch of classroom teacher, ISCED 1 will appoint and for the other
branches ISCED 2 will appoint.
The ISCED level of school type for the secondary education, will be used for both
teachers and managers.
The public staff will be considered in the institution that the permanent job title stated in.
In private training institutions, general director and deputy general director will be
considered in Higher Level Managers section.
The teacher within SHCEK will be considered as attendant in “Private Training
Institution” and those will be viewed in “Private” part in UOE tables.
The number of students in Pers_ENRL UOE tables will be involved in the number of
students in the schools having staff data. The number of open primary school students
and open high school students will not be shown in this table. In a similar way, staff in
the secondary schools which have sub-type is being seen within main type. For this
reason, the number of students in only main type will be considered for these types of
school. this situation was discussed and finalized in this way in the meeting dated
07.02.2012.
Although a teacher is tenured, the situation of giving lessons at the same time in other
private institution is examined, registration at the rate of 0.3% was determined. The
decision of the rate acquired might be neglected in statics, was taken in the meeting
dated in 07.02.2012. Concerned staff registration will be considered in both public school
and private school.
It is determined the number of teachers working in more than one institution at the same
time is 0.1% in the examinations. The decision of the rate acquired might be neglected in
statics was taken in meeting dated 07.02.2012. According to this decision, the staff
serving at the same time in more than one private school will be considered in each
school and he will be considered full time staff for each registration.
UOE transformations, of all staff working in institutions where ISCED definitions can’t be
performed in administrative organization having not students like evening arts school,
will be delivered proportionately according to ISCED division of the students within the
province on which the institution depends.
t.
According to number of students within Provincial and District level, proportional
transformations will be performed concerning ISCED transformation of staff in
administration and administrative staff within Provincial and District Directors of National
Education.
u. ISCED transformation of staff in administration and administrative staff within Ministry
will be performed with the proportional transformation according to number of students in
across Turkey.
v. Putting in the table of only the number of staff in charge in schools is stable in instruction
book for maintenance and operation staff. Therefore, maintenance and operation staff in
charged in administrative organizations won’t be added into UOE tables.
w. Putting in the table of only the number of staffs in charge in schools is stable in
instruction book for health and social services. Therefore, health and social services staff
in charged in administrative organizations won’t be added into UOE tables.
x. Age of staff is calculated basing on reference date during the transfer to first target table
(FACT_PERSONEL_BILGILERI). But the calculation base changes to “start date of
period”, when it comes to building UOE tables. Therefore diversion between “age group”
for each table is expected.
1.18. ETL CONTRAINTS OF FINANCE DATA
A. Source Tables:
schema. Firstly all tables under ilsisweb schema are transferred to Finance source tables in
MONESTAT schema. Data sources for Finance tables derived from Tefbis System Tables,
Tefbis Central Budget Tables and Tefbis Household Questionnaire Analysis Results.
ST_ISCED_FINANS: This source table will be used for matching ISCED levels with institution
type for data related to institutions from TEFBIS sub modules and for distribution of
expenditures by ISCED levels. It is constructed by using ST_ISCED table that is under
MONESTAT user in institution data warehouse server as source.
FIGURE 34 Table Description of ST_ISCED_FINANS
BI_TEFBIS_FINANS_GIDER: The amount of outcome for Education expenditures taken from
Tefbis sub modules are located in this table. Data are transferred from tables under the
ILSISWEB schema to MONESTAT stage tables with same name.
This source table contains education expenditures (outcome) by Analytical Budget System
(ABS) codes and financial year. The related fact tables, designed on the data warehouse, will
be constructed based on this table. MODUL_KODU field, should be filled by related
submodule short codes (“OAB”, “OKUL”, “PANS”, “MEM”, “OO”, “DOSE”).
In order to make discrimination for province/district management and grants, category code
has been added to the first design later.
ff. Institution Number
gg. Institution Type
hh. Reference Date
ii. Financial Year
jj. Tefbis Sub Module Code
kk. Tefbis Category Id
ll. Analytical Budget System Codes
i. Functional Codes (ABS_FONK1-2-3-4)
ii. Financial Code (ABS_FIN)
iii. Economical Codes (ABS_EKON1-2-3-4)
mm.
Amount of Outcome
FIGURE 35 Table Description of BI_TEFBIS_FINANS_GIDER
BI_TEFBIS_FINANS_GELIR: The amount of income for Education expenditures taken from
Tefbis sub modules are located in this table. Data are transferred from tables under the
This source table contains education expenditures (income) by Analytical Budget System
(ABS) codes and financial year. The related fact tables, designed on the data warehouse, will
be constructed based on this table. MODUL_KODU field, should be filled by related
submodule short codes (“OAB”, “OKUL”, “PANS”, “MEM”, “OO”, “DOSE”).
In order to make discrimination for province/district management and grants, category code
has been added to the first design later.
a. Institution Number
b. Institution Type
c. Reference Date
d. Financial Year
e. Tefbis Sub Module Code
f. Tefbis Category Id
g. Analytical Budget System Codes
ii. Financial Code (ABS_FIN)
iii. Economical Codes (ABS_EKON1-2-3-4)
h. Amount of Income
FIGURE 36 Table Description of BI_TEFBIS_FINANS_GELIR
BI_EBUTCE: The amount of Education expenditures taken from Central Budget tables under
Tefbis system database are located in this table. Data are transferred from tables under the
This table, whose source is TEFBİS-Ebudget summary tables, consist of central management
expenditures and all analytical budget system (ABS) codes. Data corresponding to financial
year and ABS codes are extracted from this table and processed. Reference date will be
written as record transfer date. Data record year implies the financial year corresponding to
data. The related fact tables, designed on the data warehouse, will be created based on this
table.
a. Financial Year
b. Reference Date
c. Analytical Budget System Codes
i. Institutional Codes (KKOD1-2-3-4)
ii. Financial Unit Code (KKOD5)
iii. Functional Codes (ABS_FONK1-2-3-4)
iv. Financial Code (ABS_FIN)
v. Economical Codes (ABS_EKON1-2-3-4)
d. Amount of Expenditure
e. Amount of Expenditure for Special Provincial Administration
FIGURE 37 Table Description of BI_EBUTCE
BI_BELEDIYE: The amount of Education expenditures (for Special Provincial Administration)
taken from tables under Tefbis system database are located in this table. Data are transferred
from tables under the ILSISWEB schema to MONESTAT stage tables with same name.
a. Financial Year
b. Reference Date
c. Special Provincial Administration/Municipality Information
d. Province Information
e. Type of Special Provincial Administration
f. Analytical Budget System Codes
ii. Economical Codes (ABS_EKON1-2-3-4)
g. Amount of Expenditure
h. Amount of Expenditure-Special Provincial Administration
FIGURE 38 Table Description of BI_BELEDIYE
BI_HANEHALKI_ANALIZ: This table was designed for Household Education Expenditures.
The results of “Household Expenditures Questionnaire” for both Public and Private Institiutions
are manually entered into this table. In a test meeting on 11st of May 2012, it has been decided
to create a data structure for entering the analysis results to database, to do calculations and
reports using this table by KEY3-Statistics Expert and project officers from Ministry of
Education. In the field of questionnaire type, there is a differentiation for public and private. It
has been also provided to enter the amount of expenditure by ISCED levels for each question
number.
a. Financial Year
b. Reference Date
c. Questionnaire Type (Public/Private)
d. Item Number
e. ISCED Levels
f. Amount of Expenditure
FIGURE 39 Table Description of BI_HANEHALKI_ANALIZ
BI_FINANS_TANIM: This table consists of finance categories with their descriptions for
Finance 1 and Finance 2 tables. It has been designed as a dimension table. It also contains
both the English and Turkish descriptions of finance categories.
ST_ISLEM_TARIHI_FINANS: This table contains the reference dates of the transformed
targets related to finance data source types. This table will be used as a dimension table in BI
system. There are 3 columns in the table;
ISLEM_TARIHI contains the reference date,
ISLEM_YILI contains the financial year,
TABLO_TURU contains the type of the transformed table.
TF1: represents FACT_TEFBIS_FINANS1
TF2: represents FACT_TEFBIS_FINANS2
TFO: represents FACT_TEFBIS_FINANS_OZEL
EB1: represents FACT_EBUTCE_FINANS1
EB2: represents FACT_ EBUTCE_FINANS2
EBO1: represents FACT_ EBUTCE_FINANS1_BELTAB
EBO2: represents FACT_ EBUTCE_FINANS2_BELTAB
HH1: represents FACT_ HANEHALKI_FINANS1_UOE
FIGURE 40 Table Description of ST_ISLEM_TARIHI_FINANS
ST_EBUTCE_IDARIBIRIM_TURU: This table is a lookup table for discriminating the data
(obtained from Central Budget tables) for province (district) national education directorate. This
table will be used as a dimension table in BI system.
FIGURE 41 Table Description of ST_EBUTCE_IDARIBIRIM_TURU
ST_HANEHALKI_ANKET_TIPLERI: It has been designed as a look-up table which contains
household questionnaire types and their descriptions. This table will be used as a dimension
table in BI system.
FIGURE 42 Table Description of ST_HANEHALKI_ANKET_TIPLERI
FINANS_TOPLAM_HESAP: It has been formed for finance categories which specify
summative fields in Finance 1 and Finance 2 tables. This calculation table is used to fill
FACT_FINANS main finance table.
FIGURE 43 Table Description of FINANS_TOPLAM_HESAP
B. Target Tables:
inserts the data into the target tables after making appropriate transformations. The target
below:
FACT_TEFBIS_FINANS1: This table is used for the discrimination of Finance categories in
Finance 1 table. Finance categories will be identified during the data processing phase and
transformed data will be put in this table. Also, it is used for existing analyses in BI system.
This fact table is filled by using BI_TEFBIS_FINANS_GIDER ve BI_TEFBIS_FINANS_GELIR
tables. The finance categories of data taken from TEFBIS system sub modules are determined
and written on this table. It has been designed by the thought of one expenditure could be
classified in more than one finance category.
FIGURE 44 Table Description of FACT_TEFBIS_FINANS1
FACT_EBUTCE_FINANS1: This table is used for the discrimination of Finance categories in
Finance 1 table. The Finance category of each record taken from Central Budget summary
tables under TEFBIS system is determined and written to this table. Also, it is used for existing
analyses in BI system. It has been designed by the thought of one expenditure could be
FIGURE 45 Table Description of FACT_EBUTCE_FINANS1
FACT_EBUTCE_FINANS1_BELTAB: This table is used for the discrimination of Finance
categories in Finance 1 table. The Finance category of each record taken from Special
Provincial Administration financial table under TEFBIS system is determined and written to this
table. Also, it is used for existing analyses in BI system. It has been designed by the thought of
one expenditure could be classified in more than one finance category.
FIGURE 46 Table Description of FACT_EBUTCE_FINANS1_BELTAB
FACT_TEFBIS_FINANS2: This table is used for the discrimination of Finance categories in
Finance 2 table. Finance categories will be identified during the data processing phase and
transformed data will be put in this table. Also, it is used for existing analyses in BI system.
This fact table is filled by using BI_TEFBIS_FINANS_GIDER ve BI_TEFBIS_FINANS_GELIR
tables. The finance categories of data taken from TEFBIS sistem sub modules are determined
and written on this table. It has been designed by the thought of one expenditure could be
FIGURE 47 Table Description of FACT_TEFBIS_FINANS2
FACT_TEFBIS_FINANS_OZEL: This table is used for the discrimination of Finance categories
in Finance 2 table for private institutions module in TEFBIS system. Finance categories will be
identified during the data processing phase and transformed data will be put in this table. Also,
it is used for existing analyses in BI system. It has been designed by the thought of one
expenditure could be classified in more than one finance category.
FIGURE 48 Table Description of FACT_TEFBIS_FINANS_OZEL
FACT_EBUTCE_FINANS2: This table is used for the discrimination of Finance categories in
Finance 2 table. The Finance category of each record taken from Central Budget summary
tables under TEFBIS system is determined and written to this table. Also, it is used for existing
analyses in BI system. It has been designed by the thought of one expenditure could be
FIGURE 49 Table Description of FACT_EBUTCE_FINANS2
FACT_EBUTCE_FINANS2_BELTAB: This table is used for the discrimination of Finance
categories in Finance 2 table. The Finance category of each record taken from Special
Provincial Administration financial table under TEFBIS system is determined and written to this
table. Also, it is used for existing analyses in BI system. It has been designed by the thought of
one expenditure could be classified in more than one finance category.
FIGURE 50 Table Description of FACT_EBUTCE_FINANS2_BELTAB
ISCED levels can not be identified during populating the tables above, those records
will be transformed in UOE tables below.
FACT_TEFBIS_FINANS1_UOE: This table is used for the discrimination of expenditures
according to ISCED levels. It is constructed after the determination of finance categories of
expenditures in FACT_TEFBIS_FINANS1 table. The field of source is a reference field that
has been added to make the discrimination of public schools/province-district national
education directorate/primary schools in the process of calculations (“IO”, “MEM”, “OZEL”
values imply different types of calculations)
FIGURE 51 Table Description of FACT_TEFBIS_FINANS1_UOE
FIGURE 52 Table Description of FACT_TEFBIS_FINANS2_UOE
FACT_EBUTCE_FINANS1_UOE: This table is used for the discrimination of expenditures
expenditures in FACT_EBUTCE_FINANS1 table. The field of source is a reference field that
has been added to make the discrimination of Special Provincial Administrations and Central
Budget data source in the process of calculations (“EBUTCE”, “BELTAB” values imply different
types of calculations)
FIGURE 53 Table Description of FACT_EBUTCE_FINANS1_UOE
FIGURE 54 Table Description of FACT_EBUTCE_FINANS2_UOE
FACT_HANEHALKI_FINANS1_UOE: The Finance 1 categories of BI_HANEHALKI_ANALIZ
table are determined in this table. The analysis results of household questionnaire will only be
used for Finance 1 table.
FIGURE 55 Table Description of FACT_HANEHALKI_FINANS1_UOE
FACT_FINANS: Data that mentioned in Finance 1 and Finance 2 UOE source tables, and
obtained from different data sources are combined in this table. This table is the main table of
Finance 1 and Finance 2 reports in BI system. Also, the calculation of summative finance
categories in ETL packages is added to this table as additional data. UOE_TANIMNO column
refer to general UOE parameter table in data warehouse (T_UOE_TANIM_TABLOSU). After
entering relevant reference date for those columns, relevant ETL packages for UOE
tarnsformation must be run by IT department experts.
FIGURE 56 Table Description of FACT_FINANS
C. ETL Constraints:
a. The required unique keys for all source tables constructed on TEFBIS database should
be created and the uniqueness of records should be checked in terms of data
consistency.
b. The data in BI_TEFBIS_FINANS_GIDER ve BI_TEFBIS_FINANS_GELIR tables will be
extracted by using Income/Outcome tables on TEFBIS submodules corresponding to
related ABS codes in addition to the corresponding sub module tables on Item f. While
the reference date refers to the date of data extraction to source table, data record year
shows the year of formal record data on TEFBIS for income/outcome corresponding to
each date in income/outcome tables.
c. It can be seen that the module data structure for schools with revolving funds on
TEFBIS system has been renewed later and data on DOSE module have not been
matched with ABS codes. So, these expenditures have not been used in 2011 OUE
tables. Ministry of Education project officers have been informed about this case.
Whenever possible to ABS code matching, this data could be extracted automatically.
d. TEFBIS modules, from which the required data in source tables will be extracted, are
given below:
a. TEFBIS School Council Module (Module code: OAB)
b. TEFBIS School Module (Module code: OKUL)
c. TEFBIS Private Schools Module (Table code: BI_TEFBIS_OZEL_GIDER)
d. TEFBIS Revolving Fund Module (Module code: DOSE)
e. TEFBIS pre-primary schools Module (Module code: OO)
f. TEFBIS National Education Directorate Modules (Province/District National
Education Directorate Modules) (Module code: MEM)
e. For the data taken from Tefbis sub modules, should be written to
BI_TEFBIS_FINANS_GIDER and BI_TEFBIS_FINANS_GELIR tables together with the
module code distinctions.
f.
It has been decided not to directly use questionnaire response tables on data structure
that is related to TEFBIS household application by both Statistics Office and project
officers. BI_HANEHALKI_ANALIZ table has been designed to enter analysis results
after the analysis of data on sample selected by Statistics experts. This table will be
filled manually using the results of analyses.
g. The distribution of expenditures related to finance categories in UOE tables by ISCED
levels has been planned as:
a. Institution data from TEFBIS system will be distributed proportionally to the
corresponding number of students by ISCED levels in each institution type. The
distribution could not be realized at the institutions for which ISCED levels
related to institution type could not determined. Also, ISCED distribution of
province/district national education directorate will be performed in terms of the
number of students in corresponding province.
b. Data from TEFBIS Cental Budget tables will be distributed proportionally to the
corresponding number of students by ISCED levels in Turkey.
c. Data from TEFBIS Central Budget Tables and that classified in personnel
salaries category on Finance 2 table have been planned to be distributed
proportionally to the number of personnel for whom ISCED levels are known.
d. Data from household questionnaire analysis results have been planned to be
distributed proportionally to the number of students for whom ISCED levels are
known.
h. It has been planned to create all finance ETL processes in PKG_ETL_FINANS
package under MONESTAT schema on data warehouse.
i.
In order to overcome the possible performance problems in the process of filling
finance tables on data warehouse, data have been designed as summary data and
queries have been created according to this strategy. The needs for
table/index/partition which could be required later will be shared with Ministry of
Education Information Technologies team during test.
j.
All “ISLEM_TARIHI” fields in intended source tables imply the system date during
record writing to tables. Data record year fields which show the related fiscal year of
data, is a numeric field designed to enter year information.
1.19. ETL CONTRAINTS OF COMBINED INSTITUTION, CLASSROOM, DIVISION AND TEACHER
DATASET
A. Source Tables:
The source environment for the ETL process is the 'Monestat' schema. To be able to combine
different fact values into one fact table for each school level , other target tables which are
designed before in the 'Monestat' schema was used as source tables.
T_KURUM_OGR_OGRETMEN : This table is a metadata table which covers referanse dates
and education period of source tables which was used in the combination. If the
Yılbası_Durum column contains 'B', FACT_IO_OGR_YIL_BASI_BILGILERI is used for getting
student numbers, if 'S' FACT_IO_OGR_YIL_SONU_BILGILERI is used for getting student
numbers
FACT_IO_OGR_YIL_BASI_BILGILERI : For the combination of institution and students,
students number was got from this table according to the information into
T_KURUM_OGR_OGRETMEN metadata table.
FACT_IO_OGR_YIL_SONU_BILGILERI: For the combination of institution and students,
students number can be get from this table according to the information into
FACT_PERSONEL_BILGILERI : For the combination of institution and teachers, teacher
numbers
was
got
from
this
table
according
to
the
information
into
FACT_KURUM_KULLANIM_ALAN : For the combination of institution and classrooms,
classroom numbers was got from this table according to the information into
B. Target Tables:
FACT_KURUM_OGR_OGRETMEN : For each educational institution, institution code, name,
institution type, number of classrooms, number of divisions, number of girls(student), number
of boys(student), number of female teachers, number of male was stored in this table.The
referanse dates and educational periods was taken from T_KURUM_OGR_OGRETMEN
metadata table.
C. ETL Constraints:
a. For each educational institute there was a one row in the target table.For some
institution types, the classroom, division and teacher numbers may be 0, because
those numbers are belongs to main type of the institution.
b. Open primary school, open high school, SHCEK, mobile pre-primary classes, other
institutions pre-primary classes won't put into the target table. This table only covers eschool , e-staff and institution systems.
c. For the classroom numbers each attribute in the e-school sytem was used,
Number of classrooms (used as pre-primary)
Number of classrooms (unused)
Number of sections either these are not classroom
Number of classrooms (Kullanılan, Kullanılmayan, Anasınıfı dahil)
d. Indicators which are student numbers per classrooms, student numbers per division,
student numbers per teacher was taken from FACT_KURUM_OGR_OGRETMEN
table. As the teacher numbers are related to main type of the school, these type of
indicators can be taken by province or General Directoriate levels.
1.20. NON-FORMAL EDUCATION
A. Source Tables:
schema.
BI_FACT_YAYGIN_KURS_BLG: The courses opened in non-formal education are located in
this table.
a. Reference Date
b. Course Period
c. Institution Number
d. Institution Type
e. Course Type
f. Course Class
g. Course Code
h. Course Name
i.
Course Group
j.
Course FOET
k. Course Open Style
l.
Certification Type
m. Course Status
n. Max Course Duration
o. Course Id
p. Course Start Date
q. Course End Date
BI_FACT_YAYGIN_KURSIYER_BLG: The trainees and their attendance information are
a. Reference Date
b. Course Period
d. Institution Type
e. Course Type
f. Course Class
g. Course Code
h. Course Name
i.
Course Group
j.
Course FOET
l.
Certification Type
m. Course Status
o. Course Id
p. Trainee Gender
q. Trainee Birth Year
r. Trainee Age
s. Is Adult?
t. Marital Status
u. Education Status
v. Labor Status
w. Disabled Status
x. Success Status
BI_FACT_YAYGIN_PERSONEL_BLG: The number of instructors attended to non-formal
education courses are located in this table.
a. Reference Date
b. Course Period
d. Institution Type
e. Course Type
f. Course Class
g. Course Code
h. Course Name
i.
Course Group
j.
Course FOET
l.
Certification Type
m. Course Status
o. Course Id
p. Branche
q. Labor Status
BI_MTSAS_BASVURU: The number of applicants for motor vehicles driving courses.
a. Reference Date
b. Year of Certification
c. Certification Type
d. Institution Number
e. Institution Type
f. Applicant Gender
g. Education Status
h. Year of Birth
BI_MTSAS_SERTIFIKA: The number of certificates given as motor vehicles driving licenses.
a. Reference Date
b. Year of Certification
c. Certification Type
d. Institution Number
e. Institution Type
f. Applicant Gender
g. Education Status
h. Year of Birth
B. Target Tables:
The ETL process for Non-formal Education application uses the source tables enlisted above
below:
FACT_YAYGIN_KURS_BILGILERI: The number of non-formal education courses are stored
in this table which will be fed from BI_FACT_YAYGIN_KURS_BILGILERI.
FIGURE 57 Table Description of FACT_YAYGIN_KURS_BLG
FACT_YAYGIN_KURSIYER_BLG: Number of trainees by institutions and courses are stored
in this table.
FIGURE 58 Table Description of FACT_YAYGIN_KURSIYER_BLG
FACT_YAYGIN_PERSONEL_BLG: Number of staff by institutions and courses are stored in
this table.
FIGURE 59 Table Description of FACT_YAYGIN_PERSONEL_BLG
FACT_MTSAS_BASVURU: Number of applicants for motor vehicles certification by institutions
are stored in this table.
FIGURE 60 Table Description of FACT_MTSAS_BASVURU
FACT_MTSAS_SERTIFIKA: Number of certificates given for motor vehicles by institutions are
stored in this table.
FIGURE 61 Table Description of FACT_MTSAS_SERTIFIKA
C. ETL Constraints:
b. The source tables about courses, trainees and staff shall have the same reference date.
c. Courses which currently are in open status shall not be included in Statistics.
d. The courses which were not opened shall be excluded from Statistics.
e. The Statistics shall include trainees with two success levels (Successful/Unsuccessful).
Trainees who did not attend regularly shall be assessed as unsuccessful.
f.
2
The staff data shall include only the staff who were assigned and had job in courses.
DATABASE OBJECTS FOR INTERNAL USAGE
2.1. LOOK-UP TABLES
T_UOE_TANIM_TABLOSU : To be able to combine different fact tables into one UOE fact
table this look-up metadata table was created. After defining relevant referance dates and
education period information of different facts which are formal education e-school data
located in Fact_IO_Ogr_YilBasi_Bilgileri and Fact_IO_Ogr_YilSonu_Bilgileri, open primary
school data located in Fact_Acik_Ilkogretim_Yeni, open high school data located in
Fact_Acik_Lise_Yeni,
other
pre-primary
students
data
located
in
Fact_Dis_Kurum_Ogr_Ogretmen, a new record have to be created into this table. Then, after
running relevant ETL package Fact_UOE_Bilgileri table will be contain new record for the
formal education UOE data with defined UOE Period.
There are columns for staff, finance and foreign language UOE data processing in this
metadata table. After entering relevant referance date for those columns, relevant ETL
packages for UOE transformation must be run by IT department experts.
FIGURE 62 Table Description of T_UOE_TANIM_TABLOSU
T_GECICI_SHCEK_BILGI : This table was used for storing SHCEK data which are located in
Excel spreadsheets. This is a temporary table, after the transformation data will store in
Fact_DIS_KURUM_OGR_OGRETMEN fact table.
FIGURE 63 Table Description of T_GECICI_SHCEK_BILGI
T_KURUM_OGR_OGRETMEN : This table is a metadata table which covers reference dates
and education period of source tables which was used in the combination of institution,
classroom, student and teacher. If the Yılbası_Durum column contains 'B',
FACT_IO_OGR_YIL_BASI_BILGILERI is used for getting student numbers, if 'S'
FACT_IO_OGR_YIL_SONU_BILGILERI is used for getting student numbers
FIGURE 64 Table Description of T_KURUM_OGR_OGRETMEN
ST_ISLEM_TARIHI : This table contains the reference dates and educational periods of the
transformed targets. This table was designed for performance tuning of the developed BI
reports for reaching referance dates and periods faster in the command provider part .There
are 3 columns in the table;
DONEM contains the education period,









'B' represents Fact_IO_OGR_YILBASI_BILGILERI
'S' represents Fact_IO_OGR_YILSONU_BILGILERI
'E' represents Fact_IO_ENGELLI_OGR
'P' represents Fact_IO_OGRENCI_PASIF
'BO' represents Fact_BURS_SINAV_ONAY_OGR
'AB' represents Fact_AKTIF_BURS_OGR_BILGILERI
'BI' represents Fact_BURSU_IPTAL_OGR_BILGILERI
'Y' represents Fact_YABANCI_DIL
'YT' represents Fact_YATILILIK_DURUM_OGR
FIGURE 65 Table Description of ST_ISLEM_TARIHI
ST_ISLEM_TARIHI_KURUM : This table contains the reference dates of the transformed
targets related to institutions. This table was designed for performance tuning of the developed
BI reports for reaching referance dates faster in the command provider part .There are 3
columns in the table;







'K' represents Fact_KURUMLAR
'A' represents Fact_KURUM_KULLANIM_ALAN
'B' represents Fact_KURUM_BINA
'D' represents Fact_DIS_KURUM_OGR_OGRETMEN
'M' represents Fact_KURUM_KUTUPHANE_MATERYAL
'Y' represents Fact_OZEL_YURT_KAPASITE
'P' represents Fact_PERSONEL_BILGILERI
FIGURE 66 Table Description of ST_ISLEM_TARIHI_KURUM
ST_ISLEM_TARIHI_ACIK : This table contains the reference dates and educational periods
of the transformed targets related to open schools. This table was designed for performance
tuning of the developed BI reports for reaching referance dates and periods faster in the
command provider part .There are 3 columns in the table;
DONEM_ACK contains the description of the period


'AI' represents Fact_AIO_OGRENCI_YENI
'AL' represents Fact_AOL_OGRENCI_YENI
FIGURE 67 Table Description of ST_ISLEM_TARIHI_ACIK
ST_ISLEM_TARIHI_FINANS :This table contains the reference dates of the transformed
targets related to finance data source types. This table will be used as a dimension table in BI
system. There are 3 columns in the table;
ISLEM_YILI contains the financial year,








'TF1' represents Fact_ TEFBIS_FINANS1
'TF2' represents Fact_ TEFBIS_FINANS2
'TFO' represents Fact_ TEFBIS_FINANS_OZEL
'EB1' represents Fact_ EBUTCE_FINANS1
'EB2' represents Fact_ EBUTCE_FINANS2
'EBO1' represents Fact_ EBUTCE_FINANS1_BELTAB
'EBO2' represents Fact_ EBUTCE_FINANS2_BELTAB
'HH1' represents Fact_ HANEHALKI_FINANS1_UOE
FIGURE 68 Table Description of ST_ISLEM_TARIHI_FINANS
ST_ISLEM_TARIHI_YAYGIN : This table contains the reference dates and educational year
of the transformed targets related to open schools. This table was designed for performance
tuning of the developed BI reports for reaching referance dates and periods faster in the
command provider part .There are 3 columns in the table;
DONEM_ACK contains the description of the period





'MB' represents Fact_MTSAS_BASVURU
'MS' represents Fact_MTSAS_SERTIFIKA
'K' represents Fact_YAYGIN_KURS_BLG
'KY' represents Fact_YAYGIN_KURSIYER_BLG
'P' represents Fact_YAYGIN_PERSONEL_BLG
FIGURE 69 Table Description of ST_ISLEM_TARIHI_YAYGIN
ST_YAS_GRUPLARI : This table contains row for ages groups in staff UOE tables. For the
staff UOE data, age groups are queried in this table.
FIGURE 70 Table Description of ST_YAS_GRUPLARI
ST_MTSC_EGITIM_DURUMU : This table contains rows for the education levels of
candidates in MTSC (vehicle courses) courses.
FIGURE 71 Table Description of ST_MTSC_EGITIM_DURUMU
FIGURE 72 Records in ST_MTSC_EGITIM_DURUMU
ST_OGRENCI_DURUM : This table contains rows for student status. If any additional records
needed, this table must be updated by IT department experts within MoNE.
FIGURE 73 Records in ST_OGRENCI_DURUM
ST_KURUMTUR : This table contains information about institution types. The primary key of
this table is 'Tur_Kodu' and 'Bagli_Genel_Mudurluk'. According to changes in the
organizational structure, to be able to show correct institution type the relevant general
directoriate information was used as primary key also. There are additiobnal columns in the
table for identifiying institution type like 'Formal/Non-Formal', 'Public/Private/Open', 'Education
Level'. If any new records will ad into main source of institution type which was stored at
"ilsisweb" schema, those records must be ad manually in this table also with additional
information columns by IT department experts.
FIGURE 74 Table Description of ST_KURUMTUR
ST_YERLESIM_YERI :This table contains only one column named 'YERLESIMYERI' and
contains below rows;
Belde
Boş
Köy
Şehir
ST_OZELYURT_YERLESIM_YERI : This table contains code and description of locations
which are used in private dormitories and contains below rows;
İl
İlçe
Köy
Kasaba
FIGURE 75 Table Description of ST_OZELYURT_YERLESIM_YERI
ST_YIL_GRUPLARI: This tablke contains rows for service entry dates of the institutions.
There are two columns in the table which are year and year group information. this table used
as a dimension table in the institutions subject area.
FIGURE 76 Table Description of ST_YIL_GRUPLARI
ST_SINIF_SEVIYESI : The class levels in the formal education is stored in this table. The
class levels combined with education levels and for UOE grade informations are also stored in
this table.
FIGURE 77 Records of ST_SINIF_SEVIYESI
ST_ULKELER : This table contains country data with EU country and non-EU country
attributes.
FIGURE 78 Records of ST_ULKELER
ST_CINSIYET : This table is used in creating relationships with student data.
ST_CINSIYET_PERSONEL : This table is used in creating relationships with staff data.
ST_CINSIYET table can not used as the information stated in the tables are different for
females. In ST_CINSIYET table female is shown as 'KIZ' in the personnel table it is used as
'KADIN'.
ST_EBUTCE_IDARIBIRIM_TURU: This table is a lookup table for discriminating the data
(obtained from Central Budget tables) for province (district) national education directorate. This
table will be used as a dimension table in BI system.
FIGURE 79 Table Description of ST_EBUTCE_IDARIBIRIM_TURU
ST_HANEHALKI_ANKET_TIPLERI: It has been designed as a look-up table which contains
household questionnaire types and their descriptions. This table will be used as a dimension
table in BI system.
FIGURE 80 Table Description of ST_HANEHALKI_ANKET_TIPLERI
ST_HANEHALKI_SORU_TANIM: It has been designed as a look-up table which contains
household questionnaire questions and their descriptions. This table will be used in data
transformation packages for Finance-1 UOE tables. And also for household expenditures
report, this table used as dimension.
FIGURE 81 Table Description of ST_HANEHALKI_SORU_TANIM
ST_FOET : This table used for FOET classifications both in Turkish and English definitions.
FIGURE 82 Table Description of ST_FOET
ST_GUNLER : This table is used for time dimensions. In the scope of Monestat project for
private dormitories opening and closure dates, this referance table is used. The last date in
this table is '01.01.2015'. When more dates needed, new records should be add manually.
FIGURE 83 Table Description of ST_GUNLER
ST_ISCED : This table contains ISCED mapping definitions. For each institution types and
grades ISCED levels, programme oriantation and programmae destination attributes are
defined in this table. During the data transformation packages, these records are used for
identifying ISCED levels of student and staff.
FIGURE 84 Table Description of ST_ISCED
FIGURE 85 Records of ST_ISCED
ST_ISCED_VIEW : This table contains only levels of the ISCED classification. This table firstly
crated as view, but because of performance problems it was changed as table.
FIGURE 86 Table Description of ST_ISCED_VIEW
FIGURE 87 Records of ST_ISCED_VIEW
ST_ISCED_EK_TANIMLAR : This table is used for UOE raports to be able to identify ISCED
level, programme orientation and programme destination parameters with all education
programmes totals.
FIGURE 88 Table Description of ST_ISCED_EK_TANIMLAR
ST_PERSONEL_GOREV_KATEGORI : This table is used in the transformation phase of staff
data to be able identify the category and group information of the staff title. These infromation
are mainly queried in UOE data tables.
FIGURE 89 Table Description of ST_PERSONEL_GOREV_KATEGORI
FIGURE 90 Records of ST_PERSONEL_GOREV_KATEGORI
2.2. VIEWS
ST_OKULONCESI_KURUMTUR : This table is used for defining pre-primary organization
types which are summer school, mobile school, SHCEK and other institutions pre-primary
schools
FIGURE 91 Table Description of ST_OKULONCESI_KURUMTUR
FACT_DIS_KURUM_OGRENCI_V : This view is used in UOE transformation of students in
pre-primary classes of summer school, mobile school, SHCEK and other institutions preprimary schools.
FIGURE 92 Table Description of FACT_DIS_KURUM_OGRANCI_V
2.3. MATERIALIZED VIEWS
ST_NUTS_IL_ILCE : This materialized table contains 3 NUTS levels and district definitions of
Turkey. The source data comes from okulsis and ilsisweb schemas. NUTS levels are taken
from lookup tables in okulsis schema, district information is taken from ST_ILLER and
ST_ILCELER tables in ilsisweb schema.
FIGURE 93 Table Description of ST_NUTS_IL_ILCE
ST_NUTS_IL_ILCE_YURT : This materialized table contains 3 NUTS levels and district
definitions of Turkey. The source data comes from okulsis and ilsisweb schemas. NUTS levels
are taken from lookup tables in okulsis schema, province infromation is taken from ST_ILLER
table in ilsisweb schema and district information is taken from ILCE table in ilsis schema.
FIGURE 94 Table Description of ST_NUTS_IL_ILCE_YURT
ST_OGRYIL_ISCED_MV : This materialized view is used in ISCED calculations of staff and
finance tables for UOE. For each institutions the number of students in different ISCED levels
are queried from this materialized view during the PL/SQL packages. This table didn't use in
the BI model.
FIGURE 95 Table Description of ST_OGRYIL_ISCED_MV
ST_KURUM_IL_MV : This materialized view is used in data transformation packages of
formal education student data to be able to write queries in good performance times. This
table didn't use in the BI model.
FIGURE 96 Table Description of ST_KURUM_IL_MV
ST_ANA_SINIFI_VAR : To be able to query pre-primary classes in the institutions this
materialized view is used during the ETL phase of institutions. The source table for this view is
'BI_SINIF_SUBE_SAYISI' under 'okulsis' schema. Only schools which have pre-primary
classes (class level is equal to 0) is populated in this materialized view.
FIGURE 97 Table Description of ST_ANA_SINIFI_VAR
FACT_UOE_CLASS_MV: To be able to prepre UOE Class data table, the number of divisions
within the Fact_IO_OgrYil_Basi_Bilgileri and Fact_IO_OgrYil_Sonu_Bilgileri was queried in
this materialized view.
FIGURE 98 Table Description of FACT_UOE_CLASS_MV
ST_BURS_DONEM : The schoolarship periods are stored in this materialized view. The
source table is 'ST_BURS_DONEM' under okulsis schema. For the start year of the period a
function named '' is develeoped in '' package. In the ETL packages the start date of the period
is needed, for this purpose a function named 'BURS_DONEM_TARIHI' under
'PKG_ETL_BURS_YATILI_OZELYURT' package is created to identifiy the start year from the
period definition. The source table is 'ST_BURS_DONEM' under 'okulsis' schema.
FIGURE 99 Table Description of ST_BURS_DONEM
ST_DONEM_BILGILERI: The education periods in e-school system is queried in this
materialized view.The source table is 'ST_DONEM_BILGILERI' under 'okulsis' schema.
FIGURE 100 Table Description of ST_DONEM_BILGILERI
ST_ENGELLI_SINIF : This materialized view is used for querying division names in disabled
students fact table. The main source table is 'ST_OGRENCI_SOZLUK' and
'ST_OGRENCI_SOZLUK_LISE' in 'okulsis' schema. For primary level class definitions
between 15 and 78 are populated in this materialized view. For upper-secondary level class
definitions between 86 and 113 are populated in this materialized view.
FIGURE 101 Table Description of ST_ENGELLI_SINIF
ST_DIL_KODLARI_MV : This materialized view contains foreign languge cdefinitions which
was taken from 'ST_OGRENCI_SOZLUK' source table in 'okulsis' schema
FIGURE 102 Table Description of ST_DIL_KODLARI_MV
BI_YABANCI_DIL_MV : This materialized view is used during the transformation packages of
foreign language studies for formal education. The source tables are 'BI_ILK_YABANCI_DIL'
and 'BI_LISE_YABANCI_DIL' in 'okulsis' schema. This table didn't use in the BI model.
FIGURE 103 Table Description of BI_YABANCIDIL_MV
ST_ATAMA_SEBEPLERI_MV : This materialized view contains assingment reasons of public
institutions staff.
FIGURE 104 Table Description of ST_ATAMA_SEBEPLERI_MV
ST_BRANSLAR_MV : This materialized view contains brunch definitions of both public and
private institutions staff.
FIGURE 105 Table Description of ST_BRANSLAR_MV
ST_GOREV_UNVAN_MV : This materialized view contains job title definitions of both public
and private institutions staff.
FIGURE 106 Table Description of ST_GOREV_UNVAN_MV
ST_HIZMET_SINIFLARI_MV : This materialized view contains service category definitions for
public institutions staff.
FIGURE 107 Table Description of ST_HIZMET_SINIFLARI_MV
ST_ISTIHDAM _TIPLERI_MV : This materialized view contains employment type definitions
of both public and private institutions staff.
FIGURE 108 Table Description of ST_ISTIHDAM_TIPLERI_MV
ST_OGRENIM_DURUMLARI_MV : This materialized view contains education level definitions
of both public and private institutions staff.
FIGURE 109 Table Description of ST_OGRENIM_DURUMLARI_MV
ST_UNVANLAR_MV : This materialized view contains permanent staff title definitions for
public institutions staff.
FIGURE 110 Table Description of ST_UNVANLAR_MV
ST_YAYGIN_BASARI_DURUMU_MV : This materialized view contains success states of the
participants at the end of the non-formal courses , contaning 'Başarılı' and 'Başarısız'.
FIGURE 111 Records of ST_YAYGIN_BASARI_DURUMU_MV
ST_YAYGIN_BRANSLAR_MV : This materialized view contains brunche definitions of staff in
the non-formal subject area.
FIGURE 112 Records of ST_YAYGIN_BRANSLAR_MV
ST_YAYGIN_CALISMA_DURUMU_MV : This materialized view contains students
employment status definitions in non-formal education subject area.
FIGURE 113 Records of ST_YAYGIN_CALISMA_DURUMU_MV
ST_YAYGIN_ENGEL_DURUMU_MV : This materialized view contains students diabled
status definitions like autistic, hearing-impaired etc. in non-formal education subject area.
FIGURE 114 Records of ST_YAYGIN_ENGEL_DURUMU_MV
ST_YAYGIN_KURS_ACMA_BICIMI_MV : This materialized view contains courses activity
status in non-formal education subject area.
FIGURE 115 Records of ST_YAYGIN_KURS_ACMA_BICIMI_MV
ST_YAYGIN_KURS_DURUMU_MV : This materialized view contains the status of course like
canceled, completed, open etc. in non-formal education subject area.
FIGURE 116 Table Description of ST_YAYGIN_KURS_DURUMU_MV
ST_YAYGIN_KURS_TIPI_MV : This materialized view contains course types like vocational
and technical courses, general courses and literacy courses in non-formal education subject
area. Vocational and technical courses can be queried as job-related courses.
FIGURE 117 Table Description of ST_YAYGIN_KURS_TIPI_MV
ST_YAYGIN_MEDENI_DURUMU_MV : This materialized view contains marital status of the
students in non-formal education subject area.
FIGURE 118 Table Description of ST_YAYGIN_MEDENI_DURUMU_MV
ST_YAYGIN_OGRENIM_DURUMU_MV : This materialized view contains education levels of
the students in non-formal education subject area.
FIGURE 119 Table Description of ST_YAYGIN_OGRENIM_DURUMU_MV
ST_YAYGIN_PERSONEL_STATUSU_MV : This materialized view contains status of staff in
non-formal education subject area. The records in this table are;
Kadrolu
Sözleşmeli
Diğer Personel
Görevlendirme
FIGURE 120 Table Description of ST_YAYGIN_PERSONEL_STATUSU_MV
ST_YAYGIN_SERTIFIKA_TIPI_MV : This materialized view contains certificate types of
vehicle courses (MTSC) in non-formal education subject area.
FIGURE 121 Table Description of ST_YAYGIN_SERTIFIKA_TIPI_MV
3
UOE TRANSFORMATION RULES
3.1. DATABASE TABLES FOR UOE
T_UOE_TANIM_TABLOSU : To be able to combine different fact tables into one UOE fact
table this look-up metadata table was created. After defining relevant referance dates and
education period information of different facts which are formal education e-school data
located in Fact_IO_Ogr_YilBasi_Bilgileri and Fact_IO_Ogr_YilSonu_Bilgileri, open primary
school data located in Fact_Acik_Ilkogretim_Yeni, open high school data located in
Fact_Acik_Lise_Yeni,
other
pre-primary
students
data
located
in
Fact_Dis_Kurum_Ogr_Ogretmen, a new record have to be created into this table. Then, after
running relevant ETL package Fact_UOE_Bilgileri table will be contain new record for the
formal education UOE data with defined UOE Period.
There are columns for staff, finance and foreign language UOE data processing in this
metadata table. After entering relevant referance date for those columns, relevant ETL
packages for UOE transformation must be run by IT department experts. UOE data
transfomation packages are stated in the table given in Section E, Part 1.3.
'TanimTur' column represents definition type in this metadata table. 'U' represents UOE, 'Y'
represents publications. This table will use for both UOE and publication combinations.
FACT_UOE_BILGILERI : This table was created for preparing formal education UOE data
containing Enrl, Entr, Regio and Grad data tables.
FACT_UOE_CLASS_MV : To be able to prepre UOE Class data table, the number of
divisions within the Fact_IO_OgrYil_Basi_Bilgileri and Fact_IO_OgrYil_Sonu_Bilgileri was
queried in this materialized view.
FACT_YABANCI_DIL_UOE: Number of students by number of foreign languages studied,
ISCED levels and institutions are stored in this table which will be reference to UOE reports.
FACT_PERSONEL_UOE : Number of public and private institutions saff data will be
transformed into ISCED levels and categories for Ad-Hoc-Module-Pers UOE data table. The
transformation results will be stored in this table. SHCEK, other pre-primary institutions and
mobile schools teacher data also put in this table.
FACT_PERS_UOE12 : Number of public and private institutions teachers an school level
managers data will be transformed into this target table containing age and sex information
with ISCED levels. SHCEK, other pre-primary institutions and mobile schools teacher data
also put in this table.
FACT_PERS_ENRL : Number of students in schools whose teacher numbers are populated
in FACT_PERS_UOE12 table will be stored in this table. Open primary school and open high
school students data won't be stoıred in this table.
FACT_HANEHALKI_FINANS1_UOE: The Finance 1 categories of BI_HANEHALKI_ANALIZ
table are determined in this table. The analysis results of household questionnaire will only be
used for Finance 1 table.
3.2. UOE TRANSFORMATION RULES
UOE Transformation for formal education, staff and finance was defined jointly with SDP and
IT departments candidates and decisions taken are listed below;
1. How ISCED classification of staff in charge in Ministry, Provincial and District Director of
National Education should be performed in 'Ad-Hoc-Module-Pers' UOE table?
a. Decision taken in weekly meeting dated 14.02.2012:
i. According to number of students within Provincial and District, proportional
transformations will be performed concerning ISCED transformation of staff
in administration and administrative staff within Provincial and District
Directors of National Education.
ii. ISCED transformation of staff in administration and administrative staff within
Ministry will be performed with the proportional transformation according to
number of students in across Turkey.
b. Alternative proposal by international experts:
i. Proportions can be done for number of teachers instead of number of students
2. Is there any special situation in category divisions in 'Ad-Hoc-Module-Pers' UOE table?
a. Putting in the table of only the number of staff in charge in schools is stable in
instruction book for maintenance and operation staff. Therefore, maintenance and
operation staff in charged in administrative organizations won’t be reflected in this
table.
b. Putting in the table of only the number of staffs in charge in schools is stable in
instruction book for health and social services. Therefore, health and social
services staff in charged in administrative organizations won’t be reflected in this
table.
3. How ISCED distribution of administrative organization in charged in primary schools
should be performed?
a. Decision taken in weekly meeting dated 14.02.2012:
i. Proportional separation will be performed for ISCED transformation of auxiliary
staff in charge in primary education level according the number of students.
The proportions will be determined according to the pre-primary placed in
school, the number of students studying in grades 1-5 and grades 6-8.
4. The rules of work decided to be used (clarified in previous meetings) during the filling of
UOE tables:
a. All staff for civil servant and private sector will be put into UOE tables as full time.
b. The staff in pre-school (educator + manager) will be in ISCED 0 level.
c. The branch of teacher in primary schools will be registered in level of 4439 and preschool teacher will be registered in the level of ISCED 0.
d. The branch of teaches in secondary schools will be registered in level of 4439 and
pre-school teacher will be registered in the level of ISCED 0.
e. The branch of teacher in primary schools:
2403- School Teaching
2632- School Teaching for Children with Mental Disabilities
2647- School Teaching for the Visually Impaired
2651- School Teaching for Hearing Impaired
Will be registered in ISCED level 1.
f. The branch of teacher in primary school will be registered in the level of ISCED 2.
g. Staff having the branch of counselor will be involved in the group of “Pedagogical
Support Staff”.
h. The counselor will not be included in the number of teacher.
i. All qualified instructor and qualified instructor staff will be considered as teachers
and only if the institution type is pre-school, staff having concerned title will be
considered as teacher aides.
j. The branch of manager will determine senior staff for primary school and if it has
branch of pre-school, ISCED 0 will appoint; if it has branch of school teaching,
ISCED 1 will appoint and for the other branches ISCED 2 will appoint.
k. ISCED level that school type has within the secondary education will be used for
both teachers and administrators.
l. It will be considered in institution within civil servant staff.
m. In private training institutions, general director and deputy general director will be
considered in top executive.
n. The teacher within SHCEK will be considered as attendant in “Private Training
Institution” and those will be viewed in “Private” part in UOE tables.
o. The number of students in Pers_ENRL UOE tables will be involved in the number of
students in the schools having staff data. The number of open primary school
students and open high school students will not be shown in this table. In a similar
way, staff in the secondary schools which have poly-type is being seen within main
type. For this reason, the number of students in only main type will be considered
for these types of school. this situation was discussed and finalized in this way in the
meeting dated 07.02.2012.
p. Although a teacher is tenured, the situation of giving lessons at the same time in
other private institution is examined, registration at the rate of 0.3% was determined.
The decision of the rate acquired might be neglected in statics, was taken in the
meeting dated in 07.02.2012. Concerned staff registration will be considered in both
public school and private school.
q. It is determined the number of teachers working in more than one institution at the
same time is 0.1% in the examinations. The decision of the rate acquired might be
neglected in statics was taken in meeting dated 07.02.2012. According to this
decision, the staff serving at the same time in more than one private school will be
considered in each school and he will be considered full time staff for each
registration.
r. UOE transformations, of all staff working in institutions where ISCED definitions
can’t be performed in administrative organization having not students like evening
arts school, will be delivered proportionately according to ISCED division of the
students within the province on which the institution depends.
5. How the open elementary school and open high school students should be presented
as fulltime or part time?
a. After the graduation from open primary school and open high school, there is
diploma acquisition. This is handled in a compressed program in basic curriculum.
These are the programs started with purpose of especially adult education. In the
case of registering of the students under 15 years old in this system for any reason
it is required for them to take place in the system for the period of standard primary
education. Therefore, it is found appropriate that students graduated from these
programs are considered full time.
6. The number of students and teachers in institutions registered in e-school and training
according to MoNE curriculum in educational institution abroad should be involved in
UOE table?
a. The teachers in charge and the students registered in these kinds of institutions will
be involved in the table of concerned country.
7. How it is required to act for the students registered to Open High School and Open
Primary School but living abroad?
a. Open Primary School students and Open High School students are shown in
ENRL_Adult table.
b. As stated in UOE Manuel Vol 1, 4.6.3, putting of the students taking distance
learning abroad into ENRL7 and GRAD1 table as mobile students is indicated. In
the meeting with the international expert, to be able to accept a student as mobile,
the information that the student should have foreign national or if the student is a
Turkish citizen, he or she should complete previous education abroad was
acquired. So, it was stated that we can not consider those students as mobile.
c. There is no clear explanation within the presentation of these students in Region
table. In the opinions received, owing to the fact that administrative units of Open
Education institutions are in Ankara, it is stated that these students may be shown
in ‘Ankara’. This suggestion was used in UOE transformation ETL packages.
8. Students of summer schools pre-primary level students won't put into UOE tables.
9. How 3C, of similar duration as ‘typical 3A or 3B programs’ and ‘3C of shorter duration
as typical 3A or 3B programs’ parts in Grad table should be filled?
a. The programs in 3C level in MoNE curriculum are given below.
Vocational Education Center
Public Education Center
Practical Trades Schools for Girls
Maturation Institute
Adults Technical Training Center
Vocational and Technical Open Education
Job Training Center for Teachable Mental Impaired
Job Training Center for Autistic Children
Motor Vehicle Driving Courses
Various Courses
A large proportion of these programs are within the concept of non-formal
education and UOE doesn’t within the concept of non-formal education data. As
well as Vocational and Technical Open Education is a formal education, it doesn’t
embody student. For this reason, relevant parts in Grad table are not fulfilled.
10. The number of students taking foreign language education is given on Lang UOE table.
If a student chooses more than one foreign language education, these students should
be given for each language separately?
a. The students taking more than one foreign language education should be put into
ENRLLNG1 table separately for each language. It should be specified whether
taking the data from the system with this division after meeting with experts of
information technologies.
b. It is required to give the number of the students never taking foreign language
education, taking one language education and students taking 2 or more foreign
language education in ENRLLNG2 and the student should be considered as
repeating.
11. How our approach to student attendance should be in FIN-ENRL-2 table within Finance
1?
a. Basic principle is to synchronize the student attendance situation in an academic
year according to fiscal year calendar. Reference year should be date before 1
year than other tables like in finance 1 and finance 2. In this respect, because of
the fact that academic year is between September and June and fiscal year is
between January and December, method used in general is to average according
to fiscal year.
12. When ABS codes of the education expenditures realized within the finance table is
taken into account, design was realized according to present ABS 2012 systematic. For
the sustainability of the system, the situation of the changing in ABS codes will be
required to update the design study.
13. TEFBİS, Household interview survey and e-budget(TEFBİS-Ebudget summary tables)
will be used as a source for finance tables.
14. In some cases that house hold education expenditures survey isn’t performed according
to whole population census, it is required to perform population distribution according to
ISCED distribution during sampling of survey and population estimation. Therefore,
UOE reports, in which household interview will be put, will be expanded and they won’t
be involved in table.
15. ISCED division will be performed for the situation corresponding to school types of
education expenditure and ABS codes. However, the situations, which can’t be
separated like ministry department expenditures data, will be separated by making a
proportional prediction.
16. In the case that situation incompatible for Turkey’s answer and special situation for
Turkey in the present UOE tables, required explanation under concerned UOE tables
should be given as footnote.
4
BI BUSINESS LAYER DESIGN
4.1. LAYERS IN THE BI ADMINISTRATION TOOL
There are three main layers in the BI Administration Tool. The first layer is called as 'Physical
Layer', which covers physical metadata of the data warehouse structures. The table definitions
and relatioıns with other tables containing each constraints are stated in this layer. The second
layer is called as 'Business Layer', which covers business model of the developed BI system.
Fact and dimension tables and their relations and new hierarchies are stated in this layer. The
last layer is called as 'Presentation Layer', the end user can only reach this layer. End user
can make his own analysis by reaching presentation layer objects.
In Monestat project, for each subject area there are different business model which are,





Institutions (BM_KURUMLAR)
Formal Education Student Data (BM_ORGUN_OGRENCI)
Staff Data (BM_PERSONEL)
Finance (BM_FINANS)
Non-Formal Course, Student and Staff Data (BM_YAYGIN)
FIGURE 122 Three Layers in the BI Administration Tool
4.2. INSTITUTIONS BUSINESS MODEL
Institution business model covers number of institutions with physical capacity informations.
There are two main hierarchies defined in this model which are;


Institution type hierarchy which contains education level, public/private/open,
general/vocational, General directoriate, institution type, institution levels
NUTS hierarchy which contains NUTS 1 , NUTS 2, NUTS 3(province), district and
institution levels
The objects which are labeled as 'Tanımları' are dimension tables and which are labeled as
'Bilgileri' are fact tables. Fact tables covers numeric measures like number of institutions,
number of pensions, number of classrooms etc.
Process date tables whose label begins 'İşlem Tarihi', are dimension tables to cover reference
dates of the corresponding fact table. These tables are designed for performance tuning to be
able to reach relevant data quickly.
FIGURE 123 Institutions Business Model
4.3. FORMAL EDUCATION BUSINESS MODEL
Formal education business model mainly covers student Statistics in formal education
containing;








Enrolled students in e-school
Graduated students in e-school
Open Primary School students
Open High School Students
Mobile, summer, SHCEK and other institutions pre-primary students
Schoolarship students
Boarding students
Private dormitories and capacities
There are 4 hierarchy defined in this model.
 Institution hierarchy (Kurum Hiyerarşisi) contains institution type and NUTS hierarchy
levels.



Institution hierarchy(View) (Kurum Hiyerarşisi(View)) contains institution type and
NUTS hierarchy levels. This hierarchy have to be created because of a constraint in
the BI tool. In the business model one dimension table must be only used in one
hierarchy. Because of this constraint when ever needed to use a second institution
hiearchy this defined hierarchy must be used. This hierarcy is used in boarding
students Statistics to be able to analyse beneficiary institution.
NUTS hierarchy contains NUTS levels from NUTS 1 to district. This hierarchy is used
in open primary and high schools analysis.
Time dimension contains year,month,day levels and used in private dormitories
opening dates information.
For the open primary and hish school designs there are two different fact tables in the
model.The previous version of the design is not deleted from the model. All analysis in the
dashboards are used
Açık Lise Öğrenci Bilgileri(Yıllık) and Açık İlköğretim Öğrenci Bilgileri(Yıllık) fact tables.
For the student analysis whose source is e-school system, there are two main fact tables. The
first table contains active semesters active students and labeled as 'Öğrenci Öğretim Yılı Başı
Bilgileri'. The second table contains passive semesters students and data is available at the
end of the semester, this table labeled as 'Öğrenci Öğretim Yılı Sonu Bilgileri'.
'Bilgileri' are fact tables. Fact tables covers numeric measures.
FIGURE 124 Formal Education Business Model
4.4. STAFF BUSINESS MODEL
Staff business model covers staff Statistics in both public and private institutions. There are
two main hierarchies defined in this model which are;


institution levels
'Bilgileri' are fact tables. Fact tables covers numeric measures like number of staff.
FIGURE 125 Staff Business Model
4.5. FINANCE BUSINESS MODEL
Finance business model covers expenditure Statistics in both school and central. There are
two main hierarchies defined in this model which are;


institution levels
FIGURE 126 Finance Business Model
4.6. NON-FORMAL BUSINESS MODEL
Non-formal business model covers course, student and staff Statistics in non-formal
education. For the vehicle courses (MTSC) attendies and certificates ststaitics will be
available. Course, students and staff Statistics comes from e-nonformal system.
FIGURE 127 Non-Formal Business Model
Section E. USER MANUEL FOR USAGE OF THE BI
DASHBOARD
1.1. GENERAL USAGE OF DASHBOARD
Login Operations : In order to login to the MONESTAT BI application; the following URL
should be typed via Microsoft Internet Explorer or Mozilla Firefox browsers.
mebistatistik.meb.gov.tr/analytics
The login page demonstrated below will be displayed, and the username, password and
language information should be entered in order to complete the login operation.
FIGURE 128 - Login Page
Dashboards : A dashboard in Oracle BI terminology refers to meaningful groups of related
analyses that are put together and presented to users. The appropriate dashboards for the
user can be reached from the top-down menu. The dashboard access sub menu is displayed
below.
FIGURE 129 Dashboard Wellcome Page
Each dashboard has one or generally more dashboard tab pages. Usually in each tab page,
there are command prompts which are used to pass parameters to analyses and the analyses
results in different views.
Dashboard prompts are responsible for helping the users to enter parameters that meet with
their requirements. The command prompt elements should be in different forms, but the mostly
used ones in our applications were the list boxes and the check boxes. Some list boxes permit
the selection of more than one option, whereas the others force the user to decide on one
selection. The “Apply” button is used in order to trigger the execution of an analysis and the
“Reset” button is used for clearing all parameters.
FIGURE 130 Dashboard Prompt Sample
The most popular analyses result views are the standard tables, pivot tables and graphic
charts. In the following example, a command prompt with various parameters and the
analyses results in pivot table and chart views are demonstrated.
FIGURE 131 Sample Dashboard Page
Some analyses include hierarchical columns which gives the users the opportunity to drilldown and roll-up between levels of the concept hierarchies. For example, the figures below
show an analyses employing AN hierarchical column. In order to drill down to details of the
selected region (“expand”), level the (+) sign should be ticked and in order to roll up to a
summary (“collapse”) the (-) sign should be used.
FIGURE 132 Sample Dashboard Page For DrillDown
FIGURE 133 Sample Dashboard Page For Rollup
The arrow signs near data labels in pivot tables can be used to change the order of the rows
and/or columns in ascending or descending order.
FIGURE 134 Sample Dashboard Page For Ordering
1.2. DESIGNED DASHBOARD PAGES
1.2.1. INSTITUTIONS DASHBOARD
1.2.1.1.
THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP TYPES IN
LOCATION HIERARCHY
FIGURE 135 Dashboard Report - THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP
TYPES IN LOCATION HIERARCHY
Parameters :
Date of the data : The validity date(s) of the institutions data.
General Directorate : The General Directorate(s) that are to be in the scope of the analysis.
Institution Type : The Institution Type(s) to be included in the analysis.
Ownership type : The ownership types such as MoNE, other ministries, municipality, private
etc.
Rental situation: The data about the fact that whether any rent is paid or not.
Heating style : Refers to difference styles of heating such as central heating, stove or combi
boiler etc.
Fuel Type : Refers to different fuel types, such as natural gas, fuel-oil or coal.
Educational institution/administrative institution: The choice of institution type on the basis of
its primary purpose.
Formal/Non-formal Selection : The choice of institution type due to its giving a formal
education or a non-formal education.
Public/Private/Open discrimination: The choice of institution type due to its being a public,
private or an open organization.
Level of education : The scope of the report due to pre-defined education levels, such as PrePrimary, Primary, Secondary and Mass Education.
Domestic/Foreign : The choice about the scope of the report to cover the institutions located in
Turkey, located abroad or both.
Location of Residence: The location of residence for the institution, such as village, town or
city center.
Open/Close Status of the Institution : The open, close or transferred status of the institution.
This parameter is mandatory parameter, must be selected before running the report.
Measures: Number of Institutions, Number of Buildings
Report Coverage : The number of institutions and number of buildings can be queried by
choosing relevant parameters. Only institutions whose building information have to be entered
in the data collection system, can be queried. The number of buildings and institutions can be
different, as some of the institutions have more than one building with different ownerships.
Usage :
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After the selection of the parameters and starting the analysis execution by pressing
“Apply” button; the results can be achieved.
The hierarchical column for locations can be used in order to accomplish drill down and
roll-up operations between different concept hierarchy levels.
The ordering opportunities can be used in order to sort the rows and columns in
ascending or descending orders.
Multiple dates can be selected in order to make comparisons.
The user can print the analysis and has opportunity to transfer the data to Excel,
Powerpoint platforms or PDF, XML, CSV file formats.
1.2.1.2.
THE NUMBER OF INSTITUTIONS DUE TO THEIR MAIN TYPE / SUB TYPE
STATUS AND CURRENT SITUATIONS IN LOCATION HIERARCHY
FIGURE 136 Dashboard Report -THE NUMBER OF INSTITUTIONS DUE TO THEIR MAIN TYPE / SUB
TYPE STATUS AND CURRENT SITUATIONS IN LOCATION HIERARCHY
Parameters :
Main Type / Sub Type : The parameter that determines the scope of the analysis in a main
type/sub type basis.
General / Vocational : The choice of the institution type on a basis for its being general or
vocational.
city center
Measures: Number of Institutions
Report Coverage : The number of institutions have to be queried with status of the institution
('Open','Close','Transferred') and NUTS levels.
Usage :
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The analysis does not contain a hierarchical column for drill down and roll-up
operations but these transitions can be done by using navigation links.
1.2.1.3.
THE NUMBER OF INSTITUTIONS WITH RESPECT TO INSTITUTION TYPES
WITH THE SELECTION FOR PROVINCES & DISTRICTS
FIGURE 137 Dashboard Report -THE NUMBER OF INSTITUTIONS WITH RESPECT TO INSTITUTION
TYPES WITH THE SELECTION FOR PROVINCES &DISTRICTS
Parameters :
Province : The province(s) that will be included in the scope of the study.
District : The district(s) that will be included in the scope of the study.
vocational.
city center.
Report Coverage : The number of institutions can be queried by choosing relevant
parameters in selected province and district with related general directorate and institution
type. At least one province have to be chose before query. If the only 'Main Type' parameter is
choosed, only the number of institutions which have main type will be queried , this means
user can not see other sub-types of the same school. By selecting both main and subtypes,
user can query every institutions type in this report.
Usage :
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The result is given in a province/district hierarchy and by using navigation links the user
can drill-down to institution details.
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1.2.1.4.
THE NUMBER OF INSTITUTIONS IN INSTITUTION TYPE HIERARCHY
FIGURE 138 Dashboard Report -THE NUMBER OF INSTITUTIONS IN INSTITUTION TYPE
HIERARCHY
Parameters :
vocational.
city center
parameters in institution type hierarchy.
Usage :
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The analysis employs a hierarchical column for the organization type hierarchy. By
using expand and collapse options the user can drill-down or roll-up between the
different levels.
1.2.1.5.
THE NUMBER OF PUBLIC/PRIVATE/OPEN INSTITUTIONS WITH LOCATION
HIERARCHY, NORMAL/TWO BASED EDUCATION
FIGURE 139 Dashboard Report - THE NUMBER OF PUBLIC/PRIVATE/OPEN INSTITUTIONS WITH
LOCATION HIERARCHY, NORMAL/TWO BASED EDUCATION
Parameters :
vocational.
city center.
parameters in location hierarchy and education type (normal education, two-based education).
Usage :
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The analysis employs a hierarchical column for the organization type hierarchy. By
using expand and collapse options the user can drill-down or roll-up between the
different levels.
1.2.1.6.
THE NUMBER OF INSTITUTIONS DUE TO THEIR ENTRANCE TO SERVICE
YEARS
FIGURE 140 Dashboard Report -THE NUMBER OF INSTITUTIONS DUE TO THEIR ENTRANCE TO
SERVICE YEARS
Parameters :
vocational.
city center
parameters with service entry year groups.
Usage :
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The result is given in a public/private discrimination and by using navigation links the
user can drill-down to the details for institution type hierarchy.
By the clicking on the time period in column titles, the user can reach the opening year
knowledge for institutions.
1.2.1.7.
THE NUMBER OF INSTITUTIONS WHICH HAVE A PREPARATORY CLASS
FIGURE 141 Dashboard Report -THE NUMBER OF INSTITUTIONS WHICH HAVE A PREPARATORY
CLASS
Parameters :
vocational.
city center
Report Coverage : The number of institutions which have pre-primary classes inside the
institution can be queried by choosing relevant parameters.
Usage :
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The result is given in a NUTS hierarchy and by using navigation links the user can drilldown to the details.
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The chart on the right side demonstrates the distribution of the institutions having
preparatory classes w.r.t. NUTS 1 regions.
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1.2.1.8.
THE NUMBER OF INSTITUTIONS WITH SELECTED PROVINCE AND DISTRICT
LEVEL
FIGURE 142 Dashboard Report - THE NUMBER OF INSTITUTIONS WITH SELECTED PROVINCE
AND DISTRICT LEVEL
Parameters :
Province : The province(s) that will be included in the scope of the study. This is a mandatory
parameter that must be selected by the user.
District : The district(s) that will be included in the scope of the study. This is a mandatory
parameter that must be selected by the user.
vocational.
city center
Report Coverage : The list of institutions can be queried by choosing relevant parameters
with district, institution code and institution name attributes.
Usage :
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The result is given in a district, institution code and institution name list.
Multiple districts can be selected in order to make comparisons.
1.2.1.9.
THE NUMBER OF CLOSED INSTITUTIONS WITH CLOSURE REASONS
FIGURE 143 Dashboard Report - THE NUMBER OF CLOSED INSTITUTIONS WITH CLOSURE
REASONS
Parameters :
vocational.
city center
Closure Reason of the Institution : The closure reason of the institution.
Measures: Number of Closed Institutions
Report Coverage : The list of institutions can be queried by choosing relevant parameters.
Usage :
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1.2.2. INSTITUTIONS ADDITIONAL INFORMATIONS DASHBOARD
1.2.2.1.
THE NUMBER OF INSTITUTIONS &CLASSROOMS IN NUTS LEVEL 2
FIGURE 144 Dashboard Report- THE NUMBER OF INSTITUTIONS &CLASSROOMS IN NUTS
LEVEL 2
Parameters :
Usage Areas : The usage area(s), such as classrooms, laboratories, ateliers etc. to be
included in the analysis.
vocational.
city center.
Measures: Number of Institutions, Number of Usage Areas
Report Coverage : The number of institutions and number of usage areas can be queried by
choosing relevant parameters in NUTS Level 2 and types of usage areas like classroom,
laboratory, manager room etc.
Usage :
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The result is given in a NUTS hierarchy and by using navigation links the user can drilldown to details.
For the usage area user can chose 'Classrooms' and query number of institutions and
classrooms.
1.2.2.2.
THE NUMBER OF INSTITUTIONS & USAGE AREAS IN NUTS HIERARCHY
FIGURE 145 Dashboard Report-THE NUMBER OF INSTITUTIONS & USAGE AREAS IN NUTS
HIERARCHY
Parameters :
Usage Areas : The usage area(s), such as classrooms, laboratories, ateliers etc. to be
included in the analysis.
vocational.
city center.
Measures: Number of Institutions, Number of Usage Areas
Report Coverage : The number of institutions and number of usage areas can be queried by
choosing relevant parameters in NUTS hierarchies and types of usage areas like classroom,
laboratory, manager room etc.
Usage :
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The result is given in a NUTS hierarchy and by using navigation links the user can drilldown to details.
1.2.2.3.
THE NUMBER OF PUBLIC HOUSES IN INSTITUTION TYPE HIERARCHY
FIGURE 146 Dashboard Report -THE NUMBER OF PUBLIC HOUSES IN INSTITUTION TYPE
HIERARCHY
Parameters :
vocational.
city center.
Measures: Number of Public Houses (with different heating status)
Report Coverage : The number of public houses can be queried by choosing relevant
parameters in NUTS levels.
Usage :
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1.2.2.4.
THE NUMBER OF PENSIONS IN INSTITUTION TYPE HIERARCHY
FIGURE 147 Dashboard Report -THE NUMBER OF PENSIONS IN INSTITUTION TYPE HIERARCHY
Parameters :
vocational.
city center.
Measures: Boys Capacity, Girls Capacity, Total Capacity
Report Coverage : The capacity of pensions can be queried by choosing relevant
parameters. For public institutions pension data, end user can query capacity information both
in boys and girls separately. But for private institutions pension data only total capacity can be
queried, as the data is not available in data collection system.
Usage :
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The result is given in a institution type hierarchy and by using navigation links the user
can drill-down to the details.
The capacities of private institutions cannot be decomposed in a gender basis due to
lack of data.
1.2.2.5.
THE BUILDING AND GARDEN AREAS IN LOCATION HIERARCHY
FIGURE 148 Dashboard Report-THE BUILDING AND GARDEN AREAS IN LOCATION HIERARCHY
Parameters :
vocational.
city center.
Measures: Number of Institutions, Average Number of Building Area, Average Number of
Garden Area
Report Coverage : The number of institutions, average number of building area and average
number of garden area can be queried by choosing relevant parameters. The building and
garden area have to be taken from building information. For this reason, only institutions
whose building information have to be entered in the data collection system, can be shown as
greater than '0' value in area measures. If one institution have more than one building, the sum
of each building area have to be given as institutions building area. For the averages, total
area value divided by total institution value.
Usage :
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1.2.2.6.
THE NUMBER OF LIBRARY MATERIALS IN LOCATION OF RESIDENCE
HIERARCHY
FIGURE 149 Dashboard Report -THE NUMBER OF LIBRARY MATERIALS IN LOCATION OF
RESIDENCE HIERARCHY
Parameters :
Material Type : The library material type(s) to be included in the analysis.
vocational.
city center.
Measures: Number of Last Years Amount, Number of New Materials Entered in The Current
Year, Number of Materials Which Exiting in The Current Year, Number of Current Materials
Report Coverage : The number of library materials can be queried by choosing relevant
parameters in material types and NUTS levels.
Usage :
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1.2.2.7.
THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP TYPES IN
LOCATION HIERARCHY
FIGURE 150 Dashboard Report - THE NUMBER OF INSTITUTIONS DUE TO THEIR OWNERSHIP
TYPES IN LOCATION HIERARCHY
Parameters :
Ownership type : The ownership types such as MoNE, other ministries, municipality, private
etc.
Rental situation: The data about the fact that whether any rent is paid or not.
Heating style : Refers to difference styles of heating such as central heating, stove or combi
boiler etc.
Fuel Type : Refers to different fuel types, such as natural gas, fuel-oil or coal.
city center.
Measures: Number of Institutions, Number of Buildings
Report Coverage : The number of institutions and number of buildings can be queried by
choosing relevant parameters. Only institutions whose building information have to be entered
in the data collection system, can be queried. The number of buildings and institutions can be
different, as some of the institutions have more than one building with different ownerships.
Usage :
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1.2.3. FORMAL EDUCATION DASHBOARD
1.2.3.1.
THE NUMBER OF STUDENTS IN INSTITUTION TYPE HIERARCHY
FIGURE 151 Dashboard Report -THE NUMBER OF STUDENTS IN INSTITUTION TYPE HIERARCHY
Parameters :
Date of the data : The validity date(s) of the beginning of the year data of students.
Semester : The semester(s) to be included in the report.
Sex : The gender(s) to be included in the scope of the analysis.
city center
Province : The province(s) to be included in the analysis.
District : The district(s) to be included in the analysis.
Class Level : The selection of class level(s) to be included in the analysis.
Measures: Number of Enrolled Students, Number of Repeaters, Number of Passed Students
and Number of Passed Students with Teacher’s Council’s Decision
Report Coverage : The number of students are queried by choosing relevant parameters.
The results are enlisted by means of the institution type hierarchy. The number of students are
grouped in a gender basis and their pass-fail statuses for the previous year.
Usage :
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The result is given in a institution type hierarchy and by using navigation links the user
can drill-down to the details.
A bar-chart is provided in order to demonstrate the changes for each pass-fail status.
A general total is supplied for each attribute within the analysis.
1.2.3.2.
THE NUMBER OF STUDENTS IN LOCATION HIERARCHY FOR FORMAL
EDUCATION BY MEANS OF LOCATION OF RESIDENCE, SEX AND
OWNERSHIP OF INSTITUTION
FIGURE 152 Dashboard Report -THE NUMBER OF STUDENTS IN LOCATION HIERARCHY FOR
FORMAL EDUCATION BY MEANS OF LOCATION OF RESIDENCE, SEX AND OWNERSHIP OF
INSTITUTION
Parameters :
Date of the data : The validity date(s) of the end of the year data of students.
Level of education : The scope of the report due to pre-defined education levels, such as PrePrimary, Primary, Upper-Secondary Education.
city center
Measures: Number of Registered Students, Number of Repeaters, Number of Passed
Students and Number of Passed Students with Teacher’s Council’s Decision, Graduated
Students
Report Coverage : The number of students are queried by choosing relevant parameters.
The results are enlisted by means of the NUTS hierarchy. The number of students are
grouped in a gender basis, residence of location, ownership and their pass-fail statuses for the
current year.
Usage :
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The result is given by means of a NUTS hierarchy and the “expand” and “collapse”
opportunities of the hierarchical column can be used to drill-down to the details or rollup to the summaries.
1.2.3.3.
THE NUMBER OF STUDENTS BY MEANS OF LOCATION OF RESIDENCE, SEX
AND SEMESTERS
FIGURE 153 Dashboard Report - NUMBER OF STUDENTS BY MEANS OF LOCATION OF
RESIDENCE, SEX AND SEMESTERS
Parameters :
city center
Measures: Number of Enrolled Students, Number of New Entrants, Number of Repeaters and
Graduated Students
Report Coverage : The number of enrolled, new entrant, graduated and repeater students are
queried by choosing relevant parameters. The results are enlisted by means of the semesters.
The change of the numbers can be observed by the pivot table as well as the bar chart.
Usage :
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Multiple dates and semesters can be selected in order to make comparisons.
1.2.3.4.
THE NUMBER OF ENROLLED STUDENTS FOR WITH RESPECT TO LOCATION
OF RESIDENCE AND SEX BY MEANS OF NUTS3 CLASSIFICATION
FIGURE 154 Dashboard Report - THE NUMBER OF ENROLLED STUDENTS FOR WITH RESPECT
TO. LOCATION OF RESIDENCE AND SEX BY MEANS OF NUTS3 CLASSIFICATION
Parameters :
city center
Measures: Number of Enrolled Students
Report Coverage : The number of enrolled students are queried by choosing relevant
parameters. The results are enlisted by means of NUTS3 (Province) hierarchy. The measure
is grouped with respect to the year of born.
Usage :
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The number of enrolled students are grouped with respect to the years of born of the
students.
The district detail for the analysis can be achieved by using the navigation link on
province data; and the detail for the institutions may be reached by clicking on the
navigation link upon district label.
1.2.3.5.
THE GENDER EQUALITY INDEX
FIGURE 155 Dashboard Report - THE GENDER EQUALITY INDEX
Parameters :
city center
Report Coverage : The ratio of enrolled female students with respect to enrolled male
students is named as “Gender Equality Index” The results are enlisted by means of NUTS
hierarchy.
Usage :
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The results are listed by using the hierarchical column based on NUTS hierarchy and
“expand” and “collapse” options can be used in order to drill down or rollup among the
different levels of hierarchy.
The equality index for each NUTS region is demonstrated in a line chart.
1.2.3.6.
THE PERCENTAGE OF ENROLLMENT IN PRIVATE INSTITUTIONS
FIGURE 156 Dashboard Report - THE PERCENTAGE OF ENROLLMENT IN PRIVATE INSTITUTIONS
Parameters :
city center
Report Coverage : The ratio of enrolled students to private institutions with respect to all
enrolled students is named as “Percentage of Enrollment in Private Institutions”. The results
are enlisted by means of NUTS hierarchy.
Usage :
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1.2.3.7.
THE PERCENTAGE OF REPEATERS (ACCORDING TO THE DATA OF BEGINNING OF
THE EDUCATION YEAR)
FIGURE 157 Dashboard Report - THE PERCENTAGE OF REPEATERS (According to the Data of
Beginning of the Education Year)
Parameters :
city center
Measures: Number of Enrolled Students, Number of Repeaters, Percentage of Repeaters
Report Coverage : The percentage of repeater students with respect to all enrolled students
is by means of gender information are enlisted by means of NUTS hierarchy. The analyses is
derived from the data of the beginning of the education year.
Usage :
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The selection of the parameters is made by using related dashboard prompt and the
analysis execution can be started by pressing “Apply” button.
1.2.3.8.
THE PERCENTAGE OF REPEATERS (ACCORDING TO THE DATA OF END OF THE
EDUCATION YEAR)
FIGURE 158 Dashboard Report - THE PERCENTAGE OF REPEATERS (According to the Data of
End of the Education Year)
Parameters :
city center
Measures: Number of Enrolled Students, Number of Repeaters, Percentage of Repeaters
Report Coverage : The percentage of repeater students with respect to all enrolled students
is by means of gender information are enlisted by means of NUTS hierarchy. The analyses is
derived from the data of the end of the education year.
Usage :
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1.2.3.9.
THE REPEAT RATIO
FIGURE 159 Dashboard Report - THE REPEAT RATIO
Parameters :
city center
Measures: Number of Enrolled Students, Number of Repeaters At the End of The Semester,
Repeat Ratio
Report Coverage : The ratios of repeater students with respect to all enrolled students is by
means of gender information are enlisted by means of NUTS hierarchy. The analyses is
derived from the data of the end of the education year.
Usage :
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1.2.3.10.
THE NUMBER OF PASSIVE STUDENTS BY CAUSES AND SEMESTERS IN
LOCATION HIERARCHY
FIGURE 160Dashboard Report - THE NUMBER OF PASSIVE STUDENTS BY CAUSES AND
SEMESTERS IN LOCATION HIERARCHY
Parameters :
Date of the data : The validity date(s) of the data about passive students.
city center
Cause of Passiveness : The reason(s) of passiveness to be regarded in the analysis.
Measures: Number of Passive Students
Report Coverage : The numbers of passive students are listed with respect to passive
reasons, semesters and location hierarchy.
Usage :
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1.2.3.11.
THE NUMBER OF PASSIVE STUDENTS BY CAUSES, OWNERSHIP AND SEX
FIGURE 161 Dashboard Report - THE NUMBER OF PASSIVE STUDENTS BY CAUSES,
OWNERSHIP AND SEX
Parameters :
Date of the data : The validity date(s) of the data about passive students.
city center
Cause of Passiveness : The reason(s) of passiveness to be regarded in the analysis.
Measures: Number of Passive Students
Report Coverage : The numbers of passive students are listed with respect to causes of
passiveness, semesters, ownership of institution and sex.
Usage :
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1.2.3.12.
THE PASS-FAIL STATUSES OF THE STUDENTS BY THE END OF SEMESTERS
WITH RESPECT TO LOCATIONS OF RESIDENCE
FIGURE 162 Dashboard Report - THE PASS-FAIL STATUSES OF THE STUDENTS BY THE END OF
SEMESTERS WITH RESPECT TO LOCATIONS OF RESIDENCE
Parameters :
Date of the data : The validity date(s) of the data about students produced at the end of the
education year.
city center
Measures: Number of Enrolled Students, Number of Graduates, Number of Repeaters,
Number of Passed Students, Number of Passed Students by Teachers Council’s Decision.
Report Coverage : The numbers of students are listed by means of semesters and their
pass/fail statuses. The results are grouped with respect to ownership of the institutions.
Usage :
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A bar chart is introduced in order to make comparison with enrolled and graduated
number of students with respect to semesters.
1.2.3.13.
THE NUMBER OF STUDENTS BY CLASS LEVELS, LOCATIONS OF
RESIDENCE AND PUBLIC/PRIVATE INSTITUTION
FIGURE 163 Dashboard Report - THE THE NUMBER OF STUDENTS BY CLASS LEVELS,
LOCATIONS OF RESIDENCE AND PUBLIC/PRIVATE INSTITUTION
Parameters :
education year.
Level of education : The scope of the report due to pre-defined education levels, such as PrePrimary, Primary, Upper Secondary Education.
city center
Measures: Number of Enrolled Students, Number of New Entrants, Number of Graduates,
Number of Repeaters, Number of Passed Students, Number of Passed Students by Teachers
Council’s Decision.
Report Coverage : The numbers of students are listed by means of class levels,
public/private institution type and gender. The results are grouped with respect to residence of
location and sex.
Usage :
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1.2.3.14.
THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL BY GENDER IN
NUTS HIERARCHY
FIGURE 164 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL BY
GENDER IN NUTS HIERARCHY
Parameters :
Date of the data : The validity date(s) of the data about open primary school students.
Education Year : The education year(s) to be included in the report.
Measures: Number of Active Students, Number of New Entrants, Number of Graduate
Students, Number of Continuous Students
Report Coverage : The numbers of active students in selected education year of open
primary school are listed by means of their gender in a NUTS hierarchy. The number of
students in foreign countries are listed in an other query table in the same dashboard report.
The source table for the open primary school is prepared by only getting active students in one
of the semester in the education year. The data can be valid education year basis.
Usage :
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“Apply” button; the all results can be achieved.
1.2.3.15.
THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL WITH EXAM
CENTERS
FIGURE 165Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL WITH
EXAM CENTERS (Students located in Turkey)
FIGURE 166 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL WITH
EXAM CENTERS (Students located abroad)
Parameters :
Date of the data : The validity date(s) of the data about open primary school students.
Measures: Number of Active Students, Number of New Entrants, Number of Graduate
Students, Number of Continuous Students
Report Coverage : The numbers of active students in selected education year of open
primary school are listed by means of NUTS hierarchy. The number of students in foreign
countries are listed in an other query table in the same dashboard report. The source table for
the open primary school is prepared by only getting active students in one of the semester in
the education year. The data can be valid education year basis.
Usage :
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The students in Turkey and that are abroad are listed in two different analyses placed
in same dashboard. While NUTS hierarchy is used for students in Turkey; the
countries are used as a grouping factor for students that are abroad.
1.2.3.16.
THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL BY GENDER IN NUTS
HIERARCHY
FIGURE 167 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL BY
GENDER IN NUTS HIERARCHY
Parameters :
Date of the data : The validity date(s) of the data about open high school students.
Measures: Number of Active Students, Number of New Entrants, Number of Re-entrants,
Number of Graduate Students, Number of Continuous Students
Report Coverage : The numbers of active students in selected education year of open high
school are listed by means of their gender in a NUTS hierarchy. The number of students in
foreign countries are listed in an other query table in the same dashboard report. The source
table for the open high school is prepared by only getting active students in one of the
semester in the education year. The data can be valid for education year basis.
Usage :
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1.2.3.17.
THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL WITH EXAM CENTERS
FIGURE 168Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL WITH
EXAM CENTERS (Students located in Turkey)
FIGURE 169 Dashboard Report - THE NUMBER OF STUDENTS IN OPEN HIGH SCHOOL WITH
EXAM CENTERS (Students located abroad)
Parameters :
Date of the data : The validity date(s) of the data about open high school students.
Measures: Number of Active Students, Number of New Entrants, Number of Re-entrants ,
Number of Graduate Students, Number of Continuous Students
Report Coverage : The numbers of active students in selected education year of open high
school are listed by means of NUTS hierarchy. The number of students in foreign countries
are listed in an other query table in the same dashboard report. The source table for the open
primary school is prepared by only getting active students in one of the semester in the
education year. The data can be valid for education year basis.
Usage :
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The students in Turkey and that are abroad are listed in two different analyses placed
in same dashboard. While NUTS hierarchy is used for students in Turkey; the
countries are used as a grouping factor for students that are abroad.
1.2.3.18.
SUMMER KINDERGARTENS, MOBILE CLASSES & KINDERGARTENS OF
OTHER INSTITUTIONS
FIGURE 170 Dashboard Report - SUMMER KINDERGARTENS, MOBILE CLASSES &
KINDERGARTENS OF OTHER INSTITUTIONS
Parameters :
Date of the data : The validity date(s) of the data about the kindergartens
city center
Organization Type: Other Institutions, Mobile Classes, SHCEK, Summer Kindergartens
Measures: Number of Students, Number of Institutions, Number of Sections, Number of
Classrooms
Report Coverage : The numbers of students, institutions, classrooms and sections of the
kindergartens in a NUTS hierarchy. The source data comes from MEIS system, and for
SHCEK the data was converted from external Excel files.
Usage :
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The number of students are grouped by the students’ ages.
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1.2.3.19.
PRE-PRIMARY STUDENTS STATİSTİCS
FIGURE 171 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Indepandant Pre-Primary
Schools)
FIGURE 172 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Pre-Primary Students in
Primary Schools)
FIGURE 173 Dashboard Report - PRE-PRIMARY STUDENTS STATİSTİCS (Pre-Primary Students in
Upper-Secondary Schools)
Parameters :
education year.
city center
Measures: Number of Pre-Primary Students
Report Coverage : The numbers of pre-primary level of students in a NUTS hierarchy is
queried in this report. Report contains different three types of data table. First one covers preprimary students in independent pre-primary schools. Second data table covers pre-primary
classes in primary schools. Third data table covers pre-primary classes in upper-secondary
schools.
Usage :






The number of students are grouped by the Public/Private/Open discrimination.
1.2.3.20.
PROVINCE BASED PRE-PRIMARY STUDENTS STATİSTİCS
FIGURE 174 Dashboard Report - PROVINCE BASED PRE-PRIMARY STUDENTS STATİSTİCS
Parameters :
education year.
Province : The province(s) to be included in the analysis. This parameter must be choosen
before running the report.
city center
Measures: Number of Pre-Primary Students
Report Coverage : The numbers of pre-primary level of students is listed for district, general
directorate, institution type, institution code and name.
Usage :






The number of students are grouped by all schools.
1.2.3.21.
DISABLED STUDENTS WITH OBSTACLE GROUPS
FIGURE 175 Dashboard Report - DISABLED STUDENTS WITH OBSTACLE GROUPS (First Data Table)
FIGURE 176 Dashboard Report - DISABLED STUDENTS WITH OBSTACLE GROUPS (Second Data Table
With Obstacle Groups)
Parameters :
Date of the data : The validity date(s) of the data about disabled students.
city center
Obstacle Group : The selection of obstacle group(s) to be included in the analysis
Service Group : The selection of service group(s) to be included in the analysis
Measures: Number of Disabled Students, Number of Obstacles
Report Coverage : The numbers of disabled students is listed in NUTS hierarchy grouped by
birth year and gender. Report contains two different data table. First table covers number of
disabled students and number of obstacles within NUTS hierarchy. Second table covers
number of disabled students with NUTS hierarchy and obstacle groups.
Usage :






The number of students are grouped by NUTS hierarchy.
1.2.3.22.
DISABLED STUDENTS WITH SERVICE GROUPS
FIGURE 177 Dashboard Report - DISABLED STUDENTS WITH SERVICE GROUPS
Parameters :
Date of the data : The validity date(s) of the data about disabled students
city center
Report Coverage : The numbers of disabled students is listed in NUTS hierarchy grouped by
birth year and gender for each service group.
Usage :







The number of students are grouped by NUTS hierarchy.
The service groups are listed in a list item at the beginning of the data table. User can
reach the different service groups data by choosing an item from the list.
1.2.3.23.
DISABLED STUDENTS IN SPECIAL CLASSES IN GENERAL SCHOOLS
FIGURE 178 Dashboard Report - DISABLED STUDENTS IN SPECIAL CLASSES IN GENERAL SCHOOLS
Parameters :
city center
Report Coverage : The numbers of disabled students in special classes within the schools
are listed in school types and classes grouped by gender.
Usage :






The results are listed by using the school types. Drill down options can be used in
school type attribute for reaching specific institution.
The number of students are grouped by classes and gender.
1.2.3.24.
NUMBER OF STUDENTS WITH PROVINCE, DISTRICT, NORMAL/TWO BASED
EDUCATION
FIGURE 179 Dashboard Report - NUMBER OF STUDENTS WITH PROVINCE, DISTRICT, NORMAL/TWO
BASED EDUCATION
Parameters :
city center
Measures: Number of Students
Report Coverage : The numbers of students are grouped by gender with the selected
parameters. The data covers in the beginning of the education semester. The list contains
province, district, general directorate, institution type, institution code, institution name,
location, normal/two based education attributes.
Usage :




The results are listed with province, district, general directorate, institution type,
institution code, institution name, location, normal/two based education attributes.
1.2.3.25.
NUMBER
OF
DIVISIONS
WITH
PROVINCE
AND
CLASS
LEVELS
FIGURE 180 Dashboard Report - NUMBER OF DIVISIONS WITH PROVINCE AND CLASS LEVELS
Parameters :
city center.
Measures: Number of Divisions
Report Coverage : The numbers of divisions are grouped by province, district and class level
with the selected parameters.
Usage :




The results are listed with province, district and class levels .
1.2.3.26.
NUMBER OF STUDENTS WHOSE RELATION WITH SCHOOL IS CANCELED
FIGURE 181 Dashboard Report - NUMBER OF STUDENTS WHOSE RELATION WITH SCHOOL IS
CANCELED
Parameters :
city center.
Measures: Number of Students
Report Coverage : The numbers of students whose considered as drop-outs are grouped by
NUTS levels with the selected parameters.
Usage :








The results are listed with NUTS levels .
There are two different table for primary and upper-secondary education levels.
The user can reach the same data in the pie chart under the data tables.
For primary education level, the code '32' in student status table is queried.
For upper-secondary education level, the codes in '49,50,51' in student status table is
queried.
The students status codes are changed by education level, so for the purpose of the
analysis, two different data table have to be developed.
1.2.4. SCHOOLARSHIP,
DASHBOARD
1.2.4.1.
BOARDING
STUDENTS
AND
PRIVATE
DORMITORIES
THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS
FIGURE 182 Dashboard Report - THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS
Parameters :
private or an open institution.
city center
Measures: Number of Scholar Students
Report Coverage : The number of scholar students are queried by choosing relevant
parameters. The results are enlisted by means of the responsible departments.
Usage :


By using navigation opportunities, the user can drill down to institution types and
institutions.


A bar-chart is provided in order to demonstrate the situations of each department.


A general total is supplied for each kind of pass-fail statuses.

1.2.4.2.
THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS AND
GENDER
FIGURE 183 Dashboard Report - THE NUMBER OF SCHOLAR STUDENTS DUE TO DEPARTMENTS
AND GENDER
Parameters :
city center
Measures: Number of Scholar Students
Report Coverage : The number of scholar students are queried by choosing relevant
parameters. The results are enlisted by means of the departments that cover their institutions
and their genders.
Usage :


institutions.


The reports data is grouped by department and gender.

A bar-chart is provided in order to demonstrate the situations of each department.


A general total is supplied for each kind of measures.

1.2.4.3.
THE SCHOLARSHIP AMOUNTS DUE TO PROVINCES AND DISTRICTS
FIGURE 184 - THE SCHOLARSHIP AMOUNTS DUE TO PROVINCES AND DISTRICTS
Parameters :
city center
Measures: Amount of Scholarships paid to students
Report Coverage : The amount of scholarships are queried by choosing relevant parameters.
The results are enlisted by means of the provinces and counties of the institutions of the
scholar students.
Usage :


institutions.



A general total and subtotals are supplied for the amount of paid scholarships.

1.2.4.4.
THE DOMESTIC SCHOLARSHIP RATES
FIGURE 185 Dashboard Report - THE DOMESTIC SCHOLARSHIP RATES Parameters :
Measures: Scholarship Indicator, Officer Payroll Coefficient and Monthly Amount of
Scholarship.
Report Coverage : The rates for scholarships are queried by choosing relevant parameters.
The results are enlisted by means of the semesters.
Usage :



Multiple semesters can be selected in order to make comparisons.

A bar-chart that demonstrates the differences of the rates due to semesters is included
in the analysis.

1.2.4.5.
THE NUMBER OF BOARDING STUDENTS DUE TO DEPARTMENTS, GENDER
AND PAYMENT SITUATIONS
FIGURE 186 Dashboard Report - THE NUMBER OF BOARDING STUDENTS DUE TO DEPARTMENTS, GENDER
AND PAYMENT SITUATIONS
Parameters :
city center
Measures: Number of Paid/Non-Paid Boarding Students.
Report Coverage : The number of paid and non-paid boarding students are queried by
choosing relevant parameters. The results are enlisted by means of the departments that
govern the institutions of the students.
Usage :


institutions.



A general total is supplied for each kind of payment statuses and genders.

1.2.4.6.
THE NUMBER OF BOARDING STUDENTS DUE TO NUTS-3 CLASSIFICATION
AND GENDER
FIGURE 187 Dashboard Report - THE NUMBER OF BOARDING STUDENTS DUE TO NUTS-3
CLASSIFICATION AND GENDER
Parameters :
city center
Measures: Number of Boarding Students.
Report Coverage : The number of boarding students are queried by choosing relevant
parameters. The results are enlisted by means of the NUTS-3 Classification and gender.
Usage :


By using navigation opportunities, the user can drill down to county level information.



A general total is supplied for each kind of genders.

1.2.4.7.
THE NUMBER OF BOARDING STUDENTS DUE TO INSTITUTION WHERE THEY
BENEFIT FROM
FIGURE 188 Dashboard Report - THE NUMBER OF BOARDING STUDENTS DUE TO INSTITUTION WHERE
THEY BENEFIT FROM
Parameters :
city center
Measures: Number of Boarding Students.
Report Coverage : The number of boarding students are queried by choosing relevant
parameters. The results are enlisted by means of the NUTS Classification of institutions where
students are benefit from.
Usage :


By using navigation opportunities, the user can drill down to county level information.



A general total is supplied for each kind of genders.

1.2.4.8.
THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR STATUES
FIGURE 189 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR
STATUES
Parameters :
Date of the data : The validity date(s) of the private dormitories subject area.
Payment Type: The payment situation of the dormitory as free of charge or charged.
Education Level: The Education Level(s) that are in the scope of the dormitory.
Meal Situation: The attribute that defines the situation of the dormitory in a dining/non-dining
fashion.
Type of Residence : The type of residence as being in the province center, county center or a
village.
Dormitory Situation : The attributes that defines the dormitory as Open, Closed and
Temporarily Closed.
Measures: Number of Private Dormitories
Report Coverage : The number of private dormitories are queried by choosing relevant
parameters. The results are enlisted by means of the situations of the dormitories.
Usage :




1.2.4.9.
THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR PLACE OF
RESIDENCE TYPES
FIGURE 190 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES DUE TO THEIR PLACE
OF RESIDENCE TYPES
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories
Report Coverage : The number of private dormitories are queried by choosing relevant
parameters. The results are enlisted by means of types of residences of the dormitories.
Usage :



A bar-chart is given in order to demonstrate the differences by means of residence
place types.


1.2.4.10.
THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES AND THE
NUMBER OF RESIDENT STUDENTS DUE TO OWNERSHIP TYPES
FIGURE 191 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES
AND THE NUMBER OF RESIDENT STUDENTS DUE TO OWNERSHIP TYPES
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories, Number of Students located in private dormitories,
Bed Capacity of the private dormitories.
Report Coverage : The number of private dormitories, the bed capacities and the number of
students located in these dormitories are queried by choosing relevant parameters. The
results are enlisted by means of ownership types of the dormitories.
Usage :




1.2.4.11.
THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES AND THE
NUMBER OF RESIDENT STUDENTS DUE TO NUTS3 CLASSIFICATION
FIGURE 192 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES, THE BED CAPACITIES
AND THE NUMBER OF RESIDENT STUDENTS DUE TO OWNERSHIP TYPES
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories, Number of Students located in private dormitories,
Bed Capacity of the private dormitories.
Report Coverage : The number of private dormitories, the bed capacities and the number of
students located in these dormitories are queried by choosing relevant parameters. The
results are enlisted by means of NUTS hierarchy.
Usage :


By using the navigation opportunities, the user can drill down to the county level.



1.2.4.12.
THE NUMBER OF PRIVATE DORMITORIES WITH EDUCATION LEVELS
Figure 15 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES WITH EDUCATION
LEVELS
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories, Number of Students located in private dormitories
Report Coverage : The number of private dormitories and the number of students located in
these dormitories are queried by choosing relevant parameters. The results are enlisted by
education levels and gender capacities.
Usage :





1.2.4.13.
THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH OPEN
DATES
FIGURE 193 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH
OPEN DATES
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories, Dormitories Capacities, Number of Students
located in private dormitories
Report Coverage : The number of private dormitories, dormitories capacities and the number
of students located in these dormitories are queried by choosing relevant parameters. The
results are enlisted by opening years of the private dormitories.
Usage :





The pie chart at the end of the analysis was prepared for all measures in the analysis.

1.2.4.14.
THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH CLOSURE
DATES
FIGURE 194 Dashboard Report - THE NUMBER OF PRIVATE DORMITORIES AND CAPACITIES WITH
CLOSURE DATES
Parameters :
fashion.
village.
Temporarily Closed.
Measures: Number of Private Dormitories, Dormitories Capacities, Number of Students
located in private dormitories
Report Coverage : The number of private dormitories, dormitories capacities and the number
of students located in these dormitories are queried by choosing relevant parameters. The
results are enlisted by closure years of the private dormitories.
Usage :





The pie chart at the end of the analysis was prepared for all measures in the analysis.

1.2.5. STAFF DASHBOARD
1.2.5.1.
THE NUMBER OF STAFF DUE TO GENDER IN INSTITUTION HIERARCHY
FIGURE 195 Dashboard Report - THE NUMBER OF STAFF DUE TO GENDER IN INSTITUTION
HIERARCHY
Parameters :
Date of the data : The validity date(s) of the staff data.
Province : The province of the institution for the staff data.
District : The district level of the institution, there are relation between province and district.
city center.
Gender : Gender information of staff containing 'Male','Female','Empty'. Empty choice
represents 'null' values in the gender column of the database table.
Measures: Number of Active Staff
Report Coverage : The number of active staff can be queried by choosing relevant
parameters. The first parameter which covers reference date is the mandatory parameter.
Usage :




The hierarchical column for institutions can be used in order to accomplish drill down
and roll-up operations between different concept hierarchy levels.
1.2.5.2.
THE NUMBER OF STAFF DUE TO PUBLIC/PRIVATE/OPEN DISCRIMINATION
IN LOCATION (NUTS) HIERARCHY
FIGURE 196 Dashboard Report - THE NUMBER OF STAFF DUE TO PUBLIC/PRIVATE/OPEN
DISCRIMINATION IN LOCATION (NUTS) HIERARCHY
Parameters :
city center.
parameters in the NUTS hierarchical report style . The first parameter which covers reference
date is the mandatory parameter.
Usage :




The hierarchical column for location of institutions can be used in order to accomplish
drill down and roll-up operations between different concept hierarchy levels.
1.2.5.3.
THE NUMBER OF STAFF DUE TO AGE GROUPS IN LOCATION (NUTS)
HIERARCHY
FIGURE 197 Dashboard Report - THE NUMBER OF STAFF DUE TO AGE GROUPS IN LOCATION
(NUTS) HIERARCHY
Parameters :
city center.
parameters with age groups in the NUTS hierarchical report style . The first parameter which
covers reference date is the mandatory parameter.
Usage :




The hierarchical column for location of the institutions can be used in order to
accomplish drill down and roll-up operations between different concept hierarchy
levels.
1.2.5.4.
THE NUMBER OF STAFF DUE TO PROVIENCE AND EDUCATION LEVEL OF
STAFF
FIGURE 198 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVIENCE AND EDUCATION
LEVEL OF STAFF
Parameters :
city center.
Education Level of Staff : Education level of staff containing 'Upper Secondary Degree',
'University Degree (Bsc.)', 'Master Degree(Msc.)', 'Doctorate (Phd.)' etc.
parameters with education level of staff in the province-district hierarchical report style . The
first parameter which covers reference date is the mandatory parameter.
Usage :




levels. User can make drilldown operation on province column and can query district
level separation of data.
1.2.5.5.
THE NUMBER OF PUBLIC STAFF BY INSTITUTION HIERARCHY DUE TO
JOB TITLES
FIGURE 199 Dashboard Report - THE NUMBER OF STAFF BY INSTITUTION HIERARCHY DUE TO
JOB TITLES
Parameters :
city center.
parameters with job titles. The first parameter which covers reference date is the mandatory
parameter.
Usage :




1.2.5.6.
THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES, EDUCATION LEVELS
AND GENDERS
FIGURE 200 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES,
EDUCATION LEVELS AND GENDERS
Parameters :
city center.
parameter.
Usage :




1.2.5.7.
THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES AND JOB TITLES
FIGURE 201 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO BRANCHES AND JOB
TITLES
Parameters :
city center.
parameter.
Usage :




1.2.5.8.
THE NUMBER OF PUBLIC STAFF DUE TO AGE GROUPS, EDUCATION
LEVELS AND GENDERS
FIGURE 202 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO AGE GROUPS,
EDUCATION LEVELS AND GENDERS
Parameters :
city center.
parameter.
Usage :



1.2.5.9.
THE NUMBER OF PUBLIC TEACHERS DUE TO EDUCATION LEVELS AND
PROVINCES
FIGURE 203 Dashboard Report - THE NUMBER OF PUBLIC TEACHERS DUE TO EDUCATION
LEVELS AND PROVINCES
Parameters :
city center.
parameter.
Usage :



1.2.5.10.
THE NUMBER OF PUBLIC STAFF DUE TO PROVINCES AND GENDERS
FIGURE 204 Dashboard Report - THE NUMBER OF PUBLIC STAFF DUE TO PROVINCES AND
GENDERS
Parameters :
city center.
parameter.
Usage :



1.2.5.11.
THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION LEVELS FOR
PUBLIC INSTITUTIONS
FIGURE 205 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION
LEVELS FOR PUBLIC INSTITUTIONS
Parameters :
city center.
Service Class of Staff: The service class infromation contains such as 'General Administration
Services', 'Support Services' etc.
Assigning/Location Change Type of Staff : Assigning Type can be used in the for assignment
process of teh staff, other tarnsactions contains location change tyep information. But all
thsese parameters are fed by same look-up table.
Branch/Speciality of Staff : Branch of the staff is avaliable only for teacher category.
Staff Title : This parameter covers the staff title of the staff.
Job Title : This parameter covers the job title of the staff. Job title and staff title can be
different, such as staff title can be 'Teacher' but job title can be 'School Manager'.
Employment Type : Employment type of staff for public institutions can be 'Permanent',
'Contractual', 'Temporary' etc.
Measures: Number of Active Staff in Public Institutions
parameters with education level of staff in the province-district hierarchical report style for
public institutions. The first parameter which covers reference date is the mandatory
parameter.
Usage :




1.2.5.12.
THE NUMBER OF STAFF BY INSTITUTIONAL HIERARCHY DUE TO JOB
TITLES FOR PRIVATE INSTITUTIONS
FIGURE 206 Dashboard Report - THE NUMBER OF PRIVATE STAFFBY INSTITUTIONAL
HIERARCHY DUE TO JOB TITLES FOR PRIVATE INSTITUTIONS
Parameters :
city center.
parameter.
Usage :



The user can print the analysis and has opportunity to transfer the data to Excel, Powerpoint
platforms or PDF, XML, CSV file formats.
1.2.5.13.
THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION LEVELS FOR
FIGURE 207 Dashboard Report - THE NUMBER OF STAFF DUE TO PROVINCES AND EDUCATION
LEVELS FOR PRIVATE INSTITUTIONS
Parameters :
city center.
Branch/Speciality of Staff : Branch of the staff is avaliable only for teacher category.
Job Title : This parameter covers the job title of the staff.
Employment Type : Employment type of staff for private institutions can be 'Permanent',
'Course Based', 'Others' .
Measures: Number of Active Staff in Private Institutions
parameters with education level of staff in the province-district hierarchical report style for
private institutions. The first parameter which covers reference date is the mandatory
parameter.
Usage :




1.2.5.14.
THE NUMBER OF STAFF DUE TO BRANCHES, EDUCATION LEVELS AND
GENDERS FOR PRIVATE INSTITUTIONS
FIGURE 208 Dashboard Report - THE NUMBER OF STAFF DUE TO BRANCHES, EDUCATION
LEVELS AND GENDERS FOR PRIVATE INSTITUTIONS
Parameters :
city center.
parameter.
Usage :



The user can print the analysis and has opportunity to transfer the data to Excel, Powerpoint
platforms or PDF, XML, CSV file formats.
1.2.5.15.
AD-HOC_MODULE_PERS UOE TABLE - EDUCATIONAL PERSONNEL BY
LEVEL OF EDUCATION, PROGRAMME ORIENTATION, PROGRAMME
DESTINATION, TYPE OF INSTITUTION, PERSONNEL CATEGORY AND
EMPLOYMENT STATUS
FIGURE 209 Dashboard Report - AD-HOC_MODULE_PERS UOE TABLE
Parameters :
UOE Period Information : Educational periods for UOE have to be chosen with in the list.
Measures: Number of Educational Personnel within schools, province and district
administrative offices and ministry level.
Report Coverage : The number of active educational personnel can be queried by choosing
relevant UOE period in AD-HOC_MODULE_PERS UOE data table format. this table covers
instructional personnel, maintenance and
operations personnel, management/quality
control/administration personnel.
Usage :



After the selection of the parameter and starting the analysis execution by pressing
1.2.5.16.
PERS1 UOE TABLE - CLASSROOM TEACHERS BY LEVEL OF EDUCATION,
PROGRAMME ORIENTATION, PROGRAMME DESTINATION,SEX,AGE, TYPE
OF INSTITUTION AND EMPLOYMENT STATUS
FIGURE 210 Dashboard Report - PERS1 UOE TABLE
Parameters :
UOE Period Information : Educational periods for UOE have to be chosen within the list.
Measures: Number of classroom teachers within schools
Report Coverage : The number of active classroom teachers can be queried by choosing
relevant UOE period in PERS1 UOE data table format. This tables query results have to be
same with the AD-HOC_MODULE_PERS table 'Classroom Teachers' part.
Usage :



1.2.5.17.
PERS2 UOE TABLE - SCHOOL LEVEL MANAGEMENT PERSONNEL AND
TEACHER AIDES IN ISCED LEVELS 0, 1, 2 AND 3
FIGURE 211 Dashboard Report - PERS2 UOE TABLE
Parameters :
Measures: Number of school level management staff and teacher aides within schools
Report Coverage : The number of active school level management staff and teacher aides
can be queried by choosing relevant UOE period in PERS2 UOE data table format. This tables
query results have to be same with the AD-HOC_MODULE_PERS table 'School Level
Management' and 'Teacher Aides' parts.
Usage :



1.2.5.18.
PERS-ENRL UOE TABLE - NUMBER OF STUDENTS WITH COVERAGE
ADJUSTED TO STATİSTİCS ON EDUCATION PERSONNEL BY LEVEL OF
EDUCATION, PROGRAMME ORIENTATION, PROGRAMME DESTINATION,
TYPE OF INSTITUTION, AND INTENSITY OF PARTICIPATION
FIGURE 212 Dashboard Report - PERS-ENRL UOE TABLE
Parameters :
Measures: Number of students whose teacher number is counted in PERS1 table
Report Coverage : The number of students can be queried by choosing relevant UOE period
in PERS_ENRL UOE data table format. This tables query results have to be represent number
of students whose teacher infromation have to put in PERS1 UOE table.
Usage :



1.2.6. FINANCE DASHBOARD
1.2.6.1.
FINANCE-1 (UOE) TABLE, EDUCATION EXPENDITURE BY LEVEL OF EDUCATION,
SOURCE AND TYPE OF TRANSACTION
FIGURE 213 Dashboard Report - FINANCE-1 TABLE
Parameters :
UOE Period Information : Financial periods for UOE have to be chosen within the list.
Measures: Amount of education expenditures by ISCED Levels (Level of education,
programme orientation, programme destination)
Report Coverage : The Finance-1 UOE table can be filled by using this report via choosing
relevant UOE period information. A parameter which covers UOE period information is the
mandatory parameter.
Usage :



1.2.6.2.
FINANCE-2 (UOE) TABLE, EDUCATION EXPENDITURE BY LEVEL OF EDUCATION,
NATURE AND RESOURCE CATEGORY
FIGURE 214 Dashboard Report – FINANCE-2 TABLE
Parameters :
UOE Period Information : Financial periods for UOE have to be chosen within the list.
Measures: Amount of education expenditures by ISCED Levels (Level of education,
programme orientation, programme destination)
Report Coverage : The Finance-2 UOE table can be filled by using this report via choosing
relevant UOE period information. A parameter which covers UOE period information is the
Usage :



1.2.6.3.
TEFBIS FINANCE-1 TABLE REPORT (DUE TO LOCATION)
FIGURE 215 Dashboard Report - TEFBIS FINANCE-1 TABLE REPORT (DUE TO LOCATION)
Parameters :
Date of the data: The validity date(s) of the Finance data.
Financial Year: The Financial Year(s) of the Finance data.
vocational.
city center.
Measures: Amount of education expenditures for institutions by ABS Codes (FunctionalFiancial-Economical)
Report Coverage : The Tefbis Finance-1 Table records can be queried by choosing relevant
parameters in Location Hierarchy. The first parameter which covers reference date is the
Usage :




levels.
1.2.6.4.
TEFBIS FINANCE-1 TABLE REPORT (DUE TO EDUCATION LEVEL)
FIGURE 216 Dashboard Report - TEFBIS FINANCE-1 TABLE REPORT (DUE TO EDUCATION
LEVEL)
Parameters :
vocational.
city center.
Report Coverage : The Tefbis Finance-1 Table records can be queried via choosing relevant
parameters by Level of Education. The first parameter which covers reference date is the
Usage :




levels.
1.2.6.5.
TEFBIS FINANCE-2 TABLE REPORT (DUE TO LOCATION)
FIGURE 217 Dashboard Report - TEFBIS FINANCE-2 TABLE REPORT (DUE TO LOCATION)
Parameters :
vocational.
city center.
Report Coverage : The Tefbis Finance-2 Table records can be queried by choosing relevant
parameters in Location Hierarchy. The first parameter which covers reference date is the
Usage :




levels.
1.2.6.6.
TEFBIS FINANCE-2 TABLE REPORT (DUE TO EDUCATION LEVEL)
FIGURE 218 Dashboard Report - TEFBIS FINANCE-2 TABLE REPORT (DUE TO EDUCATION
LEVEL)
Parameters :
vocational.
city center.
Report Coverage : The Tefbis Finance-2 Table records can be queried via choosing relevant
parameters by Level of Education. The first parameter which covers reference date is the
Usage :




levels.
1.2.6.7.
CENTRAL BUDGET FINANCE-1 TABLE REPORT
Parameters :
Administrative Unit Code: Discrimination of National Education Directorates and Educational
institutions.
Measures: Amount of education expenditures for Central Budget Finance-1 Table by ABS
Codes.
Report Coverage : Central Budget Finance-1 Table records can be queried by choosing
relevant parameters. The first parameter which covers reference date is the mandatory
parameter.
Usage :




1.2.6.8.
CENTRAL BUDGET FINANCE-2 TABLE REPORT
Parameters :
Administrative Unit Code: Discrimination of National Education Directorates and Educational
institutions.
Codes.
relevant parameters. The first parameter which covers reference date is the mandatory
parameter.
Usage :




1.2.6.9.
CENTRAL BUDGET
FINANCE-1 TABLE REPORT (EXPENDITURES OF
SPECIAL PROVINCE ADMINISTRATION)
(EXPENDITURES OF SPECIAL PROVINCE ADMINISTRATION)
Parameters :
Province : The province of the institution for the Finance data.
Codes.
relevant parameters in NUTS Hierarchy. The first parameter which covers reference date is
the mandatory parameter.
Usage :




1.2.6.10.
CENTRAL BUDGET
FINANCE-2 TABLE REPORT (EXPENDITURES OF
SPECIAL PROVINCE ADMINISTRATION)
(EXPENDITURES OF SPECIAL PROVINCE ADMINISTRATION)
Parameters :
Province : The province of the institution for the Finance data.
Codes.
relevant parameters in NUTS Hierarchy. The first parameter which covers reference date is
the mandatory parameter.
Usage :




1.2.6.11.
TEFBIS-HOUSEHOLD QUESTIONNAIRE ANALYSIS RESULTS
(HOUSEHOLD EXPENDITURES)
FIGURE 223 Dashboard Report – TEFBIS-HOUSEHOLD QUESTIONNAIRE ANALYSIS RESULTS
(HOUSEHOLD EXPENDITURES)
Parameters :
Date of the data : The validity date(s) of the Finance data.
Questionnaire Type (Public/Private): The type(s) of the Questionnaire.
Questionnaire Reference Year: The reference year(s) of the Questionnaire.
Measures: Amount of education expenditures for Household Questionnaire Results Table(for
Finance-1 table) Table by ABS Codes.
Report Coverage : Household Questionnaire Results Table records can be queried by
choosing relevant parameters by Questionnaire Type. The first parameter which covers
reference date is the mandatory parameter.
Usage :



1.2.7. NON-FORMAL DASHBOARD
1.2.7.1.
THE NUMBER OF APPLICANTS FOR MOTOR VEHICLES BY CERTIFICATE
TYPES AND PERIODS
FIGURE 224 Dashboard Report – THE NUMBER OF APPLICANTS FOR MOTOR VEHICLES BY
CERTIFICATE TYPES AND PERIODS
Parameters :
Reference Date:
The validity date of applicants data.
Certification Year:
The period of certification.
Province Name:
The province of institution which the application has been made.
District Name:
The district of institution which the application has been made.
Settlement Type:
The settlement type of place where the institution exists.
Measures: Number of applicants.
Report Coverage : The number of applicants by certificate types and periods can be queried
by choosing relevant parameters.
Usage :




THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES BY CERTIFICATE TYPES AND PERIODS
1.2.7.2.
THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES BY
CERTIFICATE TYPES AND PERIODS
FIGURE 225 Dashboard Report – THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES
BY CERTIFICATE TYPES AND PERIODS
Parameters :
Reference Date:
The validity date of certificates data.
Certification Year:
Province Name:
District Name:
Settlement Type:
Measures: Number of certificates.
Report Coverage : The number of certificates by certificate types and periods can be queried
Usage :



1.2.7.3.
THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES BY
EDUCATION LEVELS AND PERIODS
FIGURE 226 Dashboard Report – THE NUMBER OF CERTIFICATES GIVEN FOR MOTOR VEHICLES
BY EDUCATION LEVELS AND PERIODS
Parameters :
Reference Date:
The validity date of certificates data.
Certification Year:
Province Name:
District Name:
Settlement Type:
Measures: Number of certificates.
Report Coverage : The number of certificates by education levels and periods can be queried
Usage :



1.2.7.4.
THE NUMBER OF COURSES OPENED BY SETTLEMENT TYPES AND
PERIODS
FIGURE 227 Dashboard Report – THE NUMBER OF COURSES OPENED BY SETTLEMENT TYPES
AND PERIODS
Parameters :
Reference Date:
The validity date of courses data.
Course Period:
The period of course.
Course Type:
The type of course.
Province Name:
District Name:
Settlement Type:
Measures: Number of courses.
Report Coverage : The number of courses opened by settlement types and periods can be
queried by choosing relevant parameters.
Usage :



1.2.7.5.
THE NUMBER OF TRAINEES BY COURSE TYPES AND PERIODS
FIGURE 228 Dashboard Report – THE NUMBER OF TRAINEES BY COURSE TYPES AND PERIODS
Parameters :
Reference Date:
The validity date of trainees data.
Course Period:
Course Type:
The type of course.
Province Name:
District Name:
Settlement Type:
Measures: Number of trainees.
Report Coverage : The number of trainees by course types and periods can be queried by
choosing relevant parameters.
Usage :



1.2.7.6.
THE NUMBER OF TRAINEES BY EMPLOYEMENT TYPES AND PERIODS
FIGURE 229 Dashboard Report – THE NUMBER OF TRAINEES BY EMPLOYEMENT TYPES AND
PERIODS
Parameters :
Reference Date:
The validity date of trainees data.
Course Period:
Course Type:
The type of course.
Province Name:
District Name:
Settlement Type:
Measures: Number of trainees.
Report Coverage : The number of trainees by course types and periods can be queried by
choosing relevant parameters.
Usage :


1.2.7.7.
THE NUMBER OF STAFF BY STATUS AND PERIODS
FIGURE 230 Dashboard Report – THE NUMBER OF STAFF BY STATUS AND PERIODS
Parameters :
Reference Date:
The validity date of staff data.
Course Period:
Course Type:
The type of course.
Province Name:
District Name:
Settlement Type:
Measures: Number of staff.
Report Coverage : The number of staff by status and periods can be queried by choosing
relevant parameters.
Usage :



1.2.8. UOE DATA TABLES DASHBOARD
1.2.8.1.
ENRL-1 UOE DATA TABLE
FIGURE 231 Dashboard Report - ENRL-1 UOE DATA TABLES
Parameters :
UOE Period : The validity period of the UOE subject area.
Report Coverage : The number of enrolled students within the selected UOE period are
queried with ISCED levels, ages and gender. The ages of students are not grouped in the
reports for showing extraordinary ages in the original data entry systems.
Usage :


The reports data contains e-school, open primary school, open high school, mobile preprimary classes, SHCEK pre-primary schools and pre-primary schools in other
institutions (191.madde) are combined in one report by using
T_UOE_TANIM_TABLOSU metadata table.

For gender discrimination, an other data table showed in the same report. User can
change the data table coverage by selecting gender item from the list in the top of the
data table.

1.2.8.2.
ENRL1-ADULT UOE DATA TABLE
FIGURE 232 Dashboard Report - ENRL1-ADULT UOE DATA TABLES
Parameters :
Measures: Number of Enrolled Students in Adult Education
Report Coverage : The number of enrolled students of adult education within the selected
UOE period are queried with ISCED levels, ages and gender. The ages of students are not
grouped in the reports for showing extraordinary ages in the original data entry systems. For
adult education open primary school and open high school students are queried in this report.
Usage :


The reports data contains open primary school and open high school are combined in
one report by using T_UOE_TANIM_TABLOSU metadata table.

For gender discrimination, an other data table showed in the same report. User can
change the data table coverage by selecting gender item from the list in the top of the
data table.

1.2.8.3.
ENRL1A UOE DATA TABLE
FIGURE 233 Dashboard Report - ENRL1a UOE DATA TABLES
Parameters :
queried with ISCED levels, institution types(public,private) and gender.
Usage :



For institution types two different data table was prepared in the same report.

In Turkish education system, there are public and private institutions. There are not
government dependent private institutions in Turkish education system.

1.2.8.4.
ENRL1A-ADULT UOE DATA TABLE
FIGURE 234 Dashboard Report - ENRL1a-ADULT UOE DATA TABLES
Parameters :
Measures: Number of Enrolled Students in Adult Education
Report Coverage : The number of enrolled students of adult education within the selected
UOE period are queried with ISCED levels, institution types(public,private) and gender. For
adult education open primary school and open high school students are queried in this report.
Usage :


The reports data contains open primary school and open high school are combined in
one report by using T_UOE_TANIM_TABLOSU metadata table.



1.2.8.5.
Parameters :
Measures: Number of Enrolled Students , Number of Repeaters
Report Coverage : The number of enrolled students and repeaters within the selected UOE
period are queried with ISCED levels,grades and gender. Pre-primary level does not covered
in this UOE data table.
Usage :


The reports data contains e-school, open primary school, open high school are
combined in one report by using T_UOE_TANIM_TABLOSU metadata table.

For gender discrimination another data table was prepared in the same report. The
user can select gender information from the list item in the top of the data table.

1.2.8.6.
Parameters :
Measures: Number of Enrolled Students in Grade1
Report Coverage : The number of enrolled students in grade1 within the selected UOE period
are queried with ISCED levels,ages and gender. This UOE table only covers grade1 students
data.
Usage :


The reports data contains e-school and open primary school are combined in one
report by using T_UOE_TANIM_TABLOSU metadata table.

1.2.8.7.
Parameters :
Measures: Number of Foreign Students
Report Coverage : The number of foreign students within the selected UOE period are
queried with ISCED levels, citizenship and gender. In Turkish education system, there are not
mobile students in 0-3 ISCED levels, so this report only covers foreign students.
Usage :



1.2.8.8.
ENTR-1 UOE DATA TABLE
FIGURE 238 Dashboard Report - ENTR-1 UOE DATA TABLES
Parameters :
Measures: Number of Enrolled Students , Number of New Entrants, Number of Re-entrants,
Number of Continuing Students
Report Coverage : The number of enrolled, new-entrant, re-entrant and continuous students
within the selected UOE period are queried with ISCED 3 level. The second table in the
reports shows open high schools students information. This second table was included for the
request of SDP, for identifying open school details.
Usage :


The reports data contains e-school and open high school are combined in one report
by using T_UOE_TANIM_TABLOSU metadata table.

This UOE table only covers Upper-Secondary education level.

1.2.8.9.
ENTR-2 UOE DATA TABLE
FIGURE 239 Dashboard Report - ENTR-2 UOE DATA TABLES
Parameters :
Measures: Number of New Entrants in Upper-Secondary Level
Report Coverage : The number of new-entrants within the selected UOE period are queried
with ISCED 3 level, ages and gender.
Usage :



This UOE table only covers Upper-Secondary education level.

For gender discrimination another data table was prepared in the same report. The
user can select gender information from the list item in the top of the data table.

1.2.8.10.
GRAD-1 UOE DATA TABLE
FIGURE 240 Dashboard Report - GRAD-1 UOE DATA TABLES
Parameters :
Measures: Number of Graduate Students in Upper-Secondary Level
Report Coverage : The number of graduate students within the selected UOE period are
queried for ISCED level 3 with institution types(public,private) and gender.
Usage :





1.2.8.11.
Parameters :
queried for ISCED level 3 with ages and gender.
Usage :



For gender based data tables, two different data table was prepared in the same
report.

1.2.8.12.
Parameters :
queried for ISCED level 3 with FOET(Fields of Education) definitions.
Usage :



1.2.8.13.
REGIO-1 UOE DATA TABLE
FIGURE 243 Dashboard Report - REGIO-1 UOE DATA TABLES
Parameters :
queried for ISCED levels, region and gender.
Usage :



For open primary and high school data, region information takes from examination
centers. For students located in foreign countries is showed under 'Ankara' as the main
center of open schools are located at Ankara. This decision was taken by SDP during
the project.

report.

1.2.8.14.
REGIO-2 UOE DATA TABLE
FIGURE 244 Dashboard Report - REGIO-2 UOE DATA TABLES
Parameters :
queried for ISCED levels, region, age and gender.
Usage :



the project.

report.

1.2.8.15.
CLASS UOE DATA TABLE
FIGURE 245 Dashboard Report - CLASS UOE DATA TABLES
Parameters :
Measures: Average Class Size, Number of Enrolled Students, Number of Classes
Report Coverage : The average class size within the selected UOE period are queried for
ISCED 1 and 2 levels with institution types(public&private).
Usage :


The reports data contains e-school and open primary school are combined in one
report by using T_UOE_TANIM_TABLOSU metadata table.

the project.



1.2.8.16.
ENRLLANG-1 UOE DATA TABLE
FIGURE 246 Dashboard Report - ENRLLANG-1 UOE DATA TABLES
Parameters :
Measures: Number of Students Who Take Language Courses
Report Coverage : The number of students who take language courses within the selected
UOE period are queried for ISCED levels with languages.
Usage :


The reports data contains e-school system data by using T_UOE_TANIM_TABLOSU
metadata table.

Pre-Primary and Primary level first 3 classes is not showed in this data table, as in the
Turkish education system foreign language courses first given in the 4th grade of
primary level.

If a student takes more than one foreign language courses, this student data have to
be shown twice in each language row.

1.2.8.17.
ENRLLANG-2 UOE DATA TABLE
FIGURE 247 Dashboard Report - ENRLLANG-2 UOE DATA TABLES
Parameters :
Measures: Number of Students Who Take 1 Language Courses, Number of Students Who
Take 2 or more Language Courses, Number of Students Who Didn't Take Any Language
Courses
Report Coverage : The number of students who take language courses within the selected
UOE period are queried for ISCED levels with ages.
Usage :


metadata table.

Pre-Primary and Primary level first 3 classes is not showed in this data table, as in the
Turkish education system foreign language courses first given in the 4th grade of
primary level.

1.2.8.18.
PERS-1 UOE DATA TABLE
FIGURE 248 Dashboard Report - PERS-1 UOE DATA TABLES
Parameters :
Measures: Number of Teachers (in schools)
Report Coverage : The number of teachers in schools within the selected UOE period are
queried for ISCED levels with age groups, gender and institution type (public,private).
Usage :


The reports data contains e-staff and private education system, SHCEK, mobile preprimary classes and other institutions pre-primary classes data by using

This analysis contains only classroom teachers with ISCED levels.

For ISCED discrimination, the number of students in each ISCED level was queried
and teacher numbers distributed into ISCED levels according to student numbers.

1.2.8.19.
PERS-2 UOE DATA TABLE
FIGURE 249 Dashboard Report - PERS-2 UOE DATA TABLES
Parameters :
Measures: Number of School Level Management Staff (in schools) and Teacher Aides
Report Coverage : The number of school level management staff and teacher aides in
schools within the selected UOE period are queried for ISCED levels with gender and
institution type (public,private).
Usage :


The reports data contains e-staff and private education system, SHCEK, mobile preprimary classes and other institutions pre-primary classes data by using

This analysis contains only school level management staff and teacher aides with
ISCED levels.

Teacher aides covers, support staff in private pre-primary schools.

and staff numbers distributed into ISCED levels according to student numbers.

1.2.8.20.
ADHOC-MODULE-PERS UOE DATA TABLE
FIGURE 250 Dashboard Report - ADHOC-MODULE-PERS UOE DATA TABLES
Parameters :
Measures: Number of Staff (in different categories)
Report Coverage : The number of staff in school level management, school level
administrative, classroom teachers, teacher aides, higher level management, higher level
administrative, support&maintanence within the selected UOE period are queried for ISCED
levels with categories and institution type (public,private).
Usage :


The reports data contains e-staff and private education system data by using

The category of the staff is identified by using ST_PERSONEL_GOREV_KATEGORI
metadata table.

and staff numbers distributed into ISCED levels according to student numbers.

1.2.8.21.
PERS-ENRL UOE DATA TABLE
FIGURE 251 Dashboard Report - PERS-ENRL UOE DATA TABLES
Parameters :
Measures: Number of Students whose teacher numbers can be queried
Report Coverage : The number of students whose teacher numbers can be queried within the
selected UOE period are queried for ISCED levels with institution types (public,private). Open
primary school and open high school students data can not given in this table. And also
students in sub-type of the school can not given in this table, because teachers are located in
the basic type of the school. This table only covers students in which schools have teacher
staff.
Usage :


metadata table.

1.2.9. COMBINED INSTITUTION, CLASSROOM, STUDENT, TEACHER DASHBOARD
1.2.9.1.
INSTITUTION, TEACHER, STUDENT STATİSTİCS BY PROVINCE
DISTRICT LEVELS
AND
FIGURE 252 Dashboard Report - INSTITUTION, TEACHER, STUDENT STATİSTİCS BY PROVINCE AND
DISTRICT LEVELS
Parameters :
Publication Period : The validity period of the combined publication subject area.
Level of education : The scope of the report due to pre-defined education levels, such as PrePrimary, Primary and Upper-Secondary.
city center
Measures: Number of Institutions, Number of Classrooms, Number of Divisions, Number of
Pre-Primary Class Students(with gender), Number of Students (with gender), Number of
Managers, Number of Teachers (with gender and categories)
Report Coverage : The number of institutions, classrooms, divisions, students and teachers
are listed for selected province and period.
Usage :


The reports data contains e-school, public institutions, private institutions, e-staff
systems data by using T_UOE_TANIM_TABLOSU metadata table for the defined
publication period with 'Y' value in TANIM_TUR column.

The data is prepared by combining different target tables after running data
transformation package .

1.2.9.2.
INSTITUTION, TEACHER, STUDENT INDICATORS BY PROVINCE AND
DISTRICT LEVELS
FIGURE 253 Dashboard Report - INSTITUTION, TEACHER, STUDENT INDICATORS BY PROVINCE AND
DISTRICT LEVELS
Parameters :
city center
Measures: Number of Institutions, Number of Classrooms, Number of Divisions, Number of
Students (with gender), Number of Teachers (with gender), Number of Students per
Classrooms, Number of Students per Division, Number of Students per Teacher
Report Coverage : The number of institutions, classrooms, divisions, students, teachers and
calculated indicators are listed for selected province and period. The calculated indicators are;
Number of Students per Classrooms, Number of Students per Division, Number of Students
per Teacher
Usage :


The reports data contains e-school, public institutions, private institutions, e-staff
systems data by using T_UOE_TANIM_TABLOSU metadata table for the defined
publication period with 'Y' value in TANIM_TUR column.

The data is prepared by combining different target tables after running data
transformation package .

1.2.9.3.
NUMBER OF ENROLLED
PUBLICATION PERIOD
STUDENT
IN
NUTS
HIERARCHY
WITHIN
FIGURE 254 Dashboard Report - NUMBER OF ENROLLED STUDENT IN NUTS HIERARCHY WITHIN
PUBLICATION PERIOD
Parameters :
Report Coverage : The number of enrolled students are queried within the selected
publication period in NUTS hierarchy. The number of students are taken from
FACT_IO_OGRYIL_BASI_BILGILERI fact table.
Usage :


metadata table for the defined publication period with 'Y' value in TANIM_TUR column.

The number of students are taken from FACT_IO_OGRYIl_BASI_BILGILERI fact table.

This dashboard report is prepared for the end user to be able to reach publication data.
If the user knows reference date and education period, user can reach the same data
tables in formal education dashboard.

1.2.9.4.
NUMBER OF GRADUATED STUDENT IN NUTS HIERARCHY WITHIN
PUBLICATION PERIOD
FIGURE 255 Dashboard Report - NUMBER OF GRADUATED STUDENT IN NUTS HIERARCHY WITHIN
PUBLICATION PERIOD
Parameters :
Report Coverage : The number of graduated students are queried within the selected
publication period in NUTS hierarchy. The number of students are taken from
FACT_IO_OGRYIL_SONU_BILGILERI fact table.
Usage :


metadata table for the defined publication period with 'Y' value in TANIM_TUR column.

The number of students are taken from FACT_IO_OGRYIL_SONU_BILGILERI fact
table.

If the user knows reference date and education period, user can reach the same data

1.2.9.5.
NUMBER OF STUDENTS IN OPEN HIGH SCHOOL IN NUTS HIERARCHY
WITHIN PUBLICATION PERIOD
FIGURE 256 Dashboard Report - NUMBER OF STUDENTS IN OPEN HIGH SCHOOL IN NUTS HIERARCHY
Parameters :
Measures: Number of Active Students In Open High School, Number of Graduated Students
in Open High School
Report Coverage : The number of active and graduate students are queried within the
selected publication period in NUTS hierarchy, in open high school system. The number of
students are taken from FACT_AOL_OGRENCI_YENI fact table.
Usage :


The reports data contains open high school system data by using
T_UOE_TANIM_TABLOSU metadata table for the defined publication period with 'Y'
value in TANIM_TUR column.

The number of students are taken from FACT_AOL_OGRENCI_YENI fact table.

If the user knows reference date and education year, user can reach the same data

1.2.9.6.
NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL IN NUTS HIERARCHY
FIGURE 257 Dashboard Report - NUMBER OF STUDENTS IN OPEN PRIMARY SCHOOL IN NUTS HIERARCHY
Parameters :
Measures: Number of Active Students In Open Primary School, Number of Graduated
Students in Open Primary School
Report Coverage : The number of active and graduate students are queried within the
selected publication period in NUTS hierarchy, in open primary school system. The number of
students are taken from FACT_AIO_OGRENCI_YENI fact table.
Usage :


The reports data contains open primary school system data by using

The number of students are taken from FACT_AIO_OGRENCI_YENI fact table.

If the user knows reference date and education year, user can reach the same data

1.2.9.7.
SUMMER KINDERGARTENS, MOBILE CLASSES, SHCEK & KINDERGARTENS
OF OTHER INSTITUTIONS
FIGURE 258 Dashboard Report - SUMMER KINDERGARTENS, MOBILE CLASSES,SHCEK &
KINDERGARTENS OF OTHER INSTITUTIONS
Parameters :
city center
Organization Type: Other Institutions, Mobile Classes, SHCEK, Summer Kindergartens
Measures: Number of Students, Number of Institutions, Number of Sections, Number of
Classrooms
Report Coverage : The numbers of students, institutions, classrooms and sections of the
kindergartens in a NUTS hierarchy. The source data comes from MEIS system, and for
SHCEK the data was converted from external Excel files.
Usage :




The number of students are grouped by the students’ ages.

The reports data contains open primary school system data by using

The number of students are taken from FACT_DIS_KURUM_OGR_OGRETMEN fact
table.

If the user knows reference date, user can reach the same data tables in formal
education dashboard.

1.3. PACKAGES, JOBS AND RELATIONS
For data transformation different Pl/SQL packages with containing various procedures and/or
functions were developed during the project. The target tables, related/used materialized
views and package details are given in the below table. Data refresh cycle of materialized
views under okulsis, ilsis and ilsisweb schema belongs to MoNE IT experts.
Scheduled Task Name
Package Name
Procedure/Function Name
Related Materialized
Views
Source Tables
Main Target Tables
Sugges
ted
Refres
h
Period
FACT_AIO_OGRENCI_ETL_S
JOB
PKG_ETL_ACIK
FACT_AIO_OGRENCI_YEN
I_ETL
ST_NUTS_IL_ILCE
FACT_AIO_OGRENCI_YE
NI
Semiannuall
y
FACT_AOL_OGRENCI
_ETL_SJOB
PKG_ETL_ACIK
FACT_AOL_OGRENCI_YE
NI_ETL
ST_NUTS_IL_ILCE
ST_FOET
FACT_AOL_OGRENCI_YE
NI
FACT_AKTIF_BURS_OGR_BI
LGILERI _ETL_SJOB
PKG_ETL_BURS_YATIL
I_OZELYURT
FACT_AKT_BURS_OGR_BI
L_ETL
ST_BURS_DONEM
ST_NUTS_IL_ILCE
Semiannuall
y
Manuall
y after
each
schoola
rship
semest
ers
FACT_BURS_MIKTAR_ETL_S
JOB
FACT_BURS_SINAV_ONAY_
OGR _ETL_SJOB
PKG_ETL_BURS_YATIL
I_OZELYURT
PKG_ETL_BURS_YATIL
I_OZELYURT
FACT_BURS_MIKTAR_ETL
ST_BURS_DONEM
ILSISWEB.ST_ILLER
ILSISWEB.ST_ILCELER
OKULSIS.AIO_STRATEJI_ISTA
TISTIK
ILSISWEB.ST_ILLER
ILSISWEB.ST_ILCELER
OKULSIS.BI_AOL_ISTATISTIK
OKULSIS.ST_BURS_SOZLUK
OKULSIS.ST_OGRENCI_SOZL
UK
ILSISWEB.ST_UYRUKLAR
OKULSIS.BI_AKTIF_BURS_OG
R_BILGILERI
UK_LISE
OKULSIS.BI_BURS_MIKTAR
FACT_BURS_SIN_ONAY_O
GR_ETL
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
UK
OKULSIS.ST_DONEM_BILGILE
RI
UK_LISE
OKULSIS.BI_BURS_SINAV_ON
AY_OGR
FACT_BURS_SINAV_ONA
Y_OGR
FACT_BURSU_IPTAL_OGR_B
LG_ETL_SJOB
PKG_ETL_BURS_YATIL
I_OZELYURT
FACT_BURS_IPT_OGR_BIL
_ETL
ST_BURS_DONEM
ST_NUTS_IL_ILCE
FACT_BURSU_IPTAL_OG
R_BILGILERI
FACT_AKTIF_BURS_OGR
_BILGILERI
FACT_BURS_MIKTAR
UOE
Relat
ed?
Annuall
y
Semiannuall
y
Semiannuall
FACT_YATILILIK_DURUM_OG
R_ETL_SJOB
PKG_ETL_BURS_YATIL
I_OZELYURT
FACT_YATILILIK_DURUM_
OGR_ETL
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
FACT_OZEL_YURT_KAPASIT
E _ETL_SJOB
FACT_IO_ENGELLI_OGR_ET
L_SJOB
PKG_ETL_BURS_YATIL
I_OZELYURT
PKG_ETL_ORGUN_IO
FACT_OZELYURT_KAPASI
TE_ETL
FACT_IO_ENGELLI_ETL
ST_NUTS_IL_ILCE
_YURT
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
FACT_IO_OGRENCI_PASIF_E
TL_SJOB
PKG_ETL_ORGUN_IO
FACT_IO_OGRENCI_PASIF
_ETL
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
ST_KURUM_IL_MV
UK
UK_LISE
ST_BURS_DONEM
OKULSIS.BI_BURSU_IPTAL_O
GR_BILGILERI
UK
UK_LISE
RI
OKULSIS.BI_YATILILIK_DURU
M_OGR
ILSIS.OZEL_YURT_KAPASITE
ILSIS.SOZLUK_TABLOSU
UK
RI
OKULSIS.BI_ILK_OZUR_HIZM
ET
UK_LISE
UK
RI
OKULSIS.BI_ILK_OGRENCI_P
ASIF
OKULSIS.BI_ILK_OGRENCI_G
ECMIS_DURUM
OKULSIS.BI_LISE_OGRENCI_
PASIF
y
FACT_YATILILIK_DURUM_
OGR
Semiannuall
y
FACT_OZEL_YURT_KAPA
SITE
FACT_IO_ENGELLI_OGR
Monthly
FACT_IO_OGRENCI_PASI
F
Semiannuall
y
Semiannuall
y
FACT_IO_OGRYIL_BASI_BLG
_ETL_SJOB
PKG_ETL_ORGUN_IO
FACT_IO_OGRYIL_BASI_BI
LGI_ETL
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
ST_KURUM_IL_MV
FACT_IO_OGRYIL_SONU_BL
G _ETL_SJOB
PKG_ETL_ORGUN_IO
FACT_IO_OGRYIL_SONU_
BILGI_ETL
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
ST_KURUM_IL_MV
GECMIS_DURUM
ST_SINIF_SEVIYESI
UK_LISE
UK
RI
OKULSIS.BI_ILK_AKTIF_SINIF
TA_KALAN
BILGILERI
OKULSIS.BI_LISE_AKTIF_SINI
FTA_KALAN
OKULSIS.BI_LISE_AKTIF_OH_
KULLANMAYAN
ST_SINIF_SEVIYESI
UK_LISE
UK
OKULSIS.BI_ILK_OGRENCI_G
ECMIS_DURUM
OKULSIS.BI_ILK_AKTIF_SINIF
TA_KALAN
OKULSIS.BI_ILK_SINIF_TEKR
AR
RI
GECMIS_DURUM
OKULSIS.BI_LISE_AKTIF_SINI
FTA_KALAN
OKULSIS.BI_LISE_SINIF_TEK
RAR
FACT_IO_OGRYIL_BASI_B
ILGILERI
Semiannuall
y
FACT_IO_OGRYIL_SONU_
BILGILERI
Semiannuall
y
FACT_YABANCI_DIL_ETL_SJ
OB
PKG_ETL_YABANCI_DI
L_ETL
FACT_YABANCI_DIL_ETL
BI_YABANCI_DIL_MV
ST_DIL_KODLARI_MV
ST_DONEM_BILGILERI
ST_NUTS_IL_ILCE
FACT_YABANCI_DIL_UOE_E
TL_SJOB
ST_KURUMLAR _ETL_SJOB
PKG_ETL_YABANCI_DI
L_ETL
PKG_ETL_KURUM
FACT_YABANCI_DIL_UOE_
ETL
ST_KURUMLAR_ETL
ST_DIL_KODLARI_MV
FACT_KURUMLAR_ETL_SJO
B
PKG_ETL_KURUM
FACT_KURUMLAR_D_O_E
TL
ST_ANA_SINIFI_VAR
ST_NUTS_IL_ILCE
ST_NUTS_IL_ILCE
OKULSIS.BI_LISE_AKTIF_OH_
KULLANMAYAN
ST_SINIF_SEVIYESI
OKULSIS.BI_ILK_YABANCI_DI
L
OKULSIS_BI_LISE_YABANCI_
DIL
ST_ULKELER
ST_SINIF_SEVIYESI
T_UOE_TANIM_TABLOSU
FACT_YABANCI_DIL
ILSISWEB.ST_KURUM_SOZLU
K
ILSISWEB.ST_ILLER
ILSISWEB.ST_ILCELER
ILSISWEB.ST_BUCAKLAR
ILSISWEB.ST_KOYLER
ILSISWEB.ST_IBBS_DUZEY3
ILSISWEB.ST_IBBS_DUZEY2
ILSISWEB.ST_IBBS_BOLGELE
R
ILSISWEB.DK_KURUM_ANA
ILSISWEB.OK_KURUM_ANA
ILSISWEB.DK_KURUM_HARE
KETLERI
ILSISWEB.OK_KURUM_HARE
KET
ILSISWEB.DK_HIZMETE_GIRI
S
ST_KURUMLAR
ILSISWEB.DK_KURUM_ANA
ILSISWEB.OK_KURUM_ANA
ILSISWEB.DK_BINA_BILGILER
I
ILSISWEB.DK_LOJMAN_BILGI
LERI
ILSISWEB.DK_KUTUPHANE_O
GRENCI
FACT_YABANCI_DIL
Semiannuall
y
FACT_YABANCI_DIL_UOE
ST_KURUMLAR
Annuall
y
Monthly
FACT_KURUMLAR
Monthly
Yes
FACT_KURUM_BINA
_ETL_SJOB
PKG_ETL_KURUM
FACT_KURUM_BINA_ETL_
TUM
ST_NUTS_IL_ILCE
FACT_KURUM_KUL_ALAN
_ETL_SJOB
PKG_ETL_KURUM
FACT_KURUM_KULLANIM_
ETL_TUM
ST_NUTS_IL_ILCE
FACT_KURUM_KUTUP_MAT_
ETL_SJOB
PKG_ETL_KURUM
FACT_KURUM_KUTUPHAN
E_MTR_D_ETL
ST_NUTS_IL_ILCE
FACT_DIS_KURUM_OGR_OG
RMN_ETL_SJOB
PKG_ETL_KURUM
FACT_DIS_KURUM_OGR_
DERSLIK_ETL
ST_NUTS_IL_ILCE
FACT_PERSONEL_BILGILERI
_ETL_SJOB
PKG_ETL_PERSONEL
FACT_PERSONEL_BILGILE
RI_ETL
ST_UNVANLAR_MV
ST_GOREV_UNVAN_MV
ST_BRANSLAR_MV
ST_ISTIHDAM_TIPLERI_
MV
ST_HIZMET_SINIFLARI_M
V
ST_OGRENIM_DURUMLA
RI_MV
RI
OKULSIS.BI_SINIF_SUBE_SAY
ISI
ILSISWEB.OK_BINA_BILGILER
I
ILSISWEB.OK_LOJMAN_BILGI
LERI
OKULSIS.BI_KURUM_OGRETI
M_SEKLI
K
ILSISWEB.DK_BINA_BILGILER
I
ILSISWEB.OK_BINA_BILGILER
I
K
ILSISWEB.DK_BINA_KULLANI
M
ILSISWEB.OK_BINA_KULLANI
M
K
ILSISWEB.DK_KUTUPHANE_M
ATERYAL
ILSISWEB.DK_ANAOKULU
ILSISWEB.DK_ILCE_BAGIMSIZ
_KURUMLAR
ILSISWEB.BI_KAMU_PERSON
EL_BILGILERI
ILSISWEB.BI_OZEL_PERSON
EL_BILGILERI
ST_PERSONEL_GOREV_KAT
EGORI
ST_YAS_GRUPLARI
ST_CINSIYET_PERSONEL
FACT_KURUM_BINA
Monthly
FACT_KURUM_KULLANIM
_ALAN
Monthly
FACT_KURUM_KUTUPHA
NE_MATERYAL
Monthly
FACT_DIS_KURUM_OGR_
OGRETMEN
Semiannuall
y
Semiannuall
y
FACT_PERSONEL_BILGIL
ERI
FACT_PERSONEL_UOE_ETL
_SJOB
PKG_ETL_PERSONEL
FACT_PERSONEL_UOE_E
TL
FACT_PERSONEL_UOE_IO
_ETL
FACT_PERSONEL_UOE_I
MEM_ETL
FACT_PERSONEL_UOE_DI
S_ETL
FACT_PERS12_ETL_SJOB
PKG_ETL_PERSONEL
FACT_PERSONEL_UOE_1
2_ETL
FACT_PERS_ENRL
_ETL_SJOB
PKG_ETL_PERSONEL
FACT_PERS_ENRL_ETL
FACT_UOE_BILGILERI_ETL_
SJOB
PKG_ETL_UOE
FACT_UOE_BILGILERI_GU
NCELLE
ST_ATAMA_SEBEPLERI_
MV
ST_NUTS_IL_ILCE
ST_OGRYIL_ISCED_MV
T_UOE_TANIM_TABLOSU
ST_ISCED_EK_TANIMLAR
FACT_PERSONEL_UOE
Annuall
y
Yes
T_UOE_TANIM_TABLOSU
ST_YAS_GRUPLARI
T_UOE_TANIM_TABLOSU
FACT_IO_OGRYIL_SONU_BIL
GILERI
FACT_IO_OGRYIL_BASI_BILGI
LERI
RETMEN
ST_CINSIYET
T_UOE_TANIM_TABLOSU
ST_ULKELER
GILERI
LERI
FACT_AIO_OGRENCI_YENI
FACT_AOL_OGRENCI_YENI
RETMEN
ST_KURUMLAR
FACT_PERS_UOE12
Annuall
y
Yes
FACT_PERS_ENRL
Annuall
y
Yes
FACT_UOE_BILGILERI
Annuall
y
Yes
FACT_KURUM_OGR_OGRET
MEN_ETL_SJOB
PKG_ETL_UOE
FACT_KURUM_OGR_OGR
ETMEN
FACT_MTSAS_BASVURU
_ETL_SJOB
PKG_ETL_YAYGIN
FACT_MTSC_BASVURU_E
TL
FACT_MTSAS_SERTIFIKA
_ETL_SJOB
PKG_ETL_YAYGIN
FACT_MTSC_SERTIFIKA_E
TL
FACT_YAYGIN_KURS_BLG
_ETL_SJOB
PKG_ETL_YAYGIN
FACT_YAYGIN_KURS_BLG
_ETL
FACT_YAYGIN_KURSIYER_B
LG _ETL_SJOB
PKG_ETL_YAYGIN
FACT_YAYGIN_KURSIYER
_BLG_ETL
FACT_YAYGIN_PERSONEL_B
LG _ETL_SJOB
PKG_ETL_YAYGIN
FACT_YAYGIN_PERSONEL
_BLG_ETL
BI_TEFBIS_FINANS_GELIR
PKG_ETL_FINANS
FINANS_STAGE_LOAD
ST_YAYGIN_SERTIFIKA_
TIPI_MV
ST_YAYGIN_KURS_DUR
UMU_MV
ST_YAYGIN_KURS_TIPI_
MV
ST_YAYGIN_KURS_ACM
A_BICIMI_MV
ST_YAYGIN_OGRENIM_D
URUMU_MV
ST_YAYGIN_ENGEL_DUR
UMU_MV
ST_YAYGIN_CALISMA_D
URUMU_MV
ST_YAYGIN_MEDENI_DU
RUMU_MV
ST_YAYGIN_BASARI_DU
RUMU_MV
ST_YAYGIN_PERSONEL_
STATUSU_MV
ST_YAYGIN_BRANSLAR_
MV
T_KURUM_OGR_OGRETMEN
GILERI
LERI
FACT_KURUM_KULLANIM_AL
AN
ST_KURUMLAR
ILSISWEB.BI_MTSAS_BASVU
RU
ST_MTSC_EGITIM_DURUMU
ILSISWEB.BI_MTSAS_SERTIFI
KA
ST_MTSC_EGITIM_DURUMU
ILSISWEB.BI_FACT_YAYGIN_
KURS_BLG
FACT_KURUM_OGR_OGR
ETMEN
Manuall
y
FACT_MTSAS_BASVURU
Semiannuall
y
Semiannuall
y
Semiannuall
y
KURSIYER_BLG
FACT_YAYGIN_KURSIYER
_BLG
Semiannuall
y
PERSONEL_BLG
FACT_YAYGIN_PERSONE
L_BLG
Semiannuall
y
ILSISWEB.BI_TEFBIS_FINANS
BI_TEFBIS_FINANS_GELI
Annuall
FACT_MTSAS_SERTIFIKA
FACT_YAYGIN_KURS_BL
G
_ETL_SJOB
BI_TEFBIS_FINANS_GIDER
_ETL_SJOB
BI_TEFBIS_OZEL_GELIR
_ETL_SJOB
BI_TEFBIS_OZEL_GIDER
_ETL_SJOB
BI_EBUTCE _ETL_SJOB
BI_BELEDIYE _ETL_SJOB
PKG_ETL_FINANS
FACT_TEFBIS_FINANS1
_ETL_SJOB
FACT_TEFBIS_FINANS2
_ETL_SJOB
PKG_ETL_FINANS
_TEFBIS
FINANS_STAGE_LOAD
_TEFBIS
FINANS_STAGE_LOAD
_TEFBIS
FINANS_STAGE_LOAD
_TEFBIS
FINANS_STAGE_LOAD
_EBUTCE
FINANS_STAGE_LOAD
_BELTAB
FACT_TEFBIS_FINANS1
PKG_ETL_FINANS
FACT_TEFBIS_FINANS2
FACT_TEFBIS_FINANS_OZEL
_ETL_SJOB
FACT_TEFBIS_FINANS1_UOE
_ETL_SJOB
PKG_ETL_FINANS
_ETL_SJOB
PKG_ETL_FINANS
FACT_EBUTCE_FINANS1_ET
L_SJOB
FACT_EBUTCE_FINANS2_ET
L_SJOB
FACT_EBUTCE_FINANS1_BE
LTAB _ETL_SJOB
FACT_EBUTCE_FINANS2_BE
LTAB _ETL_SJOB
FACT_EBUTCE_FINANS1_UO
PKG_ETL_FINANS
FACT_TEFBIS_FINANS_OZ
EL
FACT_TEFBIS_FINANS1_U
OE_IO
OE_MEM
OE_IO
OE_MEM
OE_OZEL
FACT_EBUTCE_FINANS1
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
PKG_ETL_FINANS
_GELIR
ILSISWEB.BI_TEFBIS_FINANS
_GIDER
ILSISWEB.BI_TEFBIS_OZEL_G
ELIR
ILSISWEB.BI_TEFBIS_OZEL_G
IDER
ILSISWEB.BI_EBUTCE
R
BI_TEFBIS_FINANS_GIDE
R
BI_TEFBIS_OZEL_GELIR
ILSISWEB.BI_BELEDIYE
BI_BELEDIYE
FACT_TEFBIS_FINANS1
BI_EBUTCE
FACT_TEFBIS_FINANS2
y
Annuall
y
Annuall
y
Annuall
y
Annuall
y
Annuall
y
Annuall
y
Annuall
y
FACT_TEFBIS_FINANS_O
ZEL
FACT_TEFBIS_FINANS1_
UOE
Annuall
y
Annuall
y
ST_OGRYIL_ISCED_VIE
W
T_UOE_TANIM_TABLOSU
FACT_TEFBIS_FINANS1
ST_ISCED_FINANS
ST_OGRYIL_ISCED_VIE
W
T_UOE_TANIM_TABLOSU
FACT_TEFBIS_FINANS2
ST_ISCED_FINANS
FACT_TEFBIS_FINANS2_
UOE
Annuall
y
BI_EBUTCE
FACT_EBUTCE_FINANS1
FACT_EBUTCE_FINANS2
BI_EBUTCE
FACT_EBUTCE_FINANS2
FACT_EBUTCE_FINANS1_
BELTAB
BELTAB
BI_BELEDIYE
BELTAB
BELTAB
Annuall
y
Annuall
y
Annuall
y
Annuall
y
Annuall
BI_BELEDIYE
ST_OGRYIL_ISCED_VIE
T_UOE_TANIM_TABLOSU
Yes
Yes
Yes
E_ETL_SJOB
UOE
UOE_BELTAB
W
E _ETL_SJOB
PKG_ETL_FINANS
UOE
UOE_BELTAB
ST_OGRYIL_ISCED_VIE
W
BI_HANEHALKI_ANALIZ_ETL
_SJOB
FACT_HANEHALKI_FINANS1
_UOE _ETL_SJOB
FACT_FINANS_ETL_SJOB
-
-
-
PKG_ETL_FINANS
FACT_HANEHALKI_FINAN
S1_UOE
FACT_FINANS_TABLO_OL
USTUR
PKG_ETL_FINANS
FACT_EBUTCE_FINANS1_BEL
TAB
FACT_EBUTCE_FINANS1
ST_ISCED_FINANS
T_UOE_TANIM_TABLOSU
FACT_EBUTCE_FINANS2_BEL
TAB
FACT_EBUTCE_FINANS2
ST_ISCED_FINANS
-
UOE
y
UOE
Annuall
y
BI_HANEHALKI_ANALIZ
BI_HANEHALKI_ANALIZ
FACT_HANEHALKI_FINAN
S1_UOE
FACT_FINANS
Manuall
y
Annuall
y
Annuall
y
E
E
FACT_HANEHALKI_FINANS1_
UOE
Yes
1.4. IMPORTANT NOTES
1.4.1. CACHE STRUCTURE OF ORACLE BI
There are two main cache method in the Oracle BI tool; data cache and presentation
cache.
Cache is a usefull method for performance tuning but after data tarnsformation into
fact tables cache needs to be cleared. The administartor of the BI system must clean
the cache from 'Cache' item in 'Manage' menu like in the figures below. Administrator
should choose cache etries from the opened cache manager and pressing delete
button from keypad, choosen cache entries will be deleted.
FIGURE 259 Cache MAnager Menu Item in Oracle BI Administrator
FIGURE 260 Cache Manager
For clearing presentation cache the services of the BI system must be closed and
restarted. The stop and start batch files are stated in the desktop of the application
server. PResentation cache can be bypassed for each report by checking 'Bypass
Oracle BI Presentation Services Cache' combobox like in the figure below.
FIGURE 261 Presentation Cache Bypass Atribute in Analysis
1.4.2. INDEXES IN MATERIALIZED VIEWS
For the formal education student data which queried from e-school system summary
tables, the transformation phase can be need more time. To be able to query source
table efficiently, some table indexes needs to be created. the used indexes are given
below, after refreshing materialized view sources, indexes must be created again.
The indexes given below should be checked before the data transformation phase of
e-school data;
Index Name
Table/Materialized View Name
Columns
I_BI_LISE_OGRENCI_BILGILERI
OKULSIS.BI_LISE_OGRENCI_BILGILERI
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_LISE_AKTIF_SINIFTA_KALAN
OKULSIS.BI_LISE_AKTIF_SINIFTA_KALAN
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_LISE_AKTIF_OH_KULLANMAYAN
OKULSIS.BI_LISE_AKTIF_OH_KULLANMAYAN
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I BI_LISE_OGR_GECMIS_DURUM
OKULSIS.BI_LISE_OGRENCI_GECMIS_DURUM
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_LISE_SINIF_TEKRAR
OKULSIS.BI_LISE_SINIF_TEKRAR
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_ILK_OGRENCI_BILGILERI
OKULSIS.BI_ILK_OGRENCI_BILGILERI
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I BI_ILK_OGR_GECMIS_DURUM
OKULSIS.BI_ILK_OGRENCI_GECMIS_DURUM
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_ILK_AKTIF_SINIFTA_KALAN
OKULSIS.BI_ILK_AKTIF_SINIFTA_KALAN
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
I_BI_ILK_SINIF_TEKRAR
OKULSIS.BI_ILK_SINIF_TEKRAR
Islem_tarihi
Donem
Kurum_kodu
Kurum_turu
1.4.3. PARTITIONS IN FACT TABLES
All fact table and ST_KURUMLAR dimension table contains relevant partitions. Some
fact tables have subpartitions also. The main (first) partition is a range partition, so
when a new partitioned item comes relevant partition can be added automaticly. But
subpartitions must be in list partition type, so when the last list item will reached new
partition elements must be added manually by the BI administrators of MoNE.
1.4.4. PERFORMANCE TUNING OF BI SYSTEM
The main table which is used in all queries is ST_KURUMLAR. This table covers
each institution records in historical order for each month started from January of
2006. For taking quick response from the database this table should be located in
'keep cache' part of the database storage. With this optimization disk I/O rates will be
decreased and query response times will be decreased. 'keep cache' suggestion was
described to MoNE IT DBA experts from TAT. This situation was also stated in
'Activity Summary Document' of database and data warehouse administration
advisor under '2.3 Need for "Keep Cache" Usage for Monestat.ST_KURUMLAR
Table' section.
For the performance issue, it is recommended to use seperate database servers for
data warehouse applications. OLTP and analytical applications should not run in the
same server as OLTP and analytical databases have different workloads and needs
different system parameters. It is recommended that , Monestat schema should have
a seperate database instance of its own.
Section F.
1
USE OF ESTIMATIONS
USE OF ESTIMATIONS
1.1
INTRODUCTION
This chapter aims at providing theoretical as well as practical guidelines about estimation
methods.
Estimation is becoming more and more important in the UOE data collection framework. As
recalled in the UOE Manual, Countries should make every effort to provide complete data.
As such they are strongly encouraged to make estimations of missing or incomplete data.
Recently, in 2010, a specific project in Eurostat has been developed in order to inventory all
estimation methods in use by countries for the UOE questionnaires completion.
In addition, from 2012 onwards countries will be requested to fill in the so-called “quality
report” regarding the quality of data (metadata – see Chapter 10 on Quality issues). In the
quality report, a section is devoted to estimation methods used for the UOE tables
completion.
The estimation topic is closely connected with data gaps (missing data) in the (mostly)
administrative data that feed UOE questionnaires. For that reason, identification of data gaps
in Turkish UOE questionnaires (last data available at the moment of drafting this report, i.e.
reference year 2009 for non-finance data; 2006 for finance data) will represent a substantial
part of this chapter in the final PG.
In a first section, general principles and taxonomy of estimation needs are provided. In
subsequent sections, practical guidelines are suggested in concrete relation with the Turkish
case. In that perspective, a detailed analysis of Turkish UOE questionnaires as well as other
(national) Statistics has been performed to identify the Turkish estimation needs.
1.2
ESTIMATION METHODS : GENERAL GUIDELINES AND TAXONOMY
A recent study carried out by Eurostat in 2010 aims at reporting estimation methods used by
countries when completing UOE questionnaires. Results were discussed in a subsequent
workshop. This project lead to general guidelines and a taxonomy of estimation methods we
will refer to throughout the chapter.
1.2.1
TAXONOMY OF ESTIMATION METHODS
The Eurostat study lead to the identification four main categories of estimation, with their
respective subdivisions:
1. Mathematical conversions;
2. Sample-based estimations;
3. Population-based estimations;
4. Statistical modelling;
1. Mathematical conversion based methods
A mathematical conversion generally consists in applying a transformation to change the
measurement unit. For instance, the linear equation TF = 32 + 1.8 TC expresses a Celsius
temperature on the Fahrenheit scale. Such rules are often arbitrary.
When the mathematical conversion rule is arbitrary, this may be misleading in the estimates
obtained. For example, it is common practice to convert part-time teaching staff into full-time
equivalents (FTEs) using the conversion rate of 0.50 (i.e. 1 part-time equals 0.50 full-time).
In other words, on average, 1 part-time teacher is assumed to work half-time. However, this
arbitrary rule might not hold in all national contexts and, above all, might not be equally true
for all ISCED levels or orientations or genders.
Austria, which recently moved from aggregated data to individual data, can now validate or
invalidate several assumptions that had been made previously when no individual data were
available. Within this improved data collection system, Austrian Statisticians
computed the FTE conversion factors, by ISCED level and by gender. Results are presented
in Table 4.
These results clearly show that the part-time/full-time conversion rate varies by sex. As
expected, if on average there are few differences across ISCED levels, substantial
differences between genders do exist. It therefore invalidates a fixed conversion ratio, as it
varies at least according to gender. Furthermore, as the percentage of women is usually
higher in lower ISCED levels, the bias will differ according to the ISCED level. In Table 4, the
bias was computed as the difference between the actual value and the estimated value; the
difference is expressed as a percentage of the actual value. As a result, a positive bias
denotes an overestimation, while a negative bias denotes an underestimation of the number
of FTE part-time teachers. Concretely, according to the 2007 data, the use of the 0.50
conversion rule might have led to an underestimation in the number of FTE staff, particularly
among women. To a lesser extent, this underestimation also varies according to the ISCED
level (more accurate estimation in technical and vocational schools). Such an
underestimation would also affect the pupil/FTE teachers ratio, as this EU key indicator
would be overestimated.
Table 4: Teachers’ employment rate in Austria by ISCED level and gender
Actual conversion rates (2009)
ISCED Level
Female
Male
Total
Primary schools (Volksschule) (ISCED 1)
0.63
0.40
0.61
Lower secondary schools (Hauptschule) (ISCED 2)
0.65
0.58
0.64
Academic secondary schools (ISCED 2&3G)
0.63
0.52
0.60
Technical and vocational schools (spanning ISCED 3&4) 0.57
0.44
0.53
Number of PT teachers in terms of FTEs: 2007 data using 2009 conversion rates
ISCED Level
Female
Male
Total
4215
272
4487
5085
939
6024
6156
1201
7357
Technical and vocational schools (spanning ISCED 3&4) 2507
1026
3533
FTE as converted from PT teachers: ESTIMATED (2007 data: rule: 1 PT = 0.5 FTE)
ISCED Level
Female
Male
Total
3345
340
3685
3912
810
4722
4886
1155
6041
Technical and vocational schools (spanning ISCED 3&4) 2199
1166
3365
Bias (actual value – estimated value, in %)
ISCED Level
Female
Male
Total
-21 %
25 %
-18 %
-23 %
-14 %
-22 %
-21 %
-4 %
-18 %
Technical and vocational schools (spanning ISCED 3&4) -12 %
14 %
-5 %
It can be shown that such an arbitrary conversion rule may have different effects depending
on the national context. Table 5 reports actual data on FTE part-time teachers from three
other countries (the French-speaking Community of Belgium, Germany and the United
Kingdom) and compares them to what would be obtained if the 0.50 conversion rule was
used instead. The bias (actual figure minus estimated value) is expressed as a percentage
of the actual value and, again, can be positive (overestimation) or negative
(underestimation).
For example, in the French-speaking Community of Belgium as in the United Kingdom,
(nearly) all actual conversion rates are less than 0.50, meaning that, on average, part-time
teachers work less than half-time. As a result, the use of the 0.50 rule would have led to a
positive bias, that is an overestimation of the FTE part-time teachers and to an
underestimation of the pupil/FTE teachers ratio. In Belgium, this overestimation would have
been especially large at ISCED 0-1, while in the United Kingdom the ISCED 3 level would
have been the most affected. In contrast, in Germany the number of part-time teachers in
terms of FTEs would have been underestimated in general (males and females), except at
ISCED 4. It can be seen that the bias would have been different according to the gender
taken into consideration: the number of women would have been underestimated, whereas
the number of men would have been overestimated.
Table 5: Simulated estimations (0.50 conversion rule) versus actual data for three countries, by
ISCED level and gender
BEfr, 2008 data, Total public and private institutions
ISC0-1
ISC2-4
Actual conversion rate PT - FTE
Females
Males
Total
0.22
0.30
0.23
0.44
0.55
0.49
Potential bias ( %)
Females
130 %
13 %
Males
64 %
-9 %
Total
118 %
3%
DE, 2008 data, Total public and private institutions
ISCED 0
ISCED 1
ISCED 2
ISCED 3
ISCED 4
0.60
0.26
0.57
0.66
0.33
0.58
0.66
0.43
0.58
0.50
0.32
0.43
-25 %
16 %
-14 %
1%
55 %
17 %
ISCED 4
Females
Males
Total
0.69
0.70
0.69
Potential bias ( %)
Females
-28 %
-16 %
-24 %
Males
-29 %
96 %
50 %
Total
-28 %
-12 %
-14 %
UK, 2005 data, Total public and private institutions
ISCED 0
ISCED 1
ISCED 2
ISCED 3
0.41
0.22
0.38
0.50
0.39
0.47
0.31
0.24
0.29
22 %
125 %
31 %
1%
29 %
6%
61 %
107 %
73 %
Females
Males
Total
0.40
0.44
0.41
Potential bias ( %)
Females
Males
Total
23 %
14 %
23 %
2. Sample based methods
Some countries at some stage used survey results to complete the UOE questionnaires.
France, for instance, is conducting 14 different surveys to collect information on ISCED 5
and ISCED 6. Recently, Spain has conducted a survey designed for the breakdown of
teachers by ISCED level and by sex. The breakdown by ISCED level takes into account the
number of teaching hours in the respective levels.
The household survey is certainly the most frequent source of data observed in a sample.
Strictly speaking, survey data should be considered as an estimation because what is
observed in a sample is generalised to the whole population. If the target population is
clearly defined and entirely covered, if the sample has been drawn randomly according to a
sampling design that is scientifically consistent with the sampling theory and if the response
rates tend to 100 % of participation, this generalisation does not make any assumption.
However, as will be discussed in this section, these different methodological conditions are
generally not met. Use of survey data is therefore not as straightforward as one would
expect and Statisticians using such data should read the technical reports and appendices
carefully.
First of all, survey results might be reported at a particular level and using these results for
reporting at another level might generate substantial biases. For instance, transferring
percentages from the school level to the student level assumes that the correlation between
the school size and the observed characteristic is equal to 0. Table 6 illustrates this issue: it
presents the percentages of schools and the percentages of students by school type (private
independent schools, private dependent schools and publics schools). In several countries,
the percentages of schools do not differ substantially from the percentages of students
attending such schools, whereas in the Flemish Community of Belgium, Denmark, Spain,
Ireland, Italy, Hungary, Portugal, Sweden, the United Kingdom and Liechtenstein, the
difference between the student and the school percentages is greater than 5 %.
This discrepancy can be quite substantial. For example, only 57 % of schools in the Flemish
Community of Belgium are private dependent establishments, but about 70 % of students
attend this type of school.
Table 6: Percentage of schools and percentage of students by type of school (PISA 2006)
Country
EU-27
BE fr
BE de
BE ge
CZ
DK
DE
EE
EL
ES
IE
IT
LV
LT
LU
HU
NL
AT
PL
PT
RO
SI
SK
FI
SE
UK_
UK_SCT
IS
LI
NO
TR
Percentages of schools
Private
Private
independent
dependent
4.0
11.1
1.0
58.0
3.1
57.5
50.0
1.0
4.2
1.0
30.1
1.2
7.7
0.3
4.0
2.5
12.6
34.5
2.3
50.7
7.9
3.3
3.1
1.0
2.3
8.7
0.2
0.3
18.1
5.2
0.9
16.7
0.4
19.4
7.2
67.1
13.0
3.9
4.3
0.6
11.3
6.8
27.0
0.1
0.7
1.8
6.4
0.2
Public
84.9
41.0
39.4
50.0
94.8
68.8
91.1
95.7
97.5
52.9
47.1
88.8
100.0
99.6
80.6
89.7
32.9
86.0
93.8
87.0
100.0
99.2
88.3
93.2
73.0
81.7
94.2
97.4
83.3
93.6
99.8
Percentages of students
Private
Private
independent dependent
2.5
9.9
1.4
56.0
3.3
69.6
50.2
0.2
3.5
1.1
22.8
0.2
5.5
0.6
1.4
5.1
10.1
24.6
3.4
54.8
2.4
1.2
2.7
0.9
0.6
2.1
0.1
0.5
6.2
4.1
0.1
7.1
0.7
14.4
13.1
67.0
8.4
1.0
6.9
2.3
7.2
2.4
8.3
0.1
1.2
1.0
1.9
0.5
Public
87.6
42.6
27.1
49.8
96.2
76.1
94.3
98.1
94.9
65.3
41.8
96.4
100.0
99.3
85.6
84.2
33.0
90.7
98.4
91.1
100.0
97.7
92.3
97.6
91.7
93.7
94.7
98.9
92.9
98.1
99.5
In one of the visited countries, the national agency has asked a private research institute to
conduct a survey on a representative sample of schools to assess the nature and extent of
language learning at schools. The results of this survey are used to fill in some parts of the
language questionnaire files. For instance, estimates for the number of primary (ISCED 1)
students studying modern foreign languages and the number of students studying 1, 2, 3 & 4
and more foreign languages are based on proportions taken from the research.
It is also of prime importance to take into account non-response in the methodological
evaluation of the survey. In education surveys, the magnitude of school and student nonresponse is reported through school and student response rates; in this respect the IEA and
PISA surveys have set up minimum non-response rates for the final adjudication on the
national data. For instance, PISA requires a school participation rate of 85 % and a student
participation rate of 80 %. Countries that do not reach these thresholds will be
either flagged in the international publications (IEA), or simply not reported (PISA). Such a
sampling adjudication process is quite recent in the history of education surveys.
3. Population-based methods
Population-based estimations can be defined as the application or the transfer of observed
figures from one sub-population to another sub-population for which figures are not known.
These estimation methods therefore assume that the different sub-populations are similar for
the characteristics involved in the process.
For instance, the sheet “PERS1” in the personnel UOE questionnaire data file requires
countries to provide the number of classroom teachers, by (i) level of education, (ii)
programme orientation, (iii) sex, (iv) age, (v) type of institution and (vi) employment status.
Countries usually have teacher data at the individual level for public schools and private
dependent schools (as in France and Belgium), since teachers working in both types of
institutions are paid directly by a public institution. By contrast, countries usually hold only
aggregated data on teachers working in private independent schools.
It is quite common that countries will for instance apply the teacher share by sex observed in
public and private dependent schools to private independent schools. This estimation
assumes the independence between the distribution of teachers by sex and the distribution
of teachers by type of institution.
Some countries do not even have aggregated data on the total number of teachers working
in private independent schools. They might for example apply a rule of three to estimate the
total number of teachers. If X 1 ,Y1 respectively represent the number of students and the
number of teachers in public and private dependent schools in a given level of education,
and if X 2 ,Y2 represent their counterparts in private independent schools, and assuming X 2
is known, an estimate of Y2 can be obtained as follows: Y2 
Y1
X 2 . This estimation
X1
involves two units of information: the student unit and the teacher unit. The underlying
assumption of the estimation is the equivalence of the student/teacher ratio across institution
types. Mathematically, the assumption can be written as:
X1 X 2
.

Y1
Y2
Another example relates to the PERS2 questionnaire. In France, the Ministry of Education
pays the salaries of the personnel working in public schools and in private dependent
schools. However, the data file for the private dependent sector does not make a distinction
between teachers, school principals, school management personnel or teacher aides. The
“PERS2” sheet in the personnel questionnaire data file requests data on school
management and teacher aides by educational level and by sex. Figures from public schools
are applied to the personnel data from the private sector. It is assumed that public schools
are, on average, of the same size as private schools. This is not a strong assumption as the
cross-tabulation “classes by schools” is known for both sector. It also assumes a similar
interaction between (i) types of institutions and (ii) sex and position of personnel in the
schools.
In Germany, data on foreign students for several types of schools are only available for the
total and are not broken down by ISCED level (Berufsschulen, Berufsfachschulen,
Fachoberschulen). The distribution of foreign students by ISCED level is estimated
according to the shares of all students in these programmes in the different ISCED levels.
The underlying assumption is that the distribution of foreign students for the respective types
of schools by level is the same as for all students.
These examples illustrate the diversity of the estimation methods. The breakdown can be
based on a previous distribution or on an arbitrary rationale. However, the most frequent
rationale is to apply the distribution observed in one sub-population (males, ISCED level 1,
public institutions, etc.) to another sub-population, assuming the two sub-populations are
similar.
4. Statistical modelling
The last category of estimations called ‘Statistical modelling’ has been rarely encountered,
except for adjustments for inflation in the financial data. In the other UOE questionnaires,
such modelling is rarely implemented.
The estimation methods in this category are classified as follows:
1. Modelling on aggregated data;
a. Time series
b. Adjustment for inflation
c. Independence between marginal distributions
2. Individual data
a. Hot-deck imputation
Modelling on aggregated data: time series
Recently, Statistics Canada has developed and implemented estimations for the UOE data
collection. Basically, the reason for these estimations lies in the lack of timeliness of some
institutions in their data reporting. For instance, college graduates estimations between 2001
and 2006 were based on historical completion rates, computed by type of programme and
gender. As regards the reference year 2006, at the university level (ISCED 5A and 6)
graduates were estimated by linear multiple regressions, in which 2006 graduates were
predicted by the number of graduates in 2003, 2004 and 2005, and enrolments in 2004,
2003 and 2002.
It should be noted that such predictors are highly correlated (notably due to the imputation
method used for those years) and that associated multi-collinearity problems could occur.
For example, the method used for the selection of predictors (backward selection) could be
sensitive to a high level of multi-collinearity, like the regression coefficients. The models
were computed at different levels, using classification variables deemed as relevant to
increase the accuracy of predictions (by province, by CIP — a North American classification
of fields — , by type of programme, i.e. Bachelor, Master, Doctorate, and more rarely by
institution). In a final step, all actual and estimated data were aggregated and treated as
completed.
Secondly, when such methods of estimation are implemented, non-linearity should be tested
in order not to restrict the Statistical modelling to non-linear relationships.
Adjustment for inflation
In most of the visited countries, at some stage, parts of the financial data have been
adjusted for inflation by the using the Consumer Price Index. This inflation adjustment mainly
concerns private expenditure (private independent institutions and household expenditure on
education), as data are usually collected via surveys that are not conducted annually.
Independence between marginal distributions
In Germany, the distributions of enrolment data in special schools by ISCED level and by
grade are provided separately. As the UOE questionnaire on enrolment requires these two
criteria to be cross-tabulated, German Statisticians assume their Statistical independence
and the cells within the cross-tabulation can simply be filled in by multiplying the
corresponding column and row marginal totals and then dividing by the total enrolment.
Germany also implements this estimation method, with a few differences, for the breakdown
of enrolment data in some vocational schools by ISCED level and by grade. In Bulgaria,
independence is also assumed between sex and age for enrolments in grade 1 (ENRL4).
Indeed, the marginal distributions for age and for sex are known, but not for each cell of the
cross-tabulation. Such independence is also assumed for graduate figures at ISCED 3.
Hot-deck imputation
Statistics Canada intended to implement hot-deck imputation at the ISCED 5A and 6 levels,
with some data serving as donors for imputing missing micro-data (individual records).
Those imputations are essentially made to fill in missing data for some institutions in the
short run. Unfortunately, so far no comparison between estimated and actual data has been
undertaken to assess the validity of those methods.
1.2.2 GENERAL RECOMMENDATIONS
The Eurostat project led to the following conclusions.
Since each national situation is specific, it is not possible to provide detailed advice
regarding when estimations should or should not be used. However, some general principles
can be mentioned.
The following hierarchy (by decreasing order of preference) should be preferred:
1. Real data (when they correspond to the definition and measure required in the UOE
manuals);
2. Estimations;
3. Missing data.
Estimation should be preferred to missing data when:


Estimation improves compliance with definitions and measurements as required by
the UOE manuals;
Estimation aims at limiting under-coverage (i.e. in case of missing sub-populations).
Moreover, estimation should preferably be implemented when it aims at excluding double
counting and should preferably be performed for the following breakdowns:
 Breakdowns by ISCED level;
 Breakdowns by age;
 Breakdowns by sex;
 Breakdowns by type of institutions: public, private government-dependent and private
independent.
Finally, it is recognised that estimation should be avoided when data are not available for an
entire table of the UOE questionnaires.
Considering the above general principles, more specific conclusions were drawn on two
main issues:
 flagging and documenting information;
 checking the validity of the estimation methods as well as their underlying
assumptions;
Regarding the former one, the ISO norms have integrated the traceability concept, which is
why it would be necessary to fully document the data production. The recently developed
Quality Report requests from all all EU Member States and EFTA countries to
1. locate the data cells involved in the estimation (questionnaire, sheet, column and
row);
2. provide the reason for the estimation;
3. describe the estimation method, including underlying assumptions.
Writing down assumptions contributes to the assessment of the estimations in terms of
plausibility and accuracy. Furthermore, this makes it possible to highlight assumptions that
can be avoided by using another estimation method.
Concerning the validity of underlying assumptions, it was concluded that countries should
also develop strategies to check the validity of estimation methods. For instance, data on
public expenditure in education are not difficult to collect on an annual basis, whereas
private expenditure is usually estimated from surveys that do not take place every year.
Private expenditure data are therefore adjusted by the Consumer Price Index and by student
enrolment figures. It would be easy to estimate public expenditure using enrolment and
inflation adjustments and then compare the estimates with the real figures. This would make
it possible to assess the accuracy of the estimation method in a country. International
databases on educational surveys such as PIRLS/TIMSS and PISA can also be used to
verify certain assumptions. For instance, these surveys usually collect information on class
size, teacher qualification and so on. As such surveys include public and private institutions,
the use of public figures on private data can to some extent be tested with these
international databases.
As a general principle, any estimation should minimise the underlying assumptions. For
instance, the breakdown of expenditure between ISCED levels based on teacher population
is more valid than the estimation based on student figures, as the former does not assume a
constant pupil/teacher ratio. In this context, it can be stated that sample-based or populationbased estimations should be preferred to mathematical conversions.
The validity of the estimation method can be checked either by the results it provides (for
example, it was observed in some countries that teacher salaries were lower at ISCED 2
than at ISCED 1, indicating a potentially problematic estimation method) or, above all, by its
basic features. For example, as far as sample-based surveys are concerned, Statisticians
using them should be aware of the survey methodology, including the sampling rate, sample
size and response rates. For instance, survey data are used extensively by countries to
estimate private expenditure in education. If the response rates of such surveys are low, the
data should be used with caution.
1.2.3 SPECIAL FOCUS ON INTERNAL ESTIMATION METHODS AND UNDERLYING
ASSUMPTIONS
It has to be borne in mind that we focus here on what can be estimated using UOE
information already available, that is “internal methods of estimation”. The term “internal
method” refers to Eurostat definition recently adopted for the UOE Quality Report, that is
when the estimation can be performed using other information present in the UOE
questionnaires (in contrast with external, e.g. an independent survey). In reference to the
taxonomy reported above, they are therefore typically population-based.
As an example of external estimation method, it can be decided to launch a survey on a
representative sample of households (or by using an existing one, such as LFS) to estimate
the expenditure of parents on their children education. Virtually all missing data can be
estimated by an (external) ad-hoc sample-based survey designed to get the unavailable
data. So that it would not be informative to provide such guidelines. Instead, we will try to
find internal methods, more easily implemented. When sampling methodology and data
collection are reliable, accuracy and reliability of estimates is far better than estimates
obtained by the so-called “internal estimation methods”. However, the latter can be preferred
for saving time, energy and money.
An example of internal estimation method used in one European country was the following.
As the gender breakdown at ISCED 0 was missing, the number of girls aged 3-5 at ISCED 0
was estimated by applying to this age group the gender structure of 5-10 year-olds enrolled
at ISCED 1, where the percentage of females was available. Such a method obviously relies
on assumptions, notably the fact that the percentage of females/males remained stable
across both age groups.
Such underlying assumptions should always be explicitly documented when using estimation
methods (see chapter on Quality issues) and their validity assessed, at least in terms of
plausibility. Actually the validity of underlying assumptions depends on national specificities.
In the example, the underlying assumption can be deemed as valid in a country where
(almost) 100% of the 3-5 year-olds are enrolled at the ISCED 0 level of education. However,
it might be misleading in a country where the participation at ISCED 0 is low. Indeed, it might
be that more boys attend ISCED 0 programmes than girls do, for any reason.
To sum up, proposing an estimation method should always be made with regard to the
assumption(s) on which it relies, as well as an examination of the validity of that/those
assumption(s).
1.3
IDENTIFICATION OF ESTIMATION NEEDS IN TURKEY
Broadly speaking, two kinds of situation can lead to estimation methods needs. On the one
hand, estimation needs can appear in relation with coverage issues, typically in case of
undercoverage. For example, it may turn out that summer kindergarten have not been
included in the UOE Statistics on pre-primary education: if data are not available, estimates
can be computed whenever possible. Identification of such undercoverage issues requires to
be well informed about the background of the provided data and is therefore not easy and
reliable. On the other hand, estimation needs can arise from a missing breakdown or level of
disaggregation. For example, data can be available for all males and females as a whole,
but not for males or females separately.
As stated above, for the practical guidelines purpose, only internal methods are considered.
For each identified data gap, the feasibility of implementing such an internal estimation
method will be assessed, taking national specificities (UOE data availability as well as
contextual information) into account.
Ideally, the identification of data gaps in the Turkish questionnaires should have been made
through the last UOE questionnaires sent to international data requesters. Howevere, due to
the recent and huge improvements in data collection and processing in Turkey, this
procedure was deemed as obsolete.
Instead, at the occasion of a workshop held in Ankara in March 2012, national experts were
requested to suggest the most appropriate procedures with regard to the underlying
assumptions underlying some suggested estimation methods. The aim of this workshop was
two-fold:
a) Make the participants aware that data gaps are not a fatality and can be filled in by
estimations (and they are even encouraged by international institutions);
b) Make the participants aware of the assumptions that are necessarily underlying any
estimation methods: they should be able to identify them, formulate them clearly and,
if possible, document their validity.
Four main areas have been identified as requesting some estimation methodology:
1) the spanning ISCED 1-2 educational programmes (called “Primary school”) to be split
into ISCED 1 and ISCED 2 for UOE reporting purpose;
2) splitting the personnel data within ISCED levels for staff in the central body of MoNE,
district and province directorates of MoNE;
3) splitting the administrative and support staff (i.e. staff other than teaching staff)
between ISCED levels in combined schools;
4) splitting educational expenditures within ISCED levels between ISCED levels in
combined schools.
The following issues have been identified.
1.4
PRACTICAL GUIDELINES FOR ESTIMATIONS
From the list of data estimation needs (previous section), and the study of feasibility for
implementing internal estimation methods, the following guidelines can be provided here.
As stated above, for the practical guidelines purpose, only internal methods are considered.
As much as possible, special attention is paid to underlying assumptions.
1.4.1 SPLITTING THE ISCED SPANNING LEVELS 1-2
The main data gap identified as potentially filled in by an internal estimation method consists
in the lack of data for the ISCED level 2 (lower secondary education). The Turkish system is
organized in such a way that “Primary school” in the Turkish sense actually encompasses
both ISCED levels 1 (primary) and 2 (lower secondary). Other European systems share a
similar structure (e.g. Sweden) and use estimates for the same international purpose.
For international reporting purposes, it is recommended to split Primary schools programmes
and Statistics into two ISCED levels, as clearly specified in the new ISCED 11 Manual:
“A national educational programme with a duration exceeding the duration criteria provided
for ISCED levels is considered as spanning more than one level. It is therefore necessary to
identify the transition point (or points) from one ISCED level to the next within the course of
the programme according to the level criteria. For example, when a national primary
education programme lasts for eight years or longer, the final grades are to be classified as
ISCED level 2.”
It should be noted that already in the OECD manual on ISCED97 imptementation from
1999, Turkey was adviced to split the Turkish primary school into two levels (1 and 2).
Here are suggested practical guidelines to disaggregate Statistics by ISCED levels 1 and 2,
in two sets: a) find the cut point between the two levels and b) propose data treatment to
disaggregate the provided data.
a) Transition point
Several elements found in national practices and publications are favourable to a possible
split between grades 1-5 (which would correspond to international level ISCED 1) and
grades 6-8 (ISCED level 2). Those elements are listed below.
According to the most recent ISCED mapping sent to Eurostat, some programmes – e.g.
Açık İlköğretim (open primary school) or Konservatuar: Müzik ve Bale Okulu (Conservatory,
ballet and music school) – require entrant students to have achieved the grade 5 of the
regular primary education.
In grades 1-5 courses are basic and general. In grades 6-8 teachers and courses are
specialised by subject (e.g. mathematics). This corresponds exactly to the description given
in the ISCED 97 manual, as well as in the ISCED 11 draft version. Also, teachers have got
different qualifications according to the grades they are teaching.
It has to be borne in mind that matching the Turkish Primary school with the international
labels “ISCED 1” or “ISCED 2” does not alter the idea of a single-structured primary school
as defined at the national level. The same distinction has e.g. been made by Sweden, even
though they claim for a single-structured primary school as well. Even though the ISCED
level 1 is often labelled “Primary education” in international education (notably in the UOE
questionnaires themselves), it is well specified that this is only a label, for example in the last
ISCED 11 manual, §123: “Programmes classified at ISCED level 1 are referred to in many
ways across the world, e.g. primary education, elementary education or basic education
(stage 1/lower grades if an education system has one programme that spans ISCED levels 1
and 2). For international purposes the term ‘primary’ is used to label ISCED level 1”.
As a result, for international purposes, it can be suggested to provide UOE data (on
enrolments, personnel, and possibly finance) separately for grades 1-5 and for grades 6-8.
E-school as well as e-staff modules collect data at the individual level and grades are
collected as well, so this separation of data appears entirely feasible.
1.4.2 ISCED BREAKDOWN FOR THE ADMINISTRATIVE AND SUPPORT STAFF IN
COMBINED SCHOOLS
The administrative and support staff (i.e. non-teachers) should also be reported by ISCED
level in the UOE data collection. This may be problematic in the Turkish combined schools.
The issue is therefore how to split this staff into the different ISCED levels when data come
from schools combining different ISCED levels. The issue remains even when considering
that grades 1-5 should be allocated to ISCED level 1 and grades 6-8 to ISCED level 2.
Indeed, most often non-teaching staff is not specifically devoted to specific grades (e.g.
grades 1-5) but work at the school level, therefore spanning ISCED levels 1 and 2.
The table below summarises the possible estimation methods to split those data by ISCED
level, as well as related underlying assumptions.
Suggested Methods
Underlying assumption
1. prorating staff data according to the number of
students in each ISCED level
administrative staff is proportional to the number of
students at each ISCED level
teachers in each ISCED level
teachers at each ISCED level
classes in each ISCED level
schools at each ISCED level
The first estimation method suggests that non-teaching staff workload should probably be
proportional to the number of students in the schools. In other words, this assumption means
that 10 non-teaching staff in a primary school with 600 pupils in grades 1-5 and 400 pupils in
grades 6-8 should be allocated to the ISCED levels 1 and 2 in the same proportions, i.e. 6 at
ISCED 1 and 4 at ISCED 2.
The national experts attending the workshop in March agreed that the number of students
should be used (method 1), as the assumptions underlying methods 2 and 3 are less valid.
1.4.3 ISCED BREAKDOWN FOR STAFF IN THE CENTRAL BODIES
The UOE data collection should include staff in the central body of MoNE, district and
province directorates. The issue is how to split this staff into the different ISCED levels as
requested by UOE. Indeed, in those bodies (for example the Directorate of Strategy
Development in MONE), there is no specific allocation to the different ISCED levels: most
staff work across several ISCED levels.
The table below summarises the possible estimation methods to split those data by ISCED
level, as well as related underlying assumptions.
Suggested Methods
Underlying assumption
students in each ISCED level
students at each ISCED level
teachers in each ISCED level
teachers at each ISCED level
schools in each ISCED level
3a. in case of schools, there are "combined schools"
which cover several ISCED levels (0/1/2) =>
second-stage estimation: for each combined school,
prorating administrative staff according to the
number of students in each ISCED level
3b. in case of schools, there are "combined schools"
number of teachers in each ISCED level
3c. in case of schools, there are "combined schools"
number of classes in each ISCED level
schools at each ISCED level
schools at each ISCED level, AND within schools to
the number of students
the number of teachers
the number of classes
The national experts attending the workshop in March expressed their opinion about the
validity of the different assumptions. According to them, the number of schools should be
used (method 3). However, there are some schools combining several ISCED levels
(typically ISCED 1 and 2). Therefore, as a second step, for schools combining several
ISCED levels, the number of students should be used to split the data into the different
ISCED levels (method 3a).
1.4.4 ISCED BREAKDOWN FOR EXPENDITURE IN COMBINED SCHOOLS
Schools combining several ISCED levels are also problematic when it comes to provide
expenditure by ISCED level. Here, what is suggested is to take into account the very nature
of the expenditure before choosing how to split them into the different ISCED levels.
Specifically, we suggest distinguishing expenditure into 4 types: expenditure at the building
level such as heating (assuming that one source of heating is used for the whole building),
consumption at the individual level (e.g. water), equipment for pedagogic purpose, and
capital expenditure such as construction of new buildings.
Regarding expenditure at the building level (heating, building maintenance), it is assumed
that the consumption depends on the volume and have nothing to do with the number of
students. For example, heatning consumption for a given class is supposed to be the same
whatever the number of pupils being educated in that room. As a result, it is suggested to
make ISCED breakdown estimations proportional to the number of classes at each ISCED
level.
As to expenditure at the individual level (e.g. water consumption), it is suggested to make
estimations aproportioned to the number of students at each ISCED level. Same rationale
regarding basic equipment (tables, chairs, etc.). However, it is strongly suggested to
distinguish more elaborated equipments such as microscopes or tools for mechanic courses,
since they are likely to be more relevant for ISCED 2.
Lastly, regarding capital expenditure (e.g. construction of new combined buildings), ISCED
breakdown estimations should be performed according to the number of students at each
ISCED level.
b) Proposal for an estimation method for finance data
Given the general recommendations from the Eurostat study, three steps have to be
followed to reach a proposal: identifying which data are available in the UOE questionnaire,
considering which methods can be subsequently envisaged, and finally selecting the method
based on the plausibility (or, even better, the verifiability) of those assumptions considered.
What is available
in FINANCE1 UOE table?
 CENTRAL GOVERNMENT EXPENDITURE:
o C1 (Direct expenditure for public institutions) as well as C5 (Total expenditure
for all types of institutions) (no expenditure for independent private
institutions, and the government-dependent institutions does not exist);
o Transfers and payments for education to private entities, i.e. C10
(Scholarships and other grants to students/households) & C12 Total financial
aid to students;
o C14 (Total transfers and payments to the private sector) is not available due
to missing data for C13 Transfers and payments to other private entities.
 REGIONAL GOVERNMENT EXPENDITURE:
o No data available -> no possible estimation
 LOCAL GOVERNMENT EXPENDITURE:
o No data available -> no possible estimation
 FUNDS FROM INTERNATIONAL AGENCIES AND OTHER FOREIGN SOURCES:
o F1 International payments direct to public educational institutions;
o No data for the private sector.
in other UOE tables?
According to the information we get, enrolments and staff Statistics should be easily
counted by grades in the future data collection, as well as the number of classes.
Which a priori methods?
 The distribution of (central government) expenditure into both ISCED levels (grades
1-5 and grades 6-8) could be prorated according to enrolments. Assumptions: cost
per student is same at both levels.
 The distribution of expenditure into both ISCED levels could be prorated according to
teaching staff Statistics. Assumptions: cost per teacher is same at both levels.
 The distribution of expenditure into both ISCED levels could be prorated according to
the number of classes at each grade. Assumption: cost by class is equal through
both ISCED levels 1 & 2 (this is more true for heating expenditure than for staff cost,
for example).
Final suggestion and procedure
A priori, no estimation method can be deemed as entirely satisfactory. With the help of local
experts in education, the potentially most reliable method could be identified. The second
method may be considered as a more reliable way for estimating the breakdown, if and only
if average salaries are known for both groups separately. Indeed, it is likely that teachers at
grades 5-8 earn more than at the lowest grades.
A combination of all three methods should also be envisaged, in relation with national
specifities. Such a combination would take into account wich assumption is the most valid for
which type of expenditure (e.g. the example above shows that the “class assumption” would
hold better for current expenditure on heating and building maintenance than the “enrolment
assumption”).
1.4.5 ANTICIPATING THE NEW 4+4+4 REGULATION
The new 4+4+4 prevailing law has been enacted recently under the Republic of Turkey’s
Parliament. As a corollary the details of implementation by the relevant ministry MoNE is yet
to be defined for the use of Statistical information. However, under some assumtions
summarised in the table below, it may be possible to anticipate some changes in the data
treatment process. It is important to note that in case the assumption below will not hold
validity in the future the IT/Bi upgrading will requires further analysis to accommodate those
changes. The source of information we used is the web document “12 years compulsory
education – questions & answers”69.
Grades
1-5
6-8
9-12
Current
ISCED
level
1
2
3
Theoretical
age
7-11
12-14
15-18
Grades
1-4
5-8
9-12
Future (4+4+4)
ISCED
Theoretical
level
age
1
6-9
2
10-13
3
14-17
Current and future educational structure in Turkey, and assumed ISCED level allocation
As shown in the hypothetical correspondence table above, the ISCED level 3 (upper
secondary education) would not change neither in terms of duration (4 years) nor in terms of
age.
Within the new 4+4+4 framework, as shown in the hypothetical correspondence table above,
the length of ISCED 1, 2 and 3 schooling does not change (12 years). However a noticeable
change is the age range it applies to, starting one year earlier (at the age of 6) and ending at
the age of 17. Moreover, the lenght of compulsory schooling is being increased to 12 years.
69
http://www.meb.gov.tr/duyurular/duyurular2012/12Yil_Soru_Cevaplar.pdf
The starting age at ISCED level 1 will therefore be similar to that of most European
countries.
The difficulty here is to allocate the different (4 years long) cycles to the relevant ISCED
levels. As shown in the table above, it is assumed that ISCED 2 in Turkey would start at the
age 10. This is the main questionable assumption made here. As a matter of fact, according
to the ISCED standards, ISCED 2 is notably characterised by subject-specific teachers. This
is possible (as in Germany, Austria and Romania) but to be checked in the future
implementation of the new Turkish structure.
The ISCED allocation has to be discussed at the national level with education experts in
Turkish curriculum development. Indeed, the main criterion for classifying educational
programmes into the ISCED classification is the programme content. More specifically the
following elements, taken from the ISCED standard recommendation (2011 version), should
feed such discussions:
 ISCED 1:
Basic and broad instruction :It focuses on learning at a basic level of complexity with
little if any specialisation. Typically, one main teacher is in charge of a group of
children and facilitates the learning process, often organized around units, projects or
broad learning areas with an integrated approach (particularly in the early years of
primary education). However, a class may have other teachers, especially for certain
specialized subjects (e.g. religion, physical education, etc.).

ISCED 2:
More subject-oriented instruction: Teachers at ISCED level 1 are typically trained in
pedagogical approaches for core subjects. In contrast, in ISCED level 2 programmes,
there may be more than one teacher instructing different subject areas, often with
more in-depth training in particular subjects. As a result, teachers have got different
qualifications according to the grades they are teaching. Teachers typically have
pedagogical training in specific subjects and, more often than at ISCED level 1, a
class of students may have several teachers who have specialized knowledge of the
subjects they teach.
Apart from this, the new Turkish education structure would easily comply with the other
criteria recommended in the ISCED 2011 Manual (legal age of entry at ISCED 1 is neither
younger than 5 years nor older than 7 years, typical duration at ISCED 1 is 4 to 8 years,
completion of ISCED 1 is required prior to entering ISCED 2, cumulative duration of 8 to 11
years at the end of ISCED level 2).
Once the allocation of the different 4-years-long cycles to the ISCED levels 1, 2 and 3 has
been decided, the data treatment process should not be more complex than in the current
situation, provided that the data are available by grade. It should even be simpler, as there is
no ISCED spanning programmes to deal with. In addition, according to currently available
information, the new regulation will result in buildings devoted to one and only one cycle.
That means that, under the assumed ISCED levels matching made above, some data will be
more easily available by ISCED level than currently (especially regarding expenditure and
some staff data): the estimation procedures developed in the previous section would
become obsolete.
The new regulation may enter into force in September of this year 70. That means that for the
UOE data collection 2014 (reference year 2013, i.e. academic year 2012-2013), there might
be some breaks in series regarding provided UOE data. As far as entrants at ISCED level 1
are concerned, for example, their number will strongly increase in the reference year 2013,
since both 6 year-olds and 7 year-olds will enter the first grade in September 2012. After this
cohort will have completed ISCED 1 (4 years later, reference year 2017), there will be a
break in series regarding enrolments: ISCED level 1 pupils will obviously decrease (as the
number of grades decreases, from 5 to 4). Moreover, those pupils entering the grade 5 in
September will be considered as having completed ISCED level 1.
At ISCED 2, the enrolments will increase as soon as reference year 2013, as the number of
grades will be increased of 1 unit.
In the UOE tables those breaks in series have to be mentioned using the flag “b”. The
following table shows when (reference year), for which tables (enrolments, entrants or
graduates) and at which ISCED level a flag “b” will probably be needed when reporting UOE
data. This table is not definitive, as it relies on the hypothetical ISCED level allocation
assumed above.
Entrants
Enrolments
Graduates
ISCED 1
2013
2017
2016
ISCED 2
2013
-
ISCED 3
-
Reference years when break in series may occur following the new 4+4+4 structure, under the
assumption that the new regulation enters into force in September 2012.
1.4.6 HOW TO COMPLETE REST OF THE UOE TABLES
In cases where the coverage of the data on students enrolled, educational finance, and
educational personnel differs, these differences must be reflected in tables PERS_ENRL-2
and FIN_ENRL-2 (See vol. 2 “UOE tables and instructions for their completion and
submission”). These tables collect data on the number of students enrolled by level of
education with some breakdowns by type of programme and by type of institution with a
coverage aligned to the personnel and finance data.
For example, if the statistics on educational finance do not cover expenditures for a
particular type of institution, then the students enrolled in this type of institution should be
excluded from Table FIN_ENRL-2. Similarly, if the data on educational personnel do not
cover certain types of programmes or delivery mechanism (e.g. distance education), then
the students enrolled in these programmes should be excluded from Table PERS_ENRL-2.
70
It is stated in the regulation that the Government has a one year postponement possibility.
Such an alignment, when needed because of differences in coverage, is necessary in order
to compute some key indicators, for example expenditure by student. Indeed, in case where
the coverage of the student population is larger than the coverage of finance data, such an
indicator would be underestimated.
1.4.4.1.
ALIGNMENT OF ENROLMENT DATA TO FINANCE DATA (TABLE FIN_ENRL2)
Table FIN_ENRL2 aligns the coverage of the data on enrolments and educational finance. It
contains data on student enrolment by level of education, type of educational programme
(destination and orientation), type of institution and intensity of participation (full-time/parttime).
The rows “aligned to data on educational finance” should be completed with the enrolment
statistics for which the coverage of the statistics is aligned to the coverage reported in the
tables FINANCE-1 and FINANCE-2.
For example, if the statistics on educational finance do not cover expenditures for a
particular type of service provider, then the students enrolled in this type of service providers
should be excluded from Table FIN_ENRL-2.
Table Fin_Enrl2 should be completed with the number of pupils or students enrolled in the
programmes for which financial data was reported in tables FINANCE1 and FINANCE2. This
alignment may imply that enrolment figures in Fin_ENRL2 include pupils or students which
were not included in ENRL1a. It may also imply that enrolment figures in Fin_ENRL2
exclude some pupils or students which were included in ENRL1a.
This implies that:
- If data on educational finance are not available for adult education, then the
corresponding students should be excluded from the figures in Table FIN_ENRL2;
- If data on educational finance are not available for educational institutions organised
by Ministries other than the Ministry of Education on a comparable basis, then these
students should be excluded from the alignment figures in the alignment tables
FIN_ENRL-2;
- If finance data include also expenditure for programmes shorter than one semester
(which from 2005 are excluded from the enrolment tables), and if it is not possible to
exclude also the expenditure on these programmes, the students have to be included
in FIN_ENRL-2.
1.4.4.2.
ALIGNMENT OF ENROLMENT DATA TO PERSONNEL DATA (TABLE PERS_ENRL2)
Table PERS_ENRL2 should be completed with the number of pupils or students enrolled in
the programmes for which personnel data was reported in tables PERS-1 and PERS-2. This
alignment may imply that enrolment figures in PERS_ENRL2 include pupils or students
which were not included in ENRL1a. It may also imply that enrolment figures in
PERS_ENRL2 exclude some pupils or students which were included in ENRL1a.
This implies that:
-
If data on educational personnel are not available for adult education, then the
corresponding students should be excluded from the alignment figures in the
alignment Table PERS_ENRL-2; when the estimation of personnel numbers at pre454 | F I N A L P R A C T I C A L G U I D E L I N E
primary level in mixed institutions or in programmes combining education and daycare is not possible, the corresponding enrolment figures should be excluded from
the UOE alignment table Pers_ENRL2.
As the number of educational personnel for combined school and work-based
programmes should exclude personnel in the work-based component, thus the
number of students should be properly adjusted to educational personnel in the table
PERS_ENRL-2 (to get a correct calculation of the students to teaching staff ratio);
If personnel data include personnel for programmes shorter than one semester
(which from 2005 are excluded from the enrolment tables), and if it is not possible to
exclude also the expenditure and personnel on these programmes, the students
have to be included in PERS_ENRL-2 in full-time equivalents (FTE).
If a breakdown is not possible for teachers (for example a split on ISCED 2 and
ISCED 3, with ISCED 2 teachers being included in the column for ISCED 3 in PERS1), the students should be reported in the same way in PERS_ENRL-2
If data on teachers are not available with breakdowns on each ISCED level, countries
should make efforts to estimate. If estimation is not possible and data for one ISCED
level include also another level, report the data in the column for the highest ISCED
level. ISCED 0&1 combined should be reported in ISCED 1, ISCED 1&2 combined in
ISCED 2 and ISCED 2&3 combined in ISCED 3. However, if ISCED 4 is included in
ISCED 3, teachers and students should be reported in ISCED 3.
-
-
-
-
2
PREPARING THE TRANSITION TO ISCED 2011
ISCED 2011 has been adopted by the general conference of UNESCO. Despite TURKSTAT
is in charge of the overall implementation of ISCED 2011 in all Statistical sources, it is
essential that MoNE takes fully part in the implementation of ISCED 2011 revision. It is
suggested that both TURKSTAT and MoNE attend the various EU meetings that will drive
the implementation process of ISCED 2011.
As a new ISCED is in the pipeline and Turkey like all other counties should prepare for the
new ISCED 2011. However, the ımplementatıon of ISCED 2011 ıs scheduled for 2014 wıth a
lot of other changes expected in the UOE data collectıon. Hence, there is no reason to
stress this now, it is more important first to get a working UOE system according to ISCED
97.
Levels
The changes for levels 0 – 3 are minor. The main change is the split for higher education
into the new levels 5-8. This split is not foreseen to be a classification problem in Turkey.
The data processing routines should be prepared for supplying data according to both
ISCED97 and ISCED2011. The tool is a proper ISCED mapping where all programmes are
mapped into both ISCED97 and ISCED2011 levels. This can be done during 2012 at least
for levels 0 - 3.
It is important that the BI system, the tables compiled from the administrative databases, will
be prepared for the transition to ISCED 2011.
Fields
The ISCED97 classification is composed of two main axes for cross-classification, namely
levels and fields of education. The current 2011 revision of ISCED only covers the levels.
However, UNESCO-UIS is planning to begin a revision of the fields late in 2011 with a view
to adopt a new classification in late 2013 (following a global consultation in 2012). This
means that no changes of the fields can be done until the earliest during late 2013.
EUROSTAT has already made an enquire on the fields to which Turkey has responded.
3
ROUTINES FOR TIME SERIES VALIDATION AND
PRESENTATION
A significant part of the validation of the data is related to reviewing differences compared to
the previous year and verifying that differences are consistent with national time series or
whether there is need for comments regarding breaks in time series.
The UOE data collection format is not suited for time series comparisons, but the
international organisation send feedback tables with time series comparisons, which
countries are asked to confirm. For the national data providers it is very helpful to have time
series tables also for the input tables, as a tool for verifying the data at the lowest level of
aggregation as well as for confirming the calculations made by international organisations.
As there are few other tables with summaries for the whole education system in Turkey, the
tables prepared for international organisations may also be input to national Statistics.
In the design of the data processing routines the proposed solution is to include the time
dimension in the ISCED-mapping table in the IT system. That will enable MoNE to apply
different standards for different years.
Most important is to compare the current data for UOE submission with the data reported
last year to make sure they are consistent. Breaks in the data need to be commented on.
OECD checks the Turkish UOE data when received. If “mistakes” are discovered, OECD will
ask MoNE for explanations. Hence, it is important to check the UOE data before submitting
them.
4
4.1
QUALITY ISSUES
QUALITY IN THE EUROPEAN STATISTICAL SYSTEM (ESS)
For obvious reasons, quality is a key issue for any Statistical system. For instance, it is
especially expressed that the Eurostat mission is ‘to provide the European Union with a highquality Statistical information service’. The production and the dissemination of Statistics
should be performed according to the European Statistics code of practice71.
The ESS is developing a set of standardised tools to report on the quality of Statistics. It is
advised to consult information on this issue which are available at:
71
Available at : http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/documents/CoP_October_2011.pdf
 Information on quality reports, tools & standards for quality reporting and EU
legislation regarding quality are available at:
http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/quality_reporting
 Information on the Euro-SDMX Metadata Structure (ESMS) is available at:
http://epp.eurostat.ec.europa.eu/portal/page/portal/Statistics/metadata/metadata_stru
cture
4.2
QUALITY REPORTING IN THE UOE
Quality reporting is part of the “Commission Regulation (EU) No 88/2011 of 2 February 2011
as regards Statistics on education and training systems Its annex 2 includes requirement on
data quality and on quality reporting.
Quality reporting in the UOE is currently under elaboration and could be subject to changes.
However, it is advised that MoNE use the same principles as Eurostat when assessing the
quality of the UOE data. Using routinely this framework has the following two advantages:
1. Establishing and documenting the quality of UOE data at national level on a regular
basis;
2. Allowing the mandatory transmission of UOE quality reports to Eurostat without
increasing the workload of MoNE staff.
Eurostat recommended the six following principles to be taken into account in implementing
the Quality Report Framework:
1- each of the seven chapters foreseen to be structured according to the tables in the
link 172 with four main headings: definitions/concepts, sources, estimations, revisions;
2- the quality report framework should start with a general chapter regarding
application of main concepts used in the UOE collection;
3- information on comparability of data and when data are published nationally will be
included but limiting the information to the strictly necessary;
4- the quality reporting should be done for both obligatory and optional tables;
5- countries should not report on what are already in the ISCED mappings;
6- the quality report framework should as far as possible only contain information
which could also be published as meta-data information.
The implementation of the above mentioned principle is illustrated by the template that all
members of the ESS will have to complete. In Turkey, MoNE will have to complete the
information as listed and presented in Annex 2.
72
Of Commission Regulation (EU) No 88/2011 of 2 February 2011 as regards Statistic on education and training
systems.
5
SUMMARIZING DATA FROM DIFFERENT SOURCES
It is recommended to maintain separate datasets for each data provider, and also for specific
parts of the educations system, wherever found feasible and relevant. That would mean that
there are full sets of UOE tables for the most important parts of the education system. In
case there is need for estimations, the recommendation is to insert an intermediate step,
create a new copy of the file with formulas referring to the version of the file before
estimations and apply the estimation method only in the second file. That is one method that
could be used to maintain transparency and verify which of the data are coming from the
source files and which may be manipulated by estimations. The estimation method should
be documented directly in the file with the estimations.
The last and final step is typically sum the data through all contributing files to the final
national version. That can be made in two stages, one for summing the numbers and a
second for applying codes for missing values etc. As the UOE requests alphabetic
information in the same cells as the numeric data, there is reason to insert the alphabetic
codes as a separate final step. As most empty cells are requested to be changed to code “n”
it is important that data suppliers don’t edit anything else than numeric information and
provide information about coding for “missing” data separately.
6
TRAINING NEEDS
In the publication Training Needs Analysis a number of conclusions and recommendations
on training activities are given. It seems clear that more knowledge in both Statistics and IT
is needed within MoNE.
In the context of the UOE data collection and international education Statistics it is important
to understand how the Turkish education Statistics is used internationally. International
comparisons of education systems using Statistical indicators are common already today
and will surely increase in the future. Hence, basic knowledge of Statistics and educational
concepts are necessary for everybody (both data providers and data users) involved in
international education Statistics in order to properly understand how international education
Statistics is compiled and used. To use international education Statistics more effectively, an
improved Statistical knowledge within MoNE and also YÖK and ÖSYM is needed.
An improved Statistical capacity within MoNE will also contribute to the sustainability of the
education Statistics system developed there.
ANNEXES
Annex 1: List of UOE Tables
No UOE Table
1
2
3
4
ENRL-Bologna
ENRL1
ENRL1_Adult
Number of students
enrolled by level of
education (tertiary level),
by sex and detailed field of
education reporting in
accordance with the
Bologna two cycle
(Bachelor-Master) and
Ph.D degree structure
Number of students by
level of education,
programme orientation,
programme destination,
intensity of participation,
sex and age
Number of students in
adult education
programmes reported in
ENRL1 by level of
education, programme
orientation, intensity of
participation, sex and age
level of education,
type of institution, intensity
of participation and sex
No
Yes
Yes
Filled in by Turkey
2010
Description
(Yes/No/Partly)
Yes
Partly
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
Partly
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
Yes
Partly
ENRL1a_adult
adult education reported in
ENRL1a by level of
orientation, type of
institution, intensity of
participation and sex
No
Partly
6
ENRL3
Number of students and
repeaters (ISC 123) in
general programmes by
level of education, sex and
grade
No
Partly
7
ENRL4
No
Yes
8
ENRL5
Yes
Yes
5
9
ENRL1a
Mandatory
(Yes/No)
Title
ENRL6
grade 1 by sex and age
Number of students (ISC
56) by level of education,
field of education and sex
Number of mobile and
foreign students (ISCED 5
and 6) by level of
destination and field of
No
Partly
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly. There is
no data for
private inst.
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
There is no
available data
for mobile
students
No UOE Table
Mandatory
(Yes/No)
Title
Filled in by Turkey
2010
Description
(Yes/No/Partly)
education
10
ENRL7
11
ENRL8
12
ENRL9
13
ENTR1
14
ENTR2
15
ENTR3
16
GRAD-Bologna
17
GRAD1
18
GRAD2
19
GRAD3
Number of mobile and
foreign students by level of
destination, EU/non EU
citizenship and sex
Number of students
(ISCED 5/6) by level of
destination, country of
citizenship
Number of students (ISC
5/6) by level of education,
programme destination
and country of origin
(usual residence and/or
prior education)
Annual intake by level of
education and programme
destination
Number of new entrants
by level of education, sex
and age
Number of new entrants
by level of education, sex
and field of education
Number of
graduates/graduations
(tertiary level), by sex and
detailed field of education
reporting in accordance
with the Bologna two cycle
(Bachelor-Master) and
Ph.D degree structure
Number of graduates
(ISCED 3 and 4) by level
of education, programme
destination, programme
orientation, type of
institution, sex and by
mobile and foreign student
by sex
Number of graduates
destination, programme
orientation, age and sex
Number of graduates
destination, cumulative
duration, type of
institution, sex and mobile
and foreign students by
No
Partly
Yes
Yes
There is no
available data
for mobile
students
There is no
available data
for
COUNTRY OR
TERRITORY
OF ORIGIN
No
No
No
Yes
Yes
Yes
Yes
Yes
No
Yes
No
Partly
3B and 3C
should be
determined
Yes
Partly
3B and 3C
should be
determined
No
Yes
No UOE Table
Mandatory
(Yes/No)
Title
Filled in by Turkey
2010
Description
(Yes/No/Partly)
sex
20
21
22
23
24
25
26
Number of graduates
GRAD4
destination, cumulative
duration, age and sex
Number of graduations by
level of education,
GRAD5
sex and field of education
Average duration of
Average duration
tertiary education
Survey 2009 to estimate
tertiary education
Completion rates completion rates for
national and foreign
students
Yes
Yes
Yes
Yes
No
NA
NA
No
NA
NA
Class 1
Average class size by
level of education and by
type of institutions
No
Partly
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
PERS_ENRL2
Number of students with
coverage adjusted to
statistics on education
personnel by level of
destination, type of
institution and mode of
study.
Yes
Partly
If any, part time
status missing.
PERS1
Classroom teachers
(ISCED 0-4) and
academic staff (ISCED 56) by level of education,
sex, age, type of institution
and employment status
Yes
Partly
If any, part time
status missing.
Also ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
No
No
Yes
PArtly
27
PERS2
28
FIN_ENRL2
School level management
personnel and teacher
aides in ISCED levels 0, 1,
2 and 3
Number of students with
coverage adjusted to
statistics on education
finance by level of
destination, type of
institution and mode of
study.
There is no
avilable data for
finance
Mandatory
(Yes/No)
Filled in by Turkey
2010
Description
(Yes/No/Partly)
No UOE Table
Title
29
FINANCE1
Education expenditure by
level of education, source
and type of transaction
Yes
No
30
FINANCE2
Education expenditure by
level of education, nature
and resource category
Yes
No
31
REGIO1
level of education,
sex and region
Yes
Partly
32
REGIO2
age, sex and region
Yes
Yes
33
ENRLLNG1
34
ENRLLNG2
35
ISCMAP_
PROGR
36
ISCMAP_QUAL
level of education,
programme orientation
and modern foreign
languages studied
level of education,
age and modern foreign
languages studied
Mapping of national
educational programmes
Mapping of national
educational qualifications
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly.
ISCED1
includes
ISCED1+ISCE
D2 together,
that is why
partly. There is
no data for
private inst.
Yes
Partly
Yes
No
No
NA
NA
No
NA
NA
Annex 2: UOE Quality Reporting
2
Introduct
ion
Aim of this Quality Reporting questionnaire
In the Data quality report perspective, deviations from the definitions and concepts as stated in the detailed manuals for the U
collection should be documented and explained and if possible quantified. To that end, the major part of this Quality Report is
issues and concepts for which the compliance with the UOE manuals has to be checked.
Those items are organised according to the ESS standards for metadata and quality reporting.
To facilitate the filling of tables, the cells to be completed are yellow-shaded.
NATIONAL EDUCATION SYSTEM
The following documents provide general information on the educational system; please add the relevant links for your country.
General link to Eurydice:
http://eacea.ec.europa.eu/education/eurydice/eurybase_en.php
National system broad overview:
<insert link>
National Education System Description:
<insert link>
Structure of Education and Training Systems:
<insert link>
Please, use the box below if you wish to complement or amend the information provided by Eurydice:
Link to the ISCMAP programme and qualification:
http://circa.europa.eu/Public/irc/dsis/edtcs/library?l=/public/unesco_collection/programmes_isced97&vm=detailed&sb=Title
National link to programmes and qualifications:
<insert link>
3 Quality management - assessment
4
Relevanc
e
4.1
Relevance User Needs
4.2
Relevance User
Satisfaction
4.3
Completene
ss
[not requested]
-
[not requested]
[not requested]
Missing data
For each UOE questionnaire, please list the main areas of unavailable data and the reasons why (e.g. low national priority, high
UOE
questionnaire
UOE table
ENRL
ENRL1
Missing (broad) areas
private institutions, etc.)
(e.g.
Reasons
ENRL1_Adult
ENRL1a
ENRL1a_Adult
ENRL3
ENRL4
ENRL5
ENRL6
ENRL7
ENRL8
ENRL9
ENRL-Bologna
ENTR
ENTR1
ENTR2
ENTR3
GRAD
GRAD1
GRAD2
GRAD3
GRAD4
GRAD5
GRAD-Bologna
PERS
PERS_ENRL2
PERS1
PERS2
CLASS
CLASS1
FINANCE
FIN_ENRL2
FINANCE1
FINANCE2
FINANCESUP2
FINANCESUP3
DEM
DEM1
ISCMAP
PROG
QUAL
4.3.1
Data
completenes
s - rate
5
Accuracy
and
reliability
Average duration
of tertiary studies
-
Completion rates
-
[not requested]
-
5.1 Accuracy
- overall
[not requested]
5.2 Sampling
[not requested]
error
5.2.1
Sampling
error
indicators
-
[not requested]
5.3
Nonsampling
error
[not requested]
5.3.1
Coverage
error
1. Vocational training
Please see the UOE manuals for UOE requirement details
In your country, are vocational and technical training
programmes in enterprises included in the UOE data
collection (Yes/No)?
If Yes, how is the 10 % school based component over
the whole length of the programme assessed?
If no, how does your coverage deviate from the UOE
Manual recommendation?
2. Programme shorter than one semester (or Implementation of the semester rule)
In your country, do (formal) programmes of shorter
duration than one semester, full time equivalent duration
as defined nationally, exist (YES/NO)?
Could you please explain how their duration (shorter
than one semester) is assessed?
Are all programmes of shorter duration than one
semester, full time equivalent duration as defined
nationally excluded from the UOE data collection
(YES/NO)?
If no, how does your coverage deviate from the UOE
Manual recommendation?
3. Early childhood education programmes
Do pre-primary education for children below 3 years
exist in your country (YES/NO)?
If Yes, are these programmes excluded from the UOE
data collection (YES/NO)?
If No (i.e. programmes in pre-primary education for
children under 3 are not excluded from the UOE data
collection), how does your coverage deviate from the
UOE Manual recommendation?
4. Special education programmes
In your country, are students in special education
included in the ENRL, ENTR, GRAD and PERS and
(FIN_ENR2) questionnaires (YES/NO)?
If No, could you please specify for which questionnaires
and explain why?
Are students with SNE excluded from the CLASS
questionnaires (YES/NO)?
If No, could you please explain why?
5. Adult education programmes
Are adult education programmes included in your UOE
data (YES/NO/DO NOT EXIST)?
If YES, does your national definition of “adult” or
“continuing” education fully comply with the category as
defined by the UOE manual (YES/NO)?
If No, could you please explain why?
If your national definition of “adult” or “continuing”
education programmes does not fully comply with the
category as defined by the UOE manual, how do you
assess that your national “adult” or “continuing”
programmes are similar or equivalent to corresponding
initial education?
6. Students enrolled in educational institutions organised by ministries other than ministry of education
In your country, do educational programmes organised
by Ministries other than Ministry of education exist
(YES/NO)?
If Yes, please specify coverage of these programmes in
the UOE data collection.
If Yes, and if some of those programmes are excluded
from the UOE data collection, please specify which ones.
7. Domestic educational activities
Do you report all your country’s domestic educational
activities in the UOE data collection (YES/NO)?
If No, please detail which domestic educational activity
(e.g. for example Distance learning/e-learning involving
two countries, commuting students, foreign campus ,
European administration schools, etc.) is not reported
and why?
8. Distance learning / e-learning programmes
In your country, are distance learning programmes data
reported in the UOE questionnaires? (yes, no, partially,
not relevant) [Please answer "not relevant" if there are
no such programmes in your country]
If No, please explain why.
If Partially, please could you specify which ones are
excluded and for what reasons?
If distance students are reported in the UOE
questionnaires, do you exclude those national distance
learners in programmes organised by institutions outside
your country?
9. Foreign and mobile students
In your country, are all students in short term postings
(e.g. for example exchange programmes (credit
mobility)) excluded from the population of mobile student
in the data collection (YES/NO)?
If Yes, how the length of their stay abroad is assessed,
please explain:
If No, could you explain why they are not excluded?
10. Coverage according to the ISCED classification
List of national programmes not covered by the UOE data collection and reasons why they are not covered:
Which programmes are not covered at ISCED 0 - preprimary level of education? (if any). Please explain why.
Which programmes are not covered at ISCED 1 primary level of education? (if any). Please explain why.
Which programmes are not covered at ISCED 2 - lower
secondary level of education? (if any). Please explain
why.
Which programmes are not covered at ISCED 3 - upper
secondary level of education? (if any). Please explain
why.
Which programmes are not covered at ISCED 4 - postsecondary non-tertiary? (if any). Please explain why.
Which programmes are not covered at ISCED 5A Tertiary first stage, academically-oriented? (if any).
Please explain why.
Which programmes are not covered at ISCED 5B Tertiary first stage, practically-oriented? (if any). Please
explain why.
,
Which programmes are not covered at ISCED 6 Tertiary second stage? (if any). Please explain why.
5.3.1.1 Overcoverage
rate
[not requested]
5.3.2
Measuremen
t error
[not requested]
5.3.3
Non
response
error
[not requested]
5.3.3.1 Unit
nonresponse
rate
5.3.3.2 Item
nonresponse
rate
[not requested]
[not requested]
5.3.4
Processing
error
Data entry errors are limited by the use of a checking tool embedded in
the questionnaire
5.3.4.1
Imputation -
[not requested]
rate
5.3.4.2
Common
units
proportion
[not requested]
5.3.5 Model
assumption
error
[not requested]
5.3.6
Data
revision
[not requested]
5.3.6.1 Data
revision
policy
[not requested]
5.3.6.2 Data
revision
practice
Revision of UOE data (ex-post change after the data have already been made publicly available)
Description
Reason having led to
the revision
Time
period
Consequences on accuracy
Revision 1
Revision 2
Revision 3
Revision 4
Revision 5
Revision 6
Revision 7
Revision 8
Revision 9
Revision 10
Revision 11
Revision 12
Revision 13
Revision 14
Revision 15
Revision 16
Revision 17
Revision 18
Revision 19
5.3.6.3 Data
revision
average size
[not requested]
5.3.7
Seasonal
adjustment
[not requested]
6 Timelines
and
punctuality
6.1 Timeliness
Key dates
Start date
End date
Data collection
Post-collection phase
Dissemination/publication in your country
6.1.1 Time lag first result
[not requested]
6.1.2 Time lag final result
[not requested]
6.2 Punctuality
6.2.1 Punctuality
- delivery and
publication
Grad
Pers
Class
Finance
IscMap
Lang
Regio
The submission dates
for your country (latest
reference year) are, for
each
UOE
questionnaire :
Please comment the
punctuality
of
transmission
to
Eurostat,
e.g.,
the
reasons for late delivery
and action taken or
planned for improving
punctuality.
7 Accessibility and clarity
-
7.1 Dissemination format - News release
[not requested]
7.2 Dissemination format - Publications
[not requested]
7.3 Dissemination format - online database
[not requested]
7.3.1 Data tables - consultations
[not requested]
7.4 Dissemination format - microdata access
[not requested]
7.5 Documentation on methodology
[not requested]
7.5.1 Metadata completeness - rate
[not requested]
7.5.2 Metadata - consultations
[not requested]
7.6 Quality management - documentation
[not requested]
7.7 Dissemination format - other
[not requested]
8 Comparability
8.1 Comparability geographical
A. Deviations from the UOE Manual: non financial data
Concepts
UOE
Manual
reference
1) Reference period
vol. 2, § 9.1
2) Data collection period
vol. 2, § 9.1
3) Reference date for student
and personnel ages
vol. 2, § 9.1
4) Enrolment: data collection
period
vol.1, § 3.1.1
5) Enrolment in multiple fields
of education
vol.1, § 3.1.1
6) Entrants
vol.1, § 3.2.1
7) New entrants by field of
education
vol.1, § 3.2.2
8) Graduates and graduations
from specific programmes
vol.1, § 3.3.1
9)
Graduates
graduations
vol.1, § 3.3.2
10)
Graduates:
versus
unduplicated
Please describe any deviations between your
national methodology and the UOE manual
recommendations - Please see the UOE manuals
for UOE requirement details
vol.1, § 3.3.4
count
11) Graduations by field of
education
vol.1, § 3.3.5
12) Educational personnel in
workand
school-based
combined programmes
vol.1, § 3.5
13)
Educational
personnel
taxonomy: classroom teachers
(ISCED 0-4) and academic staff
(ISCED 5-6)
vol.1, § 3.5.1.1
14) Educational staff at ISCED
level 0
vol.1, § 3.5.1.1
15) Educational personnel at
ISCED levels 5-6
vol.1, § 3.5.3.1
16) Educational personnel and
temporary replacements
vol.1, § 3.5.5
17) The "class" concept
vol.1, § 3.6
18) Count of students: Would
you like to signal any issues
regarding
double
counting
which in your view would be
significant (please specify table
and reason).
vol.1, § 3.1.1
B. Deviations from the UOE Manual: Financial data
Concepts
recommendations
&
UOE
Manual
reference
1) Reference period
vol. 2, § 9.1
2) Expenditure at the preprimary level
vol.1, § 5.1.1.2
3) Expenditure at the preprimary level
vol.1, § 5.1.1.2
4)
Expenditure
teaching/academic
hospitals
vol.1, § 5.1.1.3.2
5)
Ancillary
expenditure
Please describe any deviations between your national
methodology and the UOE manual recommendations Please see the UOE manuals for UOE requirement
details
for
services
vol.1, § 5.1.1.3.4
6) Evening child care
vol.1, § 5.1.1.3.6
7) Cost of a dual-system
programme
to
the
vol.1, § 5.1.1.3.8
employer.
8.1.1 Asymmetry for
mirror
flow
statistics
coefficient
8.2 Comparability over time
8)
Adjustment
of
enrolments in case there is
no data on expenditure at
the workplace
vol.1, § 5.1.1.3.8
9)
Expenditure
for
contributions on pension
schemes
vol.1, § 5.1.1.3.9
10) Households' payments
for private tutering
vol.1, § 5.1.2.1
11) Student living costs
vol.1, § 5.1.2.2
12)
Ancillary
coverage
vol.1, § 5.1.1.3.4
services
[not requested]
Changes in the educational system
Please describe significant changes that
occurred in the educational system (and
years when those changes occurred), i.e.
"real" changes in the data due to changing
conditions of the educational system, such
as the implementation of reforms that lead
to an increase in the stock of students.
Changes in the coverage
occurred in the educational system (and
years when those changes occurred), i.e.
changes introduced due to the exclusion
or the inclusion of programmes. Inclusion
of adult literacy programmes, or private
schools could be examples.
Changes in the methodology
occurred (and years when those changes
occurred) in the methodology used
(except for ISCMAP.XLS), i.e. changes in
the
data
due
to
new/modified
methodologies in data collection or
estimation.
8.2.1
Length
of
comparable
time
series
[not requested]
8.3 Comparability -
[not requested]
domain
9 Coherence
9.1 Coherence
cross domain
Coherence with Other Sources published nationally
-
Please add as many rows as needed
Name of the national publication
9.1.1 Coherence sub
annual
and
annual statistics
Coherence issues
[not requested]
9.1.2 Coherence National Accounts
Calculation
method:
The
UOE
educational
expenditure data are compiled on a cash accounting
rather than an accrual accounting basis as
recommended by the national accounts framework.
Scope of education: in the UOE ministries and
administrative bodies should also be regarded as
education and their expenditures counted, whereas in
the national account such bodies are part of
government administration.
Please note the main issues where your
education expenditure figures do not comply
with National Account standards? [please check
the prefilled examples and provide others
according to your practice at national level]
9.2 Coherence
internal
10
Cost
and
Burd
en
-
[not requested]
Administrative staff time spent to complete UOE
Only staff responsible for compiling data for UOE purpose in administration: additional surveys excluded
Time spent (in working days)
11 Confidentiality
11.1 Confidentiality - policy
Comments
[not requested]
11.2 Confidentiality - data treatment
[not requested]
12
Statistical
processing
-
12.1 Source data
Overview of sources used in the UOE data collection
For each UOE questionnaire, please list the sources used to compile information: UOE table, name, type, date of
availability and responsibility
In case of multiples sources per UOE table, please add as many rows as needed
UOE
questionnaires
/ data involved
UOE table
ENRL
ENRL1
Name of
the source
Type
(Survey;
Register;
Estimatio
n; Other)
Date
when
the
information is
made
available
to
the UOE data
provider
Responsible of the source:
Please specify if the UOE data
provider is responsible of the
source (y/n). If not, specify the
institution responsible
ENRL1_Adult
ENRL1a
ENRL1a_Adult
ENRL3
ENRL4
ENRL5
ENRL6
ENRL7
ENRL8
ENRL9
ENRL-Bologna
ENTR
ENTR1
ENTR2
ENTR3
GRAD
GRAD1
GRAD2
GRAD3
GRAD4
GRAD5
GRAD-Bologna
PERS
PERS_ENRL2
PERS1
PERS2
CLASS
CLASS1
FINANCE
FIN_ENRL2
FINANCE1
FINANCE2
FINANCESUP2
FINANCESUP3
DEM
DEM1
ISCMAP
PROG
QUAL
12.2 Frequency
data collection
Average
duration
of
tertiary studies
-
Completion
rates
-
of
[not requested]
12.3 Data collection
[not requested]
12.4 Data validation
[not requested]
12.5 Data compilation
Weighting methods
Weighted figures for differing reference periods
Weighted figures for differing theoretical ages
Conversion factors from part-time to full-time equivalent
(FTE) data
Estimations methods used in the UOE questionnaires
In case where additional document or file is provided, please refer to the "ref number" on the left
ref number
UOE file
(e.g.
FINANCE.
xls)
UOE
sheet
UOE
row
(e.g.
A9)
UOE col
(e.g. 4)
Reference
year(s)
Data
source
(internal
to UOE
or not)
Data
type
(samplebased
or
not)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Data name
in English
(e.g. HBS)
22
23
24
25
26
27
12.6 Adjustment
[not requested]
13
Comment
A. Non finance data
Topic
Reference
year(s)
Comment
Reference
year(s)
Comment
B. Finance data
Topic
This publication has been produced with the assistance of the European Union. The
content of this publication is the sole responsibility of the Consortium led by Sogeti
and can in no way be taken to reflect the views of European Union.

Technical Assistance for Strengthening the Statistical Capacity of

Transcription

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