April, 2016

Transcription

April, 2016
April, 2016
Editorial Board
Owner
Prof. Dr. Naci GUNDOGAN (Anadolu University Rector)
Editor-in-Chief
Dr. T. Volkan YUZER (Anadolu University)
Associated Editor
Dr. Gulsun EBY (Anadolu University)
International Affairs
Dr. Ugur DEMIRAY (Anadolu University)
Editorial Board in English Language
Dr. Zulal BALPINAR (Anadolu University)
Dr. Ilknur KECIK (Anadolu University)
Proof Reading Team
Dr. Ali MERC (Anadolu University)
Dr. Ozgur YILDIRIM (Anadolu University)
Dr. Ipek KURU GONEN (Anadolu University)
Dr. Gonca SUBASI (Anadolu University)
Web Support Team
Dr. Nilgun OZDAMAR KESKIN (Anadolu University)
Abdulkadir KARADENIZ (Anadolu University)
Altan DEVRIM (Anadolu University)
Editorial Board Members
Dr. Abdul Waheed KHAN (Canada)
Dr. Anna RYBAK (Poland)
Dr. António TEIXEIRA (Portugal)
Dr. Antonis LIONARAKIS (Greece)
Dr. Asha KANWAR (Canada)
Dr. Bobby HARREVELD (Australia)
Dr. Carmencital CASTOLO (Philippines)
Dr. Cleborne D. MADDUX (Canada)
Dr. David METCALF (USA)
Dr. Dursun GOKDAG (Turkey)
Dr. Ene KOITLA (Estonia)
Dr. Ezendu ARIWA (United Kingdom)
Dr. Fahriye ALTINAY AKSAL (Turkey)
Dr. Farhad SABA (USA)
Dr. Ferhan ODABASI (Turkey)
Dr. Feyzi ULUG (Turkey)
Dr. Fons NOUWENS (Australia)
Dr. Francis GLASGOW (South America)
Dr. Gilly SALMON (United Kingdom)
Dr. Gonca Telli YAMAMOTO (Turkey)
Dr. Hakan TUZUN (Turkey)
Dr. Hanafi ATAN (Malaysia)
Dr. Jack KOUMİ (United Kingdom)
Dr. Jim FLOOD (United Kingdom)
Dr. John TRAXLER (United Kingdom)
Dr. Katherine M. SINITSA (Ukraine)
Dr. Kinshuk (New Zealand)
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Dr. Loreta ULVYDIENE (Lithuania)
Dr. Marina McISAAC (USA)
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Dr. Meena HWANG (South Korea)
Dr. Michael R. SIMONSON (USA)
Dr. Michail KALOGIANNAKIS(France)
Dr. Mihai JALOBEANU (Romania)
Dr. Nabi Bux JUMANI (Pakistan)
Dr. Natalija LEPKOVA (Lithuania)
Dr. Patrick DANAHER (Australia)
Dr. Paul KAWACHI (China)
Dr. Piet KOMMERS (Netherlands)
Dr. Ramesh C. SHARMA (India)
Dr. Roza DUMBRAVEANU (Moldova)
Dr. Rozhan B. M. IDRUS (Malaysia)
Dr. Santosh PANDA (India)
Dr. Sarah GURI-ROSENBLIT (Israel)
Dr. Shivakumar DEENE (India)
Dr. Simon STOBART (United Kingdom)
Dr. Som NAIDU (Australia)
Dr. Stephen DOWNES (Canada)
Dr. Steve WHEELER (United Kingdom)
Dr. Tamar LOMINADZE (Georgia)
Dr. Ugur DEMIRAY (Turkey)
Dr. William John FRASER (South Africa)
Dr. Yavuz AKBULUT (Turkey)
Dr. Zehra ALTINAY GAZİ (Turkey)
Dr. Zeki KAYA (Turkey)
Dr. Zdena LUSTIGOVA (Czech Republic)
Dr. Zhang WEI-YUAN (Hong Kong)
Honorary Editorial Board of TOJDE (Ordered alphabetically)
Prof. Dr. Cevat ALKAN - The pioneer of educational technology in DE in Turkey (Turkey)
Prof. Dr. Engin ATAC - Former Rector of Anadolu University for 1999-2006 period (Turkey)
Prof. Dr. John BAATH - The well-known Swedish distance educator (Sweden)
Prof. Dr. Tony BATES - Father of DE in Canada (Canada)
Prof. Dr. Yılmaz BUYUKERSEN - The founder of DE in Turkey (Turkey)
Prof. Dr. Chris CURRAN - The founder director of National DE Centre in Ireland (Ireland)
Prof. Dr. Chere Campbell GIBSON - She studied for DE all her life. Emeritus Professor (USA)
Prof. Dr. Börje HOLMBERG - He studied for DE. Emeritus Professor (Sweden)
Prof. Dr. James MARAJ - The pioneer of the open university movement (Australia)
Prof. Dr. Charles A. WEDEMEYER - The pioneer of DE in the world (USA)
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Table of Contents
From The Editor
Welcome to the Volume 17, Number 2 of TOJDE
Marcela Gerogina GOMEZ-ZERMENO & Lorena ALEMAN DE LA GARZA
Research Analysis on Mooc Course Dropout and Retention Rates
3-14
Hasan UCAR & Mujgan YAZICI BOZKAYA
Pre-Service EFL Teachers’ Self-Efficacy Beliefs, Goal Orientations, and
Participations in an Online Learning Environment
15-29
Djoko RAHARDJO, SUMARDJO, Djuara P. LUBIS & Sri HARIJATI
Internet Access and Usage in Improving Students’ Self-Directed Learning in
Indonesia Open University
30-41
Gurhan DURAK, E. Emre OZKESKIN & Murat ATAIZI
QR Codes in Education and Communication
42-58
Jose CAPACHO
Teaching and Learning Methodologies Supported by ICT Applied in Computer
Science
59-73
Muhammad Razuan ABDUL RAZAK & Ahmad Zamzuri MOHAMAD ALI
Instructional Screencast: A Research Conceptual Framework
74-87
Moanes H. TIBI
Essential Components in Structuring Asynchronous Discussion Forums
88-97
Harun CIGDEM & Mustafa OZTURK
Critical Components of Online Learning Readiness and Their Relationships with
Learner Achievement
98-109
Indrajeet DUTTA
Open Educational Resources (OER): Opportunities and Challenges for Indian
Higher Education
110-121
Reviewed By Hakan ALTINPULLUK
REVEW: E-Learning Paradigms and Applications Agent-Based Approach Edited By
Mirjana Ivanovic And Lakhmi C. Jain
122-124
Reviewed By Aylin OZTURK
REVIEW: Educational Data Mining: Applications and Trends Edited by Alejandro
Pena-Ayala
125-128
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2
Dear TOJDE Readers,
Welcome to the Volume 17, Number 2 of TOJDE,
In April 2016 issue, there are 9 articles and 2 book reviews. 18 authors from 7 different
countries write the articles. All these articles are from Colombia, India, Indonesia, Israel,
Malaysia, Mexico, and Turkey.
The 1st article is written by Dr. Marcela Gerogina GOMEZ-ZERMENO and Lorena ALEMAN DE
LA GARZA. The title of this article is RESEARCH ANALYSIS ON MOOC COURSE DROPOUT
AND RETENTION RATES. This article researches terminal efficiency of the Massive Online
Open Course “Educational Innovation with Open Resources” offered by a Mexican private
university. A quantitative methodology is used in this research. The reasons of dropout and
retention rates is explained by the writers in the article.
PRE-SERVICE EFL TEACHERS’ SELF-EFFICACY BELIEFS, GOAL ORIENTATIONS, AND
PARTICIPATIONS IN AN ONLINE LEARNING ENVIRONMENT is the title of the 2nd article.
Hasan UCAR and Prof. Dr. Mujgan YAZICI BOZKAYA are the writers. Embedded mixed
design was used in the study. In the quantitative part of the study, the participants were
186 senior pre-service EFL teachers and data were collected on two scales and a
questionnaire. Qualitative data were collected in form of one-on-one interviews from 2 preservice EFL teachers. Results shows several positive associations between teachers’ goal
orientations and self-efficacy beliefs. The writers also presents future research suggestions
in the end of article.
The 3rd article’s title is INTERNET ACCESS AND USAGE IN IMPROVING STUDENTS’ SELFDIRECTED LEARNING IN INDONESIA OPEN UNIVERSITY. Djoko RAHARDJO, Prof. Dr.
SUMARDJO, Dr. Djuara P. LUBIS, and Dr. Sri HARIJATI are the writers of the article. This
study aims to analyze the relationship between internet access and usage in improving
students' self-directed learning which is using structural equation model method. The
result shows that the internet usage is still low in Indonesia due to limited internet facilities
that affect the knowledge and willingness of students to access the internet. In the end,
the writers has a suggestion. The strategy in improving student internet usage is applying
social media as guidance that can be accessed through cellular phones.
Dr. Gurhan DURAK, E. Emre OZKESKIN, and Dr. Murat ATAIZI are the writers of the 4th
article. QR CODES IN EDUCATION AND COMMUNICATION is the tile of this article.
Descriptive data analysis is used in the study. The findings are interpreted on the basis of
Theory of Diffusion of Innovations and Theory of Uses and Gratifications. The writers
highlight that the students mentioned that they did not have any difficulty using QR Codes.
According to students, the content should include both superficial and in-depth
information.
The 5th article, titled TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY ICT
APPLIED IN COMPUTER SCIENCE, is written by Dr. Jose CAPACHO. The main objective of
this paper is to show a set of new methodologies applied in the teaching of Computer
Science using ICT. Behavioral Theory, Gestalt Theory. Genetic-Cognitive Psychology
Theory, and Dialectics Psychology support the theoretical framework of the article.
INSTRUCTIONAL SCREENCAST: A RESEARCH CONCEPTUAL FRAMEWORK is the tile of the
6th article. Muhammad Razuan ABDUL RAZAK and Ahmad Zamzuri MOHAMAD ALI are the
writers of this article. According to writers, the cognitive style will ultimately affect how
information is processed in the students’ memory structure. Students will also easily
process the given information, if it is performed in accordance with their dominant learning
style. In the end of the article, the writers suggest experimental studies are important to
determinate the ideal screencast design for specific learning style and cognitive style.
The 7th article is titled ESSENTIAL COMPONENTS IN STRUCTURING ASYNCHRONOUS
DISCUSSION FORUMS. Dr. Moanes H. TIBI is the writer of this article. This paper reviews
the literature regarding the main elements and components that makes an asynchronous
discussion forum more effective for knowledge acquisition and thereby increases the
quality of online learning.
Dr. Harun CIGDEM and Dr. Mustafa OZTURK are the writers of the 8th article. The title of
this article is CRITICAL COMPONENTS OF ONLINE LEARNING READINESS AND THEIR
RELATIONSHIPS WITH LEARNER ACHIEVEMENT. This study is aimed to examine the
relationship between certain factors of online learning readiness and learners’ end-ofcourse achievements. The results show that the students’ self-direction towards online
learning appeared to be the strongest predictor of their achievements within the course;
whereas computer/Internet self-efficacy and motivation for learning did not predict the
learner achievement significantly.
The title of the 9th article is OPEN EDUCATIONAL RESOURCES (OER): OPPORTUNITIES AND
CHALLENGES FOR INDIAN HIGHER EDUCATION and the writer is Dr. Indrajeet DUTTA. The
writer highlightsthe easy and widespread availability of high quality educational material
will change the paradigm of teaching and learning and thus improve the quality of
education. Government of India has started several innovative programs and schemes like
SHAKSHAT, NMEICT, NPTEL, OSCAR, E-grid etc. related to developing and disseminating
educational resources. This article focuses on the opportunities and challenges with respect
to OER in Indian higher education.
There are two book reviews in this issue. E-LEARNING PARADIGMS AND APPLICATIONS:
AGENT-BASED APPROACH is the title of 1st book. This book is an editorial book. The editors
are Mirjana Ivanovic and Lakhmi C. Jain. The reviewer is Hakan ALTINPULLUK.
Other book’s title is EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS. This is
another editorial book and the editor is Alejandro Pena-Ayala. This book is reviewed by
Aylin OZTURK.
Hope to meet you July 2016 issue of TOJDE.
Cordially,
Dr. T. Volkan YUZER
Editor-in-Chief
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 1
RESEARCH ANALYSIS ON MOOC COURSE DROPOUT AND
RETENTION RATES
Dr. Marcela Gerogina GOMEZ-ZERMENO
Tecnológico de Monterrey, School of Education,
Humanities and Social Sciences, Monterrey, MEXICO
Lorena ALEMAN DE LA GARZA
Tecnológico de Monterrey, School of Education,
Humanities and Social Sciences, Monterrey, MEXICO
ABSTRACT
This research’s objective was to identify the terminal efficiency of the Massive Online Open
Course “Educational Innovation with Open Resources” offered by a Mexican private university.
A quantitative methodology was used, combining descriptive statistics and probabilistic
models to analyze the levels of retention, completion, and desertion, as well as the
characteristics of the students who completed the course. The results show a 14% of student
retention and an 11.7% of student completion, relative to the total number of participants,
who had some common characteristics: having a graduate (master or doctorate), being
experienced in online education, committed to the course and self-taught. The participants
who abandoned the course expressed the following reasons: problems with the course’s
structure, limitations in the use of information and communication technologies or limited
English proficiency, family reasons or low time disposition. It is recommended to take actions
that will increase the knowledge in order to explain the MOOCs’ desertion rates and to
strengthen their structures to improve the retention and completion rates.
Keywords: Distance education, Open educational resources, MOOC, Terminal efficiency, School
desertion
INTRODUCTION
The evolution of distance education and technological advances signify an important
opportunity to increase education’s access and contribution to the compliance of international
commitments regarding education. In this respect, the United Nations Educational, Scientific,
and Cultural Organization (UNESCO, 2002, 2012) has established that free access to
educational resources is a strategy to upgrade the quality of education, to facilitate the
dialogue about policies, to interchange knowledge and to develop skills.
Massive Online Open Courses (MOOC) are an emerging practice in open learning. It began in
2008, when George Siemens and Stephen Downes offered the course Connectivism and
Connective Knowledge in the University of Manithoba in Canada; the course had a duration of
12 weeks and 2,300 students enrolled (Fini, 2009; Wiley & Hilton III, 2009).
Among their characteristics, MOOCs allow the construction of bonds between hundreds or
even thousands of students who self-organize their participation, learning goals, knowledge,
3
abilities and interests (McAuley, Stewart, Siemens & Cormier, 2010). Additionally, their free
online access enables the enrollment of a large number of students (SCOPEO, 2013).
Currently, Coursera, EdX, and Udacity are among the platforms that host MOOCs. For Latin
American participants, MiriadaX and RedunX are available (Lushnikova, Chintakayala,
Rodante, 2013; SCOPEO, 2013). Many Latin American universities have developed their own
MOOCs in their institutional platforms or even through social networking sites such as
Facebook. Nevertheless, only three Latin American universities are part of the Coursera
community.
In developing countries, the use of MOOCs is an alternative educational offering for
professionals who look for complementary training and education. In addition, these courses
allow the acquisition of new knowledge and skills in fields that could provide them the
opportunity for a better income or to continue learning throughout life. Massive courses attract
thousands of participants who are interested in the offered topic; however, it is important to
note that approximately only 10% of the registered students complete the course (Lushnikova
et al., 2013). Such case is reported by the University of Toronto (Harrison, 2013), where the
percentage of terminal efficiency varied between 3% and 16%. On a similar note, SCOPEO
(2013) reported an average of 13.5% of students who completed the course, out of 188,802
registered participants in 58 courses from 18 universities.
The low terminal efficiency rates of MOOCs reveal a lack of self-regulation and self-motivation
in students (Lushnikova et al., 2013). Likewise, Clow (2013) remarks that the student’s
compromise level may diminish as the courses move forward. On this respect, Siemens and
Tittenberg (2009) established that desertion rates could be minimized by providing more
attention to the students regarding the components of effective learning, motivation,
institutional support and free access to educational resources, in order to promote the
development of interpersonal relationships among peers, faculty, and teaching staff.
A dropout in online courses refers to the persons who inconspicuously discontinue their
participation in the course; however, they are different from passive participants, students
who do not unregister and continue the course without active collaboration in it (Rodríguez,
2012). Additionally, the author signals that the desertion rates and passive behavior of some
MOOCs’ participants are among the educators’ concerns.
In Latin America, experiences related to MOOCs are still developing; due to the growing
research demand for these educational practices, it is necessary to identify and overcome the
difficulties and obstacles in order to increase their dissemination and implementation, as well
as the promotion of this type of initiatives, so they can be integrated in the public agenda of
countries, institutions and inter-institutional projects in Latin America (Mortera, 2012). These
circumstances have been confirmed by Liyanagunawardena, Adams and Williams (2013), who
signal a lack of research and information about MOOCs that can explain why participants do
not complete a course.
According to Gómez-Zermeño (2012), it is important to create a context that supports
innovative practices to evaluate the results of the undertaken efforts when new ways of
teaching and learning are promoted. Given the research demands about the potentialities of
MOOCs, it is important to inquire into the terminal efficiency of an MOOC offered in Spanish.
This investigation generated information about the MOOC Educational Innovation through
Open Resources, offered in Coursera on September of 2013. The study had the following
research questions: What was the terminal efficiency of participants in the course Educational
Innovation through Open Resources? What are the characteristics of the participants who
successfully completed the course? With a quantitative methodology that combines
4
descriptive and econometric statistics, the research results show the retention and terminal
efficiency rates of the course, the features of students who completed the course, as well as
the causes of dropout and abandonment. A probabilistic model was used to identify the weight
of each one of the dropout factors and thus evaluate the terminal efficiency of the MOOC
“Educational Innovation through Open Resources”.
RESEARCH METHOD
Based on the research questions, the study opted for a quantitative methodology, combining
the use of descriptive and econometric statistics, which allowed to identify the MOOCs’
participants profile and to calculate the dropout rates and terminal efficiency. Probabilistic
models were used to identify the weight of each one of the dropout factors. The dependent
variable is a binary variable (if the student abandoned the course, it was assigned the value of
1 and 0 on the contrary) and the independent or explanatory variables include factors such as
gender, age, previous experience in virtual education and electronic media, educational level,
English proficiency, and intrinsic characteristics such as being proactive, innovative and selftaught.
The quantitative approach was used to analyze information through statistical methods;
participants answered a diagnostic and final survey to inform about their opinions and
perspective, this allowed understanding better the numerical data. Recognizing the
participants’ experiences allowed the comprehension of the phenomenon (Alemán & GómezZermeño, 2012; Gómez-Zermeño, Rodríguez Arroyo & Márquez Guzmán, 2013).
From an explanatory point of view (Creswell & Plano, 2011), the study sought to understand
why the dropout phenomenon occurs and under what conditions, in order to identify the
reasons why MOOC’s participants decide to dropout and not complete the course. We used a
non-experimental, cross-section and ex-post-facto design, and the participants’ information
was collected during August-September of 2013 (Valenzuela y Flores, 2012).
MOOCS’s Description and Context
The MOOC “Educational Innovation through Open Resources”, offered in Coursera, can be
catalogued as continuous training; although it’s access was not restricted, it was designed
mainly for basic education teachers in Mexico. Two Head Professors who have ample
experience in the design of online courses, the use of Open Education Resources and
Educational Technology designed it. The context of the MOOC’s creation is within a prominent
Mexican University, leader in Educational Technology and the first Mexican University to
impart courses via satellite in the mid 90’s. This University has offered online courses through
their virtual campus for over 20 years.
The course covers the subject of the selection, use and reuse of open educational resources,
the possibilities the repositories that house these materials have, search strategies and
integration into educational processes, as well as measuring and assessing their impact on
learning of the participants. Thus, the participant would develop digital skills and instructional
design skills to integrate open educational resources (OER) in their learning environments
through open educational practices.
In four modules, participants were able to watch videos or read about the course’s topics, and
interacted with other participant in discussion boards by answering opinion questions. Digital
portfolios and self and peer evaluations were used to assess the students’ understanding of
how to integrate OER in institutional and learning processes in their own learning
environment.
5
Research Population and Sample
According to the statistics provided by the platform, 20,400 people registered for the course,
which started in September of 2013. From the initial population, 4,407 participants completed
the instrument called, “Pre-diagnosis survey” and 3,547 people answered the “Initial survey.”
The data of each participant was given a unique identification code, which cannot be
duplicated; by combining these two registers, we obtained 5,854 participants who were
considered as the study sample. Table 1 shows the results of both surveys.
Table: 1
Results from Pre-diagnostic and Initial Survey
Instrument
Participants
Pre-diagnostic survey
2,307
Initial survey
Both instruments
Participants of the research population
%
39.4
1,447 24.7
2,100 35.9
5,854 100.0
Considering the information of 5,854 out of 20,400 people who registered, it was important to
confirm if the number of existing cases permitted a statistical analysis in order to identify
significant differences among the constructs. The formula to calculate the sample of finite
populations was used; in Social Sciences research, the maximum sampling error is 5%, and
although this data was not available, 5,854 of the participants who completed either the prediagnosis or the initial survey correspond to a sampling error of 1.2%, considered statistically
significant.
Instruments
The data collection instruments were created by the head professors of the MOOC; there
following 6 surveys were applied and used for collecting data:
Ø
Ø
Ø
Ø
Ø
Ø
Pre-diagnosis survey: is a structured questionnaire with 49 questions, combining
closed questions, multiple options and weighted options using Likert rating scale.
This instrument collects information about: general student data, MOOCs
perceptions, skills and knowledge of information technologies, use of search
engines, use of OER, Innovation and open education movement,
Initial survey: collects general information on participants such as age, sex, marital
status, country of residence, education, experience in online education, computer
and internet connection type, social networks used, among others. Additionally,
survey asked about the reasons for registering in the course, the level of
commitment and hours per week to devote to the course.
Topic 1 self-assessment: 15 multiple choice questions regarding the topic 1 Open
educational movement.
Topic 2 self-assessment: 15 multiple choice questions regarding the topic 2 Search
of educational resources.
Topic 3 self-assessment: 15 multiple choice questions regarding the topic 3 Use of
open educational resources in learning processes.
Topic 4 self-assessment: 15 multiple choice questions regarding the topic 4
Mobilization of open educational resources in learning environments.
These instruments do not have psychometric test results and do not correspond to an
evaluation research design, but rather an exploratory design. They were completed online by
participants using the platform Coursera.
6
Research Procedure
During the first week of the course, the pre-diagnosis and initial electronic surveys were
administrated; a link was provided thru the platform, and e-mail notification was sent to all
the registered participants. The instruments were completed virtually and voluntarily; the
results show that more than 70% of the enrolled students did not answer the surveys.
The self-assessment instruments for topics 1 to 4 were provided at the end of each week thru
a direct link. As the course moved forward, the number of participants who completed the
instruments decreased. Table 2 shows that at the end of the first week, 30% of the participants
delivered evidence of their work, which diminished to a 15.6% in the last week of the course.
Table: 2
Level of participation throughout the course
Instrument
Participants
%
Research population
5854
100.0%
Topic 1 Self-assessment
1779
30.4%
Topic 2 Self-assessment
1165
19.9%
Topic 3 Self-assessment
967
16.5%
Topic 4 Self-assessment
911
15.6%
RESULTS ANALYSIS
Using a quantitative method, in this research, descriptive and econometric statistics were used
to calculate the retention and terminal efficiency rates of the course, to identify the features
of students who completed the course, as well as the causes of dropout and abandonment.
Finally, a probabilistic model was created to identify the weight of each one of the dropout
factors and thus evaluate the terminal efficiency of the MOOC “Educational Innovation through
Open Resources”.
Retention and Terminal Efficiency Rates
The databases were processed in SPSS (Statistical Package for the Social Sciences) and STATA,
in order to calculate the MOOCs’ retention rate by dividing the number of participants who
completed the last self-assessment (Topic 4) by the total number of students who fulfilled the
first instruments (pre-diagnosis and initial survey).
Table 3 shows the retention and terminal efficiency results of the MOOC, regarding the gender
and total participants. 14.5% of retention was reported, meaning 818 participants who
remained engaged until the last week of the course; while 11.7%, 683 participants, delivered
all four topic’s self-assessments.
Table: 3
Terminal efficiency according to gender
Efficiency
Female
Male
Total percentage
Desertion
Retention
Incomplete
Completed
82.2%
17.8%
85.5%
14.5%
82.4%
17.6%
84.3%
15.7%
86.0%
14.0%
88.3%
11.7%
Total
number
5,036
818
5,171
683
It is interesting, that when comparing the retention results (14%) and terminal efficiency
(11.7%) of the course, the percentages are similar to those denoted by the University of
Toronto which reported 8% average of terminal efficiency (Harrison, 2013), 10% reported by
Miriadax (SCOPEO, 2013), and 10% reported by Lushnikova et al. (2013).
7
Features of Students who Completed the Course
Researchers carried out a comparative analysis of the characteristics of the persons who
abandoned the course against those who remained, and the features confrontation of those
who completed the course and those who did not deliver the self-evaluation assessments. This
analysis shows that the students who possess a master’s degree or higher are more likely to
remain in the course, rather than those who only have a professional degree or lower
educational level (Table 4). The persons who did not have previous experience with online
education had lower rates of completion and terminal efficiency (Figure 1).
Table: 4
MOOCs Terminal efficiency according to educational level
Educational Level
Student’s retention
Terminal efficiency
High school
11.4%
10.7%
Technical career
9.0%
8.0%
Undergraduate degree
14.4%
12.1%
Master’s degree
19.0%
15.9%
Doctorate
Post-doctorate
20.1%
28.2%
17.2%
23.1%
20
15
10
5
0
Retention
Terminalefficiency
Experienced inonlineeducation
Unexperienced inonlineeducation
Figure: 1
Terminal efficiency in the MOOC according to experience with online courses.
Additionally, results show that the participants who expressed more initial commitment
presented higher completion and terminal efficiency rates; these participants planned to
complete all the activities and evaluations to obtain a diploma and registered to the course as
a way to complement their previous studies. On the contrary, the people who registered out
of curiosity or who were not committed to the activities registered lower completion and
terminal efficiency rates. These results confirm the statements by Cabrol & Székely (2012),
regarding the importance of relevant education as a strategy to avoid academic failure and
desertion. Likewise, Alemán, Sancho-Vinuesa y Gómez-Zermeño (2015) highlight the need for
resource and strategy analysis under selection criteria.
Individuals who expressed to have economic stability, either full-time or part-time workers,
business owners, at home work or people who have a flexible schedule, reported higher
completion and terminal efficiency rates, as opposed to those who study in high school or a
undergraduate degree.
It is important to mention that the participants who described themselves as self-learners
obtained higher completion and terminal efficiency rates.
8
Regarding the features of the participants with higher completion rates, they displayed a
proficient use of information technologies, of digital resources design, intermediate English
level, knowledge organization skills, participation in research networks, and other
characteristics. In relation to the people who described themselves as pro-active, there were
no significant differences in the results of completion and terminal efficiency.
On the contrary, the people without knowledge about copyrights, web information
administration, use of OER in the classroom, and lack of experience in research networks
presented higher abandonment of the course.
It must be noted that the previously mentioned characteristics have significant statistic
differences, which were validated by the Pearson’s chi-squared test, at 95% confidence
interval.
Causes of Dropout and Abandonment
Coursera politics do not allow e-mail sharing in order to avoid spam. Therefore, it was not
possible to administrate a sanctioned follow-up survey to explore the specific reasons some
participants had when deciding to dropout or abandon the course. As an alternative, a
reflection about various messages shared on the discussion forums was made. Among the
stated reasons that may cause the discouragement of the participants and to abandon the
course were:
Ø Difficulties with the structure of the course, and lack of a tutorial to guide users.
Ø The quality of the materials was also criticized.
Ø Family reasons and no availability for the course.
Ø Limitations on the use of information technology or in the English language.
Ø Limitations of the Coursera platform.
Probabilistic Model to Evaluate Terminal Efficiency of MOOC
Given the results, the terminal efficiency of the MOOC was analyzed through the construction
of a probabilistic model in order to quantify the weight of the main features of participants
who do not complete the course. The main results of the models (table 5) are:
The odds of desertion of the MOOC increases 5.7% when the participant has an
undergraduate or lower degree, and the probability rises 5% when the student does
not have knowledge about copyrights. On the contrary, the odds of desertion
diminishes 7% if the participant is older than 55 years old, 17% when they show a
strong commitment to the MOOC and 4.2% when they have a full-time or part-time
job
Ø The odds to complete the MOOC increases by 3.2 % when the participant is female
and 3.8 % when it has no copyrights knowledge. By contrast, the odds of not
completing decreases 8% when participants are over 55, 15 % when they have a
strong commitment, and another 3.2 % when they are excited by applying course’s
knowledge in their practice as teachers or daily life.
Ø
9
Table: 5
Probabilistic model of the participants who do not complete an MOOC
Traits of the participant
Desertion
Dropout
Female
0.0187
0.0323*
Older than 55 years old
-0.0698*
-0.0803**
Experienced in online education
-0.02
-0.015
Does not have a degree (high school or technician)
0.0568*
0.0396
Full-time or part-time job
-0.042**
-0.021
Plans to accomplish activities and tests to obtain certificate
-0.1702**
-0.1499**
Null (0 - 20%) - IT domain to create audio, video, images,
etc.
0.0451
0.0423
Null (0 - 20%) – Knowledge about copyrights
0.0501**
0.0382*
Not important – Research filters
-0.0491
0.0215
Null (0 - 20%) I do not know the English language
0.0271
0.0245
Lack of confidence – During information research
0.0989
0.1115
Self-taught (Constantly updating my knowledge)
-0.0031
-0.0165
0.003
-0.0026
-0.0756
-0.0526
0.0001
0.042
-0.0226
-0.0316*
-0.0085
-0.0169
0.0306
0.022
Null (0 - 20%) - Knowledge of use of techniques and
methods to organize knowledge in an accessible and
considering scientific objectives, observable facts, and /
or measurable
Null (0 - 20%) - Domain to communicate in virtual
environments
Null (0 - 20%) - Domain to determine credibility of
information
To complement my classes (design and/or prepare
courses)
Uncertain, because they do not know what students will
think of the use of open resources
Does not participate in research network
Not willing to participate as facilitator or Teaching
0.0092
0.0166
Assistant
Note: ** significant at 95 % confidence level * significant at 90 % confidence.
For probabilistic models, the dependent variable is constrained between zero and one, being
derived from the cumulative distribution function (Gujarati, 1997). One way of evaluating the
probabilistic models is derived from the goodness of fit (R2); however, when dealing with
nonlinear models the goodness of fit is meaningless in terms of the defined coefficient of
determination. The pseudo R2 of the model to neglect and no completion corresponds to 0.0249
and 0.0252, respectively. However, note that by supplementing with another statistic shows
that the model correctly classifies drops to 75% of cases, whereas the model for not completed
correctly classified 78% of instances. So the models can be considered quite acceptable for a
multi factorial phenomenon as desertion and abandonment.
CONCLUSIONS
The main results of this research reveal low terminal efficiency rate of a MOOC, which was
offered by a higher education institution. Although there was a positive response from the
students, the percentage of participants who successfully completed the course indicates the
opposite; therefore, it is important to study the reasons that led the participants to enroll and
the causes of desertion.
10
The MOOC analyzed in this study had a rate of 11.7 % completion rate, which represents the
number of students who delivered their respective assessments and answered throughout the
course evaluations. In contrast, the high dropout rate of 86% agrees with the statements of Clow
(2013), who mentions that the abandonment of online courses is higher than in classroom
education. This result is parallel with the report of the University of Toronto, which showed a rate
of approximately 8% of students who completed the course (Harrison, 2013). Similarly, Lushnikova
et al. (2013) indicate that about 10 % of the students who enrolled in a MOOC managed to complete
the course. In this connection, Siemens and Tittenberger (2009) note that desertion rates can be
minimized by upgrading the course components that lead to an increase in the motivation levels
and better student-faculty relationships.
This study identified the main characteristics of the participants who managed to stay and complete
the course, being favored those with graduate degrees, online educational previous experience,
greater commitment to the course and economic stability. Other found features were the advanced
or expert proficiency in the use of information technology, advanced proficiency in creating digital
resources, intermediate English language skills, advanced proficiency in the use of techniques and
methods to organize knowledge and active participation in research networks, among others. On
the other hand, those who decided to leave the course indicated problems with the structure and
guidance in the course, limitations on the use of information technology or in English, in addition
to the limited availability of time due to family or work reasons. It is noteworthy that among the
deserters were participants with a high school or bachelor education who do not participate in
research networks, which is consistent with the statement made by Siemens (2005), who defines
the research groups as a means to update the knowledge and maintain connections for continuous
learning.
The results of the probabilistic models constructed to measure the weight of the characteristics of
participants who drop out or fail to complete a MOOC course, reflect that the participants’ likelihood
to leave the MOOC course increases when the participant has a lower educational degree level and
has no knowledge of copyrights. On the contrary, the probability of abandonment decreases when
participants are over 55, have a strong commitment to the MOOC and when they have full or partial
employment. In terms of completeness, the chances of not completing the MOOC increases when
the participant is female and does not have any knowledge of copyrights. By contrast, the odds of
not completing decreases when participants are over 55 when they have a strong commitment, and
when they are excited by applying knowledge of the course in their practice as teachers or daily
life.
In light of the results obtained in this research, two possible courses of action arise as strategies to
increase the level of awareness of the terminal performance of MOOCs’ participants: First, the
application of surveys to students who decide to leave the course to obtain additional information
about their reasons. Second, to increase the level of terminal efficiency of MOOCs, it is proposed to
include in the course’s structure items such as a welcome tutorial to guide novice users in this type
of courses, on their function and structure; organize discussion forums by language, country or
thematic affinities, and improve the quality of the videos and captions.
These recommendations are consistent with the approach of Aguaded (2013) who states the need
to strengthen areas, such as interaction with the facilitators, collaborative and interactive work,
respect cultural and linguistic diversity, for MOOC constituting an exceptional learning experience.
Similarly, for the effectiveness of these courses you must create a scaffold to guide and help the
participants to achieve their learning goals (Salmerón, Rodríguez, & Gutiérrez2010).
This research enables institutions that offer MOOC courses to consider the characteristics of
the participants, in order to achieve greater efficiency and lower desertion rates. Thus, the
educational practices in MOOC will benefit by improving their implementation and continue
gathering information on new experiences in such resources.
11
BIODATA and CONTACT ADDRESSES of the AUTHORS
Prof. Dr. Marcela Gerogina GOMEZ-ZERMENO holds a doctorate in Educational
Innovation from Tecnológico de Monterrey, and a master’s degre in Information
and Communication Technology Engineering Sciences. INT-CITCOM, France
Télécoms Higher Education. She also holds a bachelor’s degree in Computer and
Administration Systems from ITESM. She is a tenured lecturer at Tecnologico de
Monterrey’s masters degree programs in Education and in Educational Technology,
as well as on the doctoral program in Educational Innovation. She is a member of
the the Mexican Education Research Council (COMIE). She is the technical
manager on educational research projects of the Mexican National Council of Science and
Technology (CONACYT) and on the ALFA program of the European Commission. She forms part of
the National System of Researchers (SNI) Level 1.
Prof. Dr. Marcela Gerogina GOMEZ-ZERMENO
Tecnológico de Monterrey, Campus Monterrey,
Edificio CEDES, Ave. Eugenio Garza Sada, 2501 Sur,
CP 64849 Monterrey, N.L., MÉXICO.
Phone: +52 81 16461430.
Email: marcela.gomez@itesm.mx
Lorena ALEMAN DE LA GARZA is a doctoral candidate on the Education and
ICT (e-learning) doctoral program at the Open University of Catalonia (UOC),
Spain. She holds a master’s degree, with honors, in Educational Institution
Administration from ITESM, and a bachelor’s degree, with honors, in Business
Administration from TecMilenio University, Mexico. She has worked as a
postgraduate lecturer at Tecnológico de Monterrey’s masters degree
programs in Educational Institution Administration, in Education and in
Educational Technology. She is the technical manager on educational research
projects of the Mexican National Council of Science and Technology
(CONACYT). She currently is the director of Continuing Education at Tecnológico de Monterrey.
Lorena ALEMAN DE LA GARZA
Tecnológico de Monterrey, Campus Monterrey,
Edificio CEDES, Ave. Eugenio Garza Sada, 2501 Sur,
CP 64849 Monterrey, N.L., MÉXICO.
Phone: +52 81 16461435.
Email: lorena.aleman@itesm.mx
REFERENCES
Aguaded, J.I. (2013). La revolución MOOCs, ¿una nueva educación desde el paradigma
tecnológico? Comunicar, 41, 07-08.
Alemán de la Garza, L.Y., Sancho-Vinuesa, T. & Gómez-Zermeño, M.G. (2015). Indicadores
para evaluar la calidad de un curso en línea masivo y abierto para la actualización
docente. Revista Universidad y Sociedad del Conocimiento, 12(1), 104-118.
Alemán, L., & Gómez-Zermeño, M. G. (2012). Liderazgo Docente para la Enseñanza de la
Innovación. Revista de Investigación Educativa, 4(2), 2-7.
Cabrol, M. y Székely, M. (2012). Educación para la Transformación. Washington, DC: Banco
Interamericano de Desarrollo.
12
Clow, D. (2013). MOOCs and the Funnel of Participation. The Open University. Retrieved from
http://dougclow.org/mooc-funnel/
Creswell, J. W. y Plano Clark, V. L. (2011). Designing and conducting Mixed Method Research
(2a ed.). Thousand Oaks CA, USA: Sage.
Fini, A. (2009). The Technological Dimension of a Massive Open Online Course: The Case of
the CCK08 Course Tools. The International Review Of Research In Open And Distance
Learning, 10 (5).
Gómez-Zermeño, M. G. (2012). Digital Libraries: Electronic Bibliographic Resources on Basic
Education. Comunicar, 20(39), 119-126.
Gómez-Zermeño, M. G., Rodríguez Arroyo, J. A. y Márquez Guzmán, S. (2013). Estudio
Exploratorio-Descriptivo ʺCurso Híbrido: Contabilidad Vʺ. Revista de Investigación
Educativa de la Escuela de Graduados en Educación, 4(7), 70-79.
Gujarati, D. (1997). Econometría Básica. Colombia: McGraw Hill.
Harrison, L. (2013). Open UToronto MOOC Initiative: Report on First Year on Activity.
Toronto: University of Toronto.
Liyanagunawardena, T., Adams, A., y Williams, S. (2013). MOOCs: A systematic study of the
published literature 2008-2012. The International Review of Research in Open and
Distance Learning, 14(3).
Lushnikova, N., Chintakayala, P. & Rodante, A. (2013). Massive Open Online Courses from Ivy
League universities: benefits and challenges for students and educators. XI
International Conference “Providing continuity of content in the system of stepwise
graduate and postgraduate education", Ukraine, November 15-16, 2012.
McAuley, A., Stewart, S., Siemens, G. y Cormier, D. (2010). The MOOC Model for Digital
Practice. Canadá: University of Prince Edward Island.
Mortera, F. (2012). Internet, los Recursos Educativos Abiertos y el Movimiento Abierto. Red
Latinoamericana Portales Educativos (RELPE). Retrieved from:
http://www.relpe.org/destacados/internet-los-recursos-educativos-abiertos-y-elmovimiento-abierto/
Rodríguez, O. (2012). MOOCs and the AI-Stanford like Courses: Two Successful and Distinct
Course Formats for Massive Open Online Courses. European Journal of Open, Distance
and E-Learning. Retrieved from: http://files.eric.ed.gov/fulltext/EJ982976.pdf
Salmerón, H., Rodríguez, S. y Gutiérrez, C. (2010). Metodologías que optimizan la
comunicación en entornos de aprendizaje virtual. Comunicar, 34, 163-171. DOI:
10.3916/C34-2010-03-16.
SCOPEO (2013). MOOC: Estado de la situación actual, posibilidades, retos y futuro. Scopeo
Informe No. 2.
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International journal
of instructional technology and distance learning, 2(1), 3-10.
Siemens, G. y Tittenberger, P. (2009). Handbook of Emerging Technologies for Learning.
Retrieved from: http://elearnspace.org/Articles/HETL.pdf
UNESCO (2002). Forum on the impact of open courseware for higher education in developing
countries: final report. Paris: UNESCO.
UNESCO (2012). Declaración de París de 2012 sobre los REA. Congreso Mundial sobre los
Recursos Educativos Abiertos (REA). Paris: UNESCO.
13
Valenzuela, J. R. y Flores, M. (2012). Fundamentos de investigación educativa, Volumen 2.
Monterrey, México: Editorial Digital Tecnológico de Monterrey.
Wiley, D., & Hilton III, J. (2009). Openness, Dynamic Specialization, and the Disaggregated
Future of Higher Education. The International Review of Research in Open and Distance
Learning, 10(5).
14
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 2
PRE-SERVICE EFL TEACHERS’ SELF-EFFICACY BELIEFS, GOAL
ORIENTATIONS, AND PARTICIPATIONS IN AN ONLINE
LEARNING ENVIRONMENT
Hasan UCAR
Bilecik Seyh Edebali University, Bilecik, Turkey
Prof. Dr. Mujgan YAZICI BOZKAYA
Open Education Faculty
Anadolu University, Eskisehir, Turkey
ABSTRACT
This study examined the pre-service EFL teachers’ self-efficacy beliefs, goal orientations,
and participations in an online learning environment. Embedded mixed design was used in
the study. In the quantitative part of the study, the participants were 186 senior pre-service
EFL teachers and data were collected on two scales and a questionnaire. Qualitative data
were collected in form of one-on-one interviews from 2 pre-service EFL teachers, the most
representative of the population, to understand the motivation and behaviour variables.
The findings of this research revealed that pre-service EFL teachers’ self-efficacy believes
are high but fragile. However, some of the participants had more than one goal orientation.
The mastery and performance oriented pre-service teachers displayed different
characteristics of motivation. Moreover, few of the pre-service EFL teachers participate in
the online learning environment. Results also showed several positive associations
between teachers’ goal orientations and self-efficacy beliefs. The results as well as their
implications are discussed and suggestions for future research are presented.
Keywords: Pre-service EFL teacher, self-efficacy, achievement goal orientation
INTRODUCTION
Teachers’ self-efficacy beliefs and goal orientations have significant implications in
education settings. Teachers are one of the most important components in education
systems. Their beliefs and attitudes during education process affect their behaviours in
teaching (Bandura, 1997). Recent studies done in the field of education have showed that
knowledge and skills are not adequate for active teaching. Teachers’ attitudes and beliefs
have also been found to be contributing to their effectiveness as educators (Bandura, 1997;
Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998). Even though there are many studies on
students’ motivation for learning, there has been little research on teachers’ motivation for
teaching (Retelsdorf, Butler, Streblow, & Schiefele, 2010).
One of main objective in education process is to reach a goal. To achieve this goal, many
variables interact with each other. The main variables that affect the teachers, the learners,
and the teaching and learning environment are self-efficacy and goal orientation
constructs. The first construct, self-efficacy belief, has been mostly studied in education
area in the last two decades. Self-efficacy belief refers to perception of one’s own ability in
organizing and completing a task successfully (Bandura, 1997). It has been applied to
understanding how teachers’ thoughts about their competence in classroom teaching,
students’ achievement and management of the classroom. Chacon (2005) also reported
that teachers’ sense of efficacy influences teachers’ actions and student outcomes. It is
also accepted that one of the most important factors affecting students’ perception and
15
goal orientation is the teacher (Afsaneh & Safoura, 2015). Beghetto (2007) and Egel
(2009) also stated that it is important for researchers to examine pre-service teachers’
efficacy beliefs about student motivation.
Achievement goal orientation is the second construct, which has been pointed to affect the
teaching and learning environment in numerous studies. This concept is about purposes
and motives that individuals had in a task. This variable has been used to assess the
students’ motivation for learning but later it has begun to be used to understand the
teachers’ motivation, as well (Butler, 2007). Kucsera, Roberts, Walls, Walker, and Svinicki
(2011) reported that achievement goal theory affects many motivation and behaviour
variables in the student and work literatures, but it is still applied specifically to teachers
and teaching. Nitsche, Dickhäuser, Fasching, and Dresel (2011) reported that teachers’
goal orientation is a significant factor for teachers’ individual development of competence.
According to Retelsdorf et al., (2010) achievement goal construct may also be useful for
defining motivation of pre-service teachers.
Pre-service teachers, when compared with experienced in-service teachers, are in closer
touch with updated teaching approaches and in fact, often bring information about new
methodologies to the in-service teachers through teaching practicum (Tang, Lee & Chun,
2012) . However, pre-service teachers’ achievement goals and efficacy belief may change
in terms of learning environments. To date, no study has researched online distance preservice EFL teachers’ psychological incentives, achievement goals, and efficacy belief. In
the present study, we attempt to examine the mentioned variables and assess the
relationships between pre-service teachers’ participation in an online learning environment
and psychological incentives, achievement goals and efficacy belief. This may help those
concerned both educators and administrators in making policy decisions about the learning
environment in order to maintain or increase psychological incentives of the pre-service
ELT teachers.
LITERATURE REVIEW
Historically, the first theory that influenced the first studies on teacher efficacy was
grounded in Rotter’s social learning theory (Tschannen-Moran, Woolfolk Hoy & Hoy, 1998).
This theory also known as Rotter’s locus of control. Locus of control defined teacher efficacy
as the extent to which teachers believed that they could control events that affect them.
There are two kinds of locus of control, internal locus of control and external locus of
control. Teachers with internal locus of control believe that their own actions determine
the outcomes they obtain, while teachers with external locus of control believe that their
experiences are not determined by themselves but by sources outside themselves like
chance, and fate.
Bandura’s social cognitive theory (1997) is another theory, which has been shown to have
a connection to the educational psychology for the last two decades. Bandura’s theory
consists of three components: human agency, outcome expectancy, and efficacy belief. As
Bandura (1997) defined self-efficacy belief is “the beliefs in one’s capabilities to organize
and execute the course of action required to produce given attainments”. According to
Bandura, self-efficacy belief affects individuals in many ways. If the people have high
efficacy, in turn, they will have high effort to accomplish the work that they deal with
(Pajares, 2002). Bandura defined teacher efficacy as a kind of efficacy. Tschannen-Moran
and Woolfolk Hoy (2001) described teacher efficacy as teachers’ belief about their
capabilities to get the desired outcomes of student engagement and learning. Henson
(2001) stated that teachers’ self-efficacy beliefs have been repeatedly associated with
positive teaching behaviours and student outcomes. In addition, self-efficacy is even a
stronger positive predictor for self-regulation (Daal, Donche, & Maeyer, 2014). Bandura
(1997) stated that teachers’ efficacy beliefs are generally open to change during the preservice time. Therefore, this construct should be examined deeply.
16
Achievement goal theory is the third theory that affects the pre-service teachers. It is very
common in the achievement motivation literature. This construct is about the purposes and
motives the individuals get in achievement task (Dweck & Leggett, 1988). It consists of
four constructs. These are: mastery-approach, mastery-avoidance, performance-approach,
and performance-avoidance achievement goal orientations (Elliot & Murayama, 2008).
Learners with approach goals try to master learning tasks and they do their best to
completely acquire the subjects, while students with avoidance goals avoid negative
results such as failure while mastering the tasks (Elliot & McGregor, 2001). In other words,
in approach aspects (mastery-approach and performance-approach) learners believe in
themselves to do well but in avoidance aspects (performance-avoidance and masteryavoidance) these learners doubt about their ability to perform well (Coutinho & Neuman,
2008). Kucsera et al., (2011) reported that achievement goal theory affect many motivation
and behaviour variables in the student and work literatures, but it is still applied specifically
to teachers and teaching. Nitsche et al. (2011) reported that teachers’ goal orientations are
significant factors for teachers’ individual development of competence. Retelsdorf et al.
(2010) cited that achievement goal construct may also be useful for defining motivation of
pre-service teachers.
The literature provides proofs that self-efficacy and achievement goal orientations are
contributing factors of success of learners and pre-service teachers (Afsaneh & Safoura,
2015; Bandura, 1997; Coutinho & Neuman, 2008; Elliot & McGregor, 2001). However, there
is a gap in the literature that identifies and links self-efficacy and achievement goal
orientation to online pre-service EFL teachers. This study adds evidence and knowledge to
the literature.
Goal of the Study and Research Questions
The study aimed to explore pre-service EFL teachers’ self-efficacy beliefs, goal orientations,
and participation in the online learning environment and examine the relationships among
these variables.
The research questions that guide this research are as follows:
 What is the level of self-efficacy beliefs of the pre-service EFL teachers?
 What kind of achievement goal orientations do the pre-service EFL teachers
have?
 Is there a relationship between the pre-service EFL teachers’ self-efficacy beliefs
and achievement goal orientations?
 Do pre-service EFL teachers’ self-efficacy beliefs change according to status of
participation in the online learning environment?
 Do pre-service EFL teachers’ achievement goal orientations change according to
status of participation in the online learning environment?
METHOD
Research Design
Embedded mixed design, which is one of the mixed method design, was used for this study.
The purpose of the embedded design is to collect quantitative and qualitative data
simultaneously or sequentially, but to have one form of data play a supportive role to the
other form of data (Cresswell, 2012:544). In this study a sequential design was used with
the embedded design. That is to say, quantitative data as a primary form was used to inform
the qualitative phase. For the quantitative part of the study, pre-service EFL teachers who
volunteer and who agree attended the study. The data were collected from 186 convenient
participants. The representative sample is accepted at 95% confidence level, 5.95%
margin of error, and 50% response distribution. Three instruments, namely English
Teachers’ Sense of Efficacy Scale (ESTES), Achievement Goals Questionnaire-Revised
(AGQ-R), and demographic and online learning environment questionnaire were used. The
quantitative information represented a major source of information for this study. For the
qualitative part, data were collected in the form of one-on-one interviews to understand
the beliefs, goals and perceptions of the pre-service teachers at first hand.
17
Quantitative Data Collection and
Analysis
Interpretation
Qualitative Data Collection
and Analysis
Figure: 1
The study design (Creswell, 2012)
Participants of the Study
The population consisted of pre-service EFL teachers enrolled at Distance English Language
Teacher Education BA program at College of Open Education, Anadolu University in Turkey.
This program has a blended model of instruction, supplies both face to face, and distance
education. The first two years of the program are conducted mainly through traditional
classroom instruction, and the third and fourth years of the program are conducted by
means of distance education supported by online courses through the online learning
environment, that is asynchronous Web-based course management tool. Online component
of the program aims to provide guidance to students. Before the main quantitative study,
38 pre-service EFL teachers consented to participate voluntarily to the face-to-face pilot
study. For the main study, 186 pre-service teachers participated. There were 144 females
and 42 males students. The age range of the sample was 21 years to 30 years. Table 1
provides the demographic information for the population, and for the sample used in this
study. As seen in Table 1, the proportions of the gender and age within the sample are
generally representative of the population.
Table: 1
The proportions of the gender and age within the sample and population
Sample
(n=186)
Population
(N=588)
Gender
Female
77.4%
76.7%
Male
22.6%
23.3%
Age
21-23
53.2%
56.7%
24-30
46.8%
43.3%
Qualitative part of the study was consisted of two one-on-one interviews. Participants of
the interviews were two pre-service EFL teachers. The participants were purposefully
selected from 186 pre-service EFL teachers who completed the English Teachers’ Sense of
Efficacy Scale (ESTES) and Achievement Goals Questionnaire - Revised (AGQ-R), and the
questionnaire. They were selected for the one-on-one interviews because their scores on
the scales and the questionnaire identified them as the most representative of the
population.
18
Table: 2
Features of the participants in the qualitative phase
Use of the Online Learning
Environment
Pre-service EFL
Teachers
Gender
Goal
Orientations
SelfEfficacy
PST1
Female
High mastery
Low
performance
High
Yes / Active
PST2
Female
Low mastery
High
performance
Medium
Yes / Not Active
Data Collection Instruments
The data were obtained, primarily, via two scales, namely English Teachers’ Sense of
Efficacy Scale (ESTES) (Chacon, 2005) and Achievement Goals Questionnaire - Revised
(AGQ-R) (Elliot & Murayama, 2008). The participants also responded to the demographic
and online learning environment questionnaire. For the qualitative part, data were
collected through two one-on-one interviews.
English Teachers’ Sense of Efficacy Scale (ESTES) consists of five subscales. In this
research, only adapted version of Teachers’ Sense of Efficacy Scale (TSES) (TschannenMoran & Woolfolk Hoy, 2001), with 12 items including four items for each of the three
dimensions was used to assess pre-service EFL teachers’ self-efficacy beliefs. The measured
three subscales are: Teachers’ efficacy for engaging students learning in EFL, teachers’
perceived efficacy for managing EFL classes, and teachers’ perceived efficacy for
implementing instructional strategies to teach EFL.
Achievement Goals Questionnaire - Revised (AGQ-R). The AGQ-R is a 12 item, 5-point Likert
scale questionnaire used to measure achievement goal orientations namely masteryapproach, mastery-avoidance, performance-approach and performance-avoidance. The
demographic information section, which was developed by the researchers, includes
questions about gender, age, educational background, and teaching and learning
experience of the pre-service EFL teachers. The last part of the questionnaire, which was
developed by the researcher and includes both Likert type and open-ended questions, is
about the students’ perceptions of and participation in online learning environment.
In qualitative one-on-one interviews, open-ended questions below were asked to the preservice EFL teachers:
 How do you describe yourself as a teacher/student?
 What are your goals (personal/academic/professional)?
 What do you do when you faced a very difficult academic task?
 What do you think about the relationship between ability and success?
 What do you do when you faced a challenging situation in the classroom?
 What do you do to get students to believe they can do well in English?
 How do you react when your students are confused?
 Do you participate in online learning environment? What is your intend use of
online learning environment?
Procedure
A pilot study was conducted before the main quantitative study. The aims of conducting
this pilot study were to find out whether the questions were clear or not and
understandable enough and to learn whether an addition to the data collection tool was
necessary. To conduct the pilot study, the researchers emailed all the pre-service EFL
teachers. Out of the 588 teachers, 38 consented to participate voluntarily to the face-toface pilot study. After the piloting procedure, which lasted for a month, the researchers
performed minor revisions regarding to language and grammar of the survey. The survey
19
link was then put on the online course room and the discussion board and participants were
asked to complete the survey thoroughly. If the learner agreed to participate in the study,
he/she completed the survey, and then submitted the completed the one-time survey
through the secure online link. The participants voluntarily consented to participate in the
study without incentives. At the end of the survey, which stayed for a month in the online
learning environment, 186 participants were attended the study. To support the primary
quantitative data, supportive qualitative data were added. Out of the 186 participants, 2
pre-service EFL teachers were purposefully selected for the one-on-one interviews. The
representative pre-service teachers were contacted by telephone for the interview and
each interview was scheduled for an hour.
Data Analysis
The quantitative data analysis was done using the SPSS program for Windows, and content
analysis was conducted in order to analyse the qualitative data obtained from the
interviews. The answers to each question in the interviews were coded and categorized by
the authors.
RESULTS
Quantitative Data
Research Question 1: What is the level of self-efficacy beliefs of the pre-service EFL
teachers?
Descriptive statistics for self-efficacy belief are presented in Table 3.
Table: 3
Descriptive statistics and Cronbach alpha measures for self-efficacy beliefs scale (n=186)
Self-Efficacy Belief
M
Sd
Min.
Max.
Cronbach Alpha
7.14
1.27
3.00
9.00
0.92
The results shown in Table 3 suggest that most of the pre-service EFL teachers in the
Distance English Language Teacher Education Program have high efficacy beliefs. That is
to say, the pre-service EFL teachers believe that they are efficacious in engaging students
learning, managing EFL classes, and implementing instructional strategies. This result is
noteworthy as Bandura (1997) stated that teachers’ self-efficacy beliefs in their
instructional efficacy affect the learning environment. In addition, as Lee & Yuan (2014)
stated, pre-service teachers with high self-efficacy beliefs might be able to think positively
of their future teaching practice and feel more motivated towards teaching despite the
possible challenges they may encounter.
Research Question 2: What kind of achievement goal orientations do the pre-service EFL
teachers have?
Descriptive statistics for achievement goal orientations are presented in Table 4.
Table: 4
Descriptive statistics and Cronbach alpha measures for achievement goal orientations
scale (n=186)
AGO
M
Sd
Min.
Max.
Cronbach Alpha
3.60
0.93
1.00
5.00
0.89
According to Table 4, results indicated a difference in the pre-service EFL teachers’ goal
adoptions. These results suggest that the pre-service EFL teachers adopt more than one
achievement goal, and mostly mastery goals for learning are adopted. This result can be
interpreted as positive since teachers adopting mastery goal orientations seek challenging
tasks and do well in difficult situations. However, mastery goal orientations involve the
20
Engaging
Students
Learning
Managing
EFL
Classes
Implementing
Instructional
Strategies
General
SelfEfficacy
MasteryApproach
PerformanceAvoidance
PerformanceApproach
Managing EFL
Classes
0.665**
Implementing
Instructional
Strategies
0.704**
0.686**
General SelfEfficacy
0.890**
0.886**
0.890**
MasteryApproach
0.156*
0.244**
0.207**
0.228**
PerformanceAvoidance
0.014*
0.049*
0.080*
0.053*
0.241**
PerformanceApproach
-0.016*
0.064*
0.039*
0.032*
0.343**
0.703**
MasteryAvoidance
0.241**
0.205**
0.228**
0.253**
0.653**
0.424**
0.358**
General AGO
0.107*
0.162*
0.162*
0.161*
0.664**
0.824**
0.826**
MasteryAvoidance
0.749**
development of competence through task mastery and the emphasis is placed on
developing new skills (Lindsay, 2010).
Table: 5
Difference in the pre-service EFL teachers’ goal adoptions
Research Question 3: Is there a relationship between the pre-service EFL teachers’ self-
efficacy beliefs and achievement goal orientations?
The present study also aimed at exploring the possible association between the subscales
of goal orientation and self-efficacy. The results of the third research question revealed the
effect of mastery goal on self-efficacy and it showed among goal orientations, mastery goal
is also positively but not significantly predicts self-efficacy. Correlation analyses performed
between the pre-service EFL teachers’ self-efficacy beliefs and achievement goal
orientations are reported in Table 5. According to the Table, there are significant
correlations at p<0.01 level among pre-service EFL teachers’ self-efficacy subscales and
achievement goal subscales. However, as expected, self-efficacy beliefs were correlated to
achievement goal orientations (r=0.16, p<0.05). Mastery approach was positively but
weakly related to engaging students learning (r=0.15, p<0.05), managing EFL classes
(r=0.24, p<0.01), implementing instructional strategies (r=0.21, p<0.01), and general
self-efficacy (r=0.23, p<0.01). The results also showed no significant relationship between
performance approach and self-efficacy variables. In addition, performance avoidance had
no significant relationship to self-efficacy subscales, either. These findings have been found
to fit to several researchers’ studies (Coutinho & Neuman, 2008; Eryenen, 2008; Hsieh,
Sullivan & Guerra, 2007). A research done by Coutinho and Neuman (2008) and Zafarmand,
Ghanizadeh, and Akbabi (2014) stated that mastery-approach and performance-approach
achievement goals were positive predictors of self-efficacy beliefs. However, Elliot and
McGregor (2001) reported that mastery-avoidance has positive connection with fear of
failure and negative connection related to self-determination. According to these
researchers, it seems unlikely that individuals with this goal orientation would have
confidence in their ability to achieve desired outcomes. In addition, performance-avoidance
21
is generally associated with poor performance, so individuals who routinely perform poorly
are unlikely to believe that they have the ability to perform well (Lindsay, 2010).
Research Question 4: Do pre-service EFL teachers’ self-efficacy beliefs change according to
status of participation in the online learning environment?
According to findings given in Table 6, there were no statistically significant difference
between self-efficacy belief and participation in the online learning environment, t (184)=
-0,111, p=0,912. It has not been found any study done about the relationship between
these variables. However, a study conducted by Sakar (2009) revealed that senior students’
frequency of participation to online learning environment in this program was quite low. It
can be concluded that attendance to the online courses makes no difference to the selfefficacy beliefs of the pre-service teachers, but in order to understand the exact
relationships, more studies are needed.
Table: 6
Self-efficacy beliefs based on status of participation in online learning environment
Participation in Online
Learning Environment
Self-Efficacy
Belief
n
M
Sd
Yes
78
7.13
1.22
No
108
7.15
1.31
t
Cronbach
Alpha
-0.111
0.912
Research Question 5: Do pre-service EFL teachers’ achievement goal orientations change
according to status of participation in the online learning environment?
As shown in Table 7, statistically no meaningful difference existed between achievement
goal orientation and its subscales to status of participation in online learning environment,
t (184) = 0,796, p= 0,427. It has not been found any study done in literature yet.
Table: 7
Achievement goal orientations based on status of participation in online learning
environment
Participation in Online
Learning Environment
AGO
n
M
Sd
Yes
78
3.67
0.78
No
108
3.56
1.02
t
Cronbach
Alpha
0.796
0.427
In addition to these questions, pre-service EFL teachers’ achievement goal orientations and
self-efficacy beliefs are also examined according to gender, age, and work experience
variables. As a result of t-test, it was found out that there were not noteworthy findings
between pre-service EFL teachers’ achievement goal orientations, self-efficacy beliefs and
gender, age and work experience. However, these findings were insufficient to note a
statistically relationship among these variables.
Qualitative Data
In one-on-one interviews, open-ended questions below were asked to the pre-service EFL
teachers. Data cited from the interviews.
How do you describe yourself as a teacher/student?
PST1 says “I am a hardworking student and teacher… and a quick learner.” She also sees
herself as a competent learner and therefore she learns efficiently. “I was always a
22
successful student and I believe that if you study hard you do wonders.” She emphasized
that her aim as a teacher was to learn for learning and this is her primary aim. PST2 says “I
am not very smart student but I study all my lessons and I do my best in the exams… Mostly
I get average grades … I am a student like that… that’s enough for me.” She adds that “If
I didn’t study and get low grades I felt guilty… I don’t want to let my family down… I try
hard to make them feel happy.”
What are your goals (personal/academic/professional)?
PST1 personal goal is to finish the school on time. She added “After I graduated I have to
study harder to teach better… If I give up studying I couldn’t teach effectively… so my goal
is to be a perfect teacher.” She thought that she is a successful teacher and her grades are
proofs for this result. Her academic and professional goals were simple. She wanted to
graduate with an honour degree and began to work as an instructor in a public university.
She added that a teacher should be enthusiastic and wise. That’s why she wants to be an
enthusiastic and wise teacher when she begins to work. For academic goal, PST2 responded
that she wanted to finish the school on time. “The grade point average doesn’t matter for
me … I just want to finish my school and make my father happy and believe in me because
he doesn’t believe that I will finish the school on time.” As a personal goal, she says “After
I graduate, I want to study in an elementary school because I love kids a lot… And I want
to spend all my spare time in my house… with my children... after I graduate I don’t want
to spend my time with challenging situations, exams… I feel tired of these.”
What do you do when you faced a very difficult academic task?
PST1 believes that every teacher can be successful if he/she studies hard. When she faces
a difficult task, first she gets the bottom of the subject. If she didn’t understand it then she
asks her teachers or friends. She emphasized that she never leaves the task incomplete.
She says “When I learn, I learn completely.” PST2 says “It is hard for me to deal with that
tasks… Mostly I lose my motivation on that occasions… so it is better for me not to think
too much on that tasks.” She added that she tried to understand and overcome the difficult
task but mostly she chose to get it out of her way. “If I do the simple tasks and have an
idea about the difficult ones that is enough for me.”
What do you think about the relationship between ability and success?
PST1 believes that one can succeed only when he/she studies hard. “This is a psychological
situation… I believe that ability is nothing without studying… If the teacher has an ability
he/she needs to study to succeed but if he/she has an ability this does not enough for
success…” PST2 responded that “ability is very important factor in success… for example
when I am not good at subject or lesson, I know that I cannot do well, so I don’t force
myself because I know that I don’t have the necessary ability.” She says “… for example I
believe that I don’t have much ability in English so I study hard before the exams and
mostly I get around 70 points… actually it is enough for me…some of my friends don’t
study hard and they get 80-90 points… I think this is because they have the ability for
that.”
What do you do when you faced a challenging situation in the classroom?
PST1 reported that challenging situations were always big problems for teachers. Moreover,
she thinks of the school as her work place. “… and if I am a teacher, I should overcome
these situations and establish a management system in the classroom… When I first enter
23
a classroom I always explain the students my expectations and warn them about their
responsibilities and behaviours”. She says “If a student doesn’t follow the classroom rules,
I speak to him/her separately and warn him/her to follow the classroom rules.” According
to PST2, controlling the challenging situations were very difficult especially with today’s
students. PST2 says “when a problem occurs my lesson entirely ruins … because it takes a
lot time to overcome the challenging situations.” She adds “when I enter a classroom… I
always pray for not to have troubled students because if I have students like these I don’t
feel happy and I can’t motivate myself and the students for the lesson.”
What do you do to get students to believe they can do well in English?
For PST1, motivating the students was the first responsibility of a teacher. She says “I
always smile to students. I believe that if a teacher smile and feel happy the students then
believe in themselves and success. I always remind them that I believe in them.” She
continues “I get through to all students, and make sure that they understand the lesson…
this is very important.” PST2 says “As a teacher I believe in myself and I think every student
should believe in himself or herself before the teacher believes in him or her. If a student
doesn’t believe that he or she can do well…It takes a long time to get him or her to believe…
I always say the students that I believe in them… and I motivate them.”
How do you react when your students are confused?
PST1 says “I am very patient in that situations…. I provide alternative examples to students,
and mostly they understand”. She emphasized that she makes the necessary preparations
to adjust the lesson to all levels of students. PST2 says “I know myself and I always do the
best to motivate the students and help them understand.” She adds “If a student doesn’t
study before he/she comes to classroom, most probably he/she will not understand the
lesson completely and he/she confuses.” According to PST 2 “if a teacher and a student take
care of their responsibilities, everything will be fine.”
Do you participate in online learning environment? If Yes - What is your intend use of online
learning environment?
PST1 participates in the online learning environment. She says “I try to enter the system
every day... I consider myself an active participant”. For the second question PST1 says “I
use the online learning environment because it motivates me and reinforce my learning…
If I don’t use it, I don’t feel myself happy and I feel something missing.” PST 2 says “I don’t
use the online learning environment very frequently… It is not compulsory for us so I just
follow the bulletin board sometimes in case of there is something important.” And she adds
“I don’t think it is useful.” She also adds “Sometimes I enter the system but I can’t find the
necessary materials.”
The qualitative results revealed that the pre-service EFL teachers have different
characteristics and views in terms of goal orientations, self-efficacy beliefs and
participating in the online learning environment. The differences exist between mastery
and performance goal oriented participants (PTS1 and PTS2) are shown on table 8. As seen
in table 8, the characteristics identify the pre-service teachers in terms of achievement goal
orientations, self-efficacy beliefs and perceptions of the online learning environment.
24
Table: 8
The characteristics and views of the pre-service EFL teachers about goal orientations,
self-efficacy beliefs and participating in the online learning environment
Variable
Achievement
Goal
Orientation
Self-efficacy
Belief
Perceptions of
the Online
Learning
Environment
Characteristics
PST1
PST2
Learning aim
Competence, selfimprove
Avoid failure
Motivation
Intrinsic
Extrinsic
Ability
Can be developed
Innate
Effort
To learn
Look-good
Interest in learning
High
Improvement
Choose challenging tasks
Medium/Low
Choose less challenging
tasks
Students engagement
Motivate, improve and
believe in sts
Classroom
management
Control the classroom
easily
Firstly, the sts should
believe in themselves,
motivate
Afraid of disruptive
behaviours
Instructional
strategies
Make preparations for
the lesson, implement
alternative strategies
Make preparations for the
lesson, sts have to take
care of their learning first
Participation
Active user
Not very much/ not
worthwhile
Motivation
Useful to my learning but
it should be improved
Useful but not necessary.
It is not available when
needed
Aim
Enhance leaning,
reinforcement
Follow the bulletin board
DISCUSSIONS
The main purpose of this study was to describe pre-service EFL teachers’ self-efficacy
beliefs, goal orientations, and participations in the online learning environment. The
quantitative and subsequent qualitative data and analysis provided consistent results on
these variables. Firstly, self-efficacy beliefs of the pre-service EFL teachers are examined.
Considering the results from the quantitative data, pre-service EFL teachers, by and large,
believe that they are efficacious in engaging students learning, managing EFL classes, and
implementing instructional strategies. This result is noteworthy as teachers’ self-efficacy
beliefs in their instructional efficacy affect the learning environment (Bandura, 1997;
Wyatt, 2013). The interviews and subsequent analysis revealed that high and medium
efficacious teachers differ in instructional strategies, students’ engagement, and classroom
management themes. These differences are close to existing researches (Coutinho, 2008;
Egel, 2009; Henson, 2001). At this point, the most effective way of developing a strong
sense of efficacy is through mastery experiences, as proposed by Bandura. That is,
performing a task successfully strengthens the pre-service teachers’ sense of self-efficacy
(Zafarmand et al., 2014). On the basis of the interviews, high efficacious teachers seem to
enhance the students’ performance and success as prior researches have mentioned
(Henson, 2001; Tschannen-Moran et al., 1998). Moreover, pre-service EFL teachers’ selfefficacy beliefs seem too fragile. In a similar vein, Yuksel (2014) found that pre-service
teachers’ self-efficacy beliefs are not stable and change at certain stages of teacher
education. New experiences and challenges disrupt their pre-existing beliefs and force
25
them to reassess their capabilities. However, at the pre-service phase they try to be
efficacious but this can change in in-service phase.
Secondly, pre-service EFL teachers’ achievement goal orientations are also examined. The
pre-service EFL teachers adopt more than one achievement goal, and mostly mastery goals
for learning are adopted. These teachers expected to be very successful as their
motivations and achievement behaviours are high (Afsaneh & Safoura, 2015; Dweck &
Leggett, 1988; Elliot, 1999; Yeung, Tay, Hui, Lin, & Low, 2014). In addition, this is important
since teachers adopting mastery goal orientations do well in difficult situations. However,
mastery goal orientations involve the development of competence through task mastery
and the emphasis is placed on developing new skills (Lindsay, 2010). However, mastery
goal oriented teachers are open to change and self-transcendence values (Pudelko & Boon,
2014). Considering the results from the interviews, the themes namely learning aim,
motivation, ability, effort, interest in learning and improvement led to differences when
mastery and performance orientations compared. The learning aim and motivation came
up as a powerful determiners in adopting goal orientations. The differences between
mastery and performance orientations are also stated in literature (Coutinho & Neuman,
2008; Elliot, 1999; Nitsche et al., 2011; Retelsdorf et al., 2010).
The issue, however, of participation in the online learning environment showed up no
statistically significant relationship between achievement goal orientation and self-efficacy
beliefs. However, on the basis of interviews, some differences between mastery and
performance oriented pre-service EFL teacher were found. The differences between
quantitative and qualitative results can be context-based. As discussed in the literature
review, self-efficacy beliefs and goal orientations are two important variables that affect
pre-service teachers in many ways (Bandura, 1997; Beghetto, 2007). The results of the
present study indicated significant relationships between achievement goal orientation and
self-efficacy and this result is consistent with the prior researches (Coutinho & Neuman,
2008; Eryenen, 2008; Hsieh et al., 2007, Minnella, 2010). In addition, this study supported
the importance of self-efficacy (Bandura, 1997) and goal orientations (Nitsche et al., 2011)
for pre-service teachers.
CONCLUSION
Based on current self-efficacy and goal orientation research in EFL teacher education and
educational psychology, this study explores pre-service EFL teachers’ self-efficacy beliefs,
goal orientations, and participations in online learning environment, which adds to the
existing self-efficacy and goal orientation knowledge in pre-service teacher education
process. However, the research is not without limitations. First, the research is limited to
Distance English Language Teacher Education program at Anadolu University, in Turkey.
Second, the use of asynchronous Web-based management tool in the program could also
be a limiting factor. Third, the class structure is another limiting factor. If the class were
structured in a different way, the results of the research may be different. Thus in the
future, studies should be replicated with a bigger population to better assess and evaluate
the relationships between achievement goal orientations, self-efficacy beliefs, and
participation in the online learning environment. In addition, qualitative study in a long
term may give different and deep results. Mastery and performance goals need further
interpretation with male and female balanced studies. Besides, the four quadrants of goal
orientations and self-efficacy beliefs need to be studied on a long term. And more research
is needed about how these orientations affect the students of these teachers adopting
different goal orientations and self-efficacy beliefs. Age and gender issues in goal
orientations and self-efficacy beliefs need further studies. Self-efficacy and goal orientation
motives are difficult to study. So more focused qualitative studies should be conducted to
understand these issues deeply. In addition, there should be qualitative studies that
examine the online learning environments effects on pre-service teachers’ self-efficacy
beliefs and goal orientations.
26
Authors’ Note: This study has been reproduced from the Master's thesis of Hasan Uçar
"Preservice English Language Teachers’ Self-Efficacy Beliefs, Goal
Orientations and Participation in Online Learning Environment: A
Study of a Distance English Language Teacher Education Program”
under the supervision of Prof. Dr. Müjgan Yazıcı Bozkaya, at Anadolu
University, Graduate School of Social Sciences.
BIODATA and CONTACT ADDRESSES of the AUTHORS
Hasan UCAR is an English language instructor at the Department of
Foreign Languages, Bilecik Seyh Edebali University, Turkey. He received
his Bachelor’s degree from College of Open Education, English
Language Teaching Department, Anadolu University. He holds a
Master’s degree in the Department of Distance Education from Anadolu
University. Currently, he is a doctoral candidate at the Department of
Distance Education, Graduate School of Social Sciences, Anadolu
University. Hasan’s current research agenda is motivational design of
instruction in online learning environments. Additional areas of
research include instructional design/technology, teaching and learning in online
technologies, and motivation and engagement of online learners.
Hasan UCAR
Bilecik Seyh Edebali University,
Bozuyuk Vocational School, 11300
Bozuyuk/Bilecik/Turkey
Phone: +90 228 2141315
e-Mail: hasan.ucar@bilecik.edu.tr
Prof. Dr. Mujgan YAZICI BOZKAYA earned her M.S. and Ph.D. degrees in
Communication Sciences from Anadolu University. She is a full Professor
at the Open Education Faculty, Anadolu University, Turkey. In her current
position, she serves as a Coordinator and an Instructional Designer in
Open Education Faculty. Her research interests are Distance Teaching
and Learning, Interpersonal Communication, Social Presence, SelfEfficacy, New Technologies and Textbook Design in Distance Education.
She has presented in recognized national and international conferences
and published scholarly articles.
Prof. Dr. Mujgan YAZICI BOZKAYA
Anadolu University
Open Education Faculty, 26470, Eskisehir, Turkey
Phone: +90 222 3350580 / 5880
e-Mail: mbozkaya@anadolu.edu.tr
REFERENCES
Afsaneh, G. & Safoura, J. (2015). An exploration of EFL learners' perceptions of classroom
activities and their achievement goal orientations. International Journal of Research
Studies in Education. 4 (3), 33-45.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman and
Company.
Beghetto, R. A. (2007). Prospective teachers’ beliefs about students’ goal orientations:
A carry-over effect of prior schooling experiences? Social Psychology of
Education, 10, 171–191.
27
Butler, R. (2007). Teachers’ achievement goal orientations and associations with
teachers’
help seeking: Examination of a novel approach to teacher
motivation. Journal of
Educational Psychology, 99 (2), 241-252.
Chacon, T. C. (2005). Teacher’ perceived efficacy among EFL teachers in middle schools in
Venezuela. Teaching and Teacher Education, 21 (3), 257-272.
Coutinho, S. (2008). Self-efficacy, metacognition, and performance. North American
Journal of Psychology, 10 (1), 165-172. Retrieved March 11, 2012,
from,http://findarticles.com/p/articles/mi_6894/is_1_10/ai_n28518811/
Coutinho, S.A. & Neuman, G. (2008). A model of metacognition, achievement, goal
orientation, learning style, and self-efficacy. Learning Environment Research, 11,
Cresswell, J. W. (2012). Educational research: planning, conducting, and evaluating
quantitative and qualitative research. Fourth edition. Pearson: Boston, MA. 131-151.
Daal, S., Donche, V. & De Maeyer, S. (2014). The impact of personality, goal orientation
and self-efficacy on participation of high school teachers in learning activities in the
workplace. Vocations and Learning, 7, 21-40.
Dweck, C. S. & Leggett, E. L. (1988). A social-cognitive approach to motivation and
personality. Psychological Review, 95 (2), 256-273.
Egel, I. P. (2009). The prospective English language teacher’s reflections of self-efficacy.
Social and Behavioral Sciences, 1, 1561-1567.
Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals.
Educational Psychologist, 34 (3), 169-189.
Elliot, A. J. & McGregor, H. (2001). A 2 x 2 achievement goal framework. Journal of
Personality and Social Psychology, 80 (3), 501-519.
Elliot, A. J. & Murayama, K. (2008). On the measurement of achievement goals: Critique,
illustration, and application. Journal of Educational Psychology, 100(3), 613-628.
Eryenen, G. (2008). The relationships between goal orientations, academic self-efficacy,
and teacher sense of efficacy and predictive roles of these variables on pre-service
teachers’ academic achievement. Unpublished master’s thesis. İstanbul: İstanbul
University.
Henson, R. K. (2001). Teacher Self-Efficacy: Substantive Implications and Measurement
Dilemmas, Paper Submitted in Annual Educational Research Exchange Conference,
Texas A. M. University, 1-43.
Hsieh, P.; Sullivan, J.R. & Guerra, N.S. (2007). A close look at college students: Selfefficacy and goal orientation. Journal of Advanced Academics, 18 (3), 454-476.
Kucsera, J.V.; Roberts, R.; Walls, S.; Walker, J. & Svinicki, M. (2011). Goal orientation
towards teaching (GOTT) scale, Teacher and Teaching: theory and practice, 17(3),
597-610.
Lee, I. & Yuan R. (2014). Motivation change of pre-service English teachers: a Hong Kong
study. Language, Culture and Curriculum, 27(1), 89-106.
Lindsay, P.C. (2010). Assessing the relationships among goal orientation, test anxiety,
self-efficacy, metacognitıon, and academic performance. Unpublished master’s
thesis. İllionis. University of North İllionis.
McMillian, J.H. (2004). Educational research: fundamentals for the consumers . Fourth
edition. Pearson: New York.
Minnella, J. M. (2010). Achievement goals, self-efficacy, metacognitıon, and learning
strategies as predictors of asynchronous learners’ academic success. Unpublished
doctoral dissertation. Capella: University of Capella.
28
Nitsche, S., Dickhäuser, O., Fasching, M.S., & Dresel, M. (2011). Rethinking teachers’ goal
orientations: Conceptual and methodological enhancements. Learning and
Instruction,
21(4), 574-586.
Pajares, M. F. (2002). Overview of social cognitive theory and of self-efficacy.Retrieved
May 19, 2012, from, http://www.emory.edu/EDUCATION/mfp/eff.html
Pudelko, C. E., & Boon, H. J. (2014). Relations between Teachers’ Classroom Goals and
Values: A Case Study of High School Teachers in Far North Queensland, Australia.
Australian Journal of Teacher Education, 39(8). Retrieved from
http://ro.ecu.edu.au/ajte/vol39/iss8/1
Retelsdorf, J.; Butler, R.; Streblow, L. & Schiefele, U. (2010). Teachers’ goal orientations
for
teaching: Associations with instructional practices, interests in teaching,
and burnout. Learning and Instruction, 20, 30-46.
Sakar, N. (2009). Online course support in distance learning: Student evaluation of
English language teaching Bachelor of Arts program. Turkish Online Journal of
Distance Education, 10 (2).
Tang, E. L., Lee, J.C., & Chun, C. K. (2012). Development of teaching beliefs and the focus
of change in the process of pre-service ESL teacher education. Australian Journal of
Teacher Education, 37(5). http://dx.doi.org/10.14221/ajte.2012v37n5.8
Tschannen-Moran, M.; Hoy, A. W. & Hoy, W. K. (1998). Teacher efficacy: Its meaning and
measurement. Review of Educational Research, 68 (2), 202-248.
Tschannen-Moran, M. & Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive
construct. Teaching and Teacher Education, 17 (7), 783-80.
Wyatt, M. (2013). Overcoming low self-efficacy beliefs in teaching English to young
learners, International Journal of Qualitative Studies in Education, 26 (2), 238-255.
Yeung, A. S., Tay, E., Hui, C., Lin, J. H. & Low, E. (2014). Pre-service Teachers’
Motivationin Using Digital Technology. Australian Journal of Teacher Education,
39(3). http://dx.doi.org/10.14221/ajte.2014v39n3.1
Yuksel, G. H. (2014). Becoming a teacher: tracing changes in pre-service English as a
foreign language teachers' sense of efficacy. South African Journal of Education, 34
(3).
Zafarmand, A., Ghanizadeh, A. & Akbabi, O. (2014). A structural equation modeling of EFL
learners' goal orientation, metacognitive awareness, and self-efficacy. Advances in
Language and Literary Studies 5(6). 112-124.
29
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 3
INTERNET ACCESS AND USAGE IN IMPROVING
STUDENTS’ SELF-DIRECTED LEARNING
IN INDONESIA OPEN UNIVERSITY
Djoko RAHARDJO
Faculty of Social and Politiacl Sciences
Universitas Terbuka, Indonesia
Prof. Dr. SUMARDJO
Faculty of Human Ecology
Bogor Agricultural University, Indonesia
Dr. Djuara P. LUBIS
Faculty of Human Ecology
Bogor Agricultural University, Indonesia
Dr. Sri HARIJATI
Faculty of Mathematics and Sciences
Universitas Terbuka, Indonesia
ABSTRACT
Internet is well known nowadays, however higher distance education students who live
in remote rural areas still have not been able to take advantages of this medium optimally
for their learning process. For accessing the internet the students have to be available
with the minimum prerequisites: the existence of adequate devices and the sufficient
capabilities. For education purposes, the students use the internet to meet their
information and fulfill learning needs, facilitate interpersonal communications, and
provide groups of discussion, as well as to be connected with friends in social media. This
study aims to analyze the relationship between internet access and usage in improving
students' self-directed learning which is using structural equation model method. The
survey is conducted in seven districts in Surakarta Regional Office of Indonesia Open
University with a sample size of 320 respondents. The result shows that the internet
usage is still low due to limited internet facilities that affect the knowledge and
willingness of students to access the internet. The strategy in improving student internet
usage is applying social media as guidance that can be accessed through cellular phones.
Keywords: Internet access, internet usage, distance education, self-directed learning
INTRODUCTION
Internet is growth in popularity as learning media in higher distance education,
unfortunately students in some rural areas are still not utilizing the internet to fulfill their
need. Web-based distance education application has become increasingly playing an
important role in the development of students learning, however it need some
requirements to access the internet. To access it, they have to provide themselves, not
only with the availability of devices, but also with the access capability.
The use of internet in higher distance education particularly emphasizes on meeting the
needs of information, interactive communications between educators and learners in the
learning process, forums for students to discuss both teaching materials and other
30
academic administrations, as well as social communications which more open among
students who are used as a venue for private disclosure or the interests of their learning
processes. This is in line with Park in Dogruer et al. (2011) which stated that the function
of the internet in education, among others, as (1) storing the information, (2) means of
communication without bounds, (3) an interactive online learning. While Gaytan
described in Stanciu and Inca (2014) confirmed that there are several levels in the use of
the internet, namely, (1) gathering information, (2) sharing information with friends who
have the same interest, (3) working on the internet as part which has been planned, (4)
studying according to the curriculum that has been prepared by the tutor to be done
through the help of it, and (5) designing activities which apply learning independently.
Some researches have been carried out in order to identify and to solve the problem of
access and use of internet. For example, Rye and Zubaidah (2008) focused on the
problem of accessing the internet at graduate students of Pangkal Pinang Regional Office
of Indonesia Open University (Universitas Terbuka/UT) in Bangka Belitung Islands which
concluded that student adversity not only on the unavailability of the means but also the
problem of unfamiliarity in the internet use. This would be a challenge for students since
the absence of other appropriate means to support their learning process.
Daulay (2008), which examined the interaction of students in the Online Communication
Forum at the UT’s website, identified that the highest rating of communication was
personal interactions, and the second rating was problems with tutorials and other
administrative matters. The conclusion of the study stated that the biggest obstacle of
the students was the lack of communication. Omotayo (2006) conducted a survey of
internet use among undergraduates. The results showed that internet use is quite high,
especially in internet café. Internet usage does not affect the use of the library. The
common problem faced by students is the weak signal from the server and cost issues.
Chen and Fu (2009) studied the association between internet use and academic
achievement of the high school students in northern Taiwan. The findings confirmed that
the search information through online help improve test scores. While the internet which
was used in socializing, playing and accessing through internet cafes lowered the
performance of their exams. Peou et.al. (2011) observed the relationship of the use and
attitudes towards the internet, and the academic utilizing in Cambodia. Use of the
internet for academic purposes was still rare among the students. It concluded that main
reason was technology adoption costs. All the examples above, however, they were
inadequately discussing on the students’ attitudes in the access and use of the internet,
i.e. internet knowledge, willingness, and the ability to operate the devices.
This research paper presents a survey on students’ internet access behavior (IAB) and
internet usage (IU) especially their university’s website. On the basis of this
investigation, it then describes how to improve students self-directed learning (SDL)
index. The students who have the ability of SDL becomes importance concept in distance
education (Moore and Kearsily, 2012). In online learning, SDL constitutes of the effect of
communication process. Index of SDL according to Williamson (2007) can be described in
five dimensions of learning, i.e. awareness, learning strategies, learning activities,
evaluation, and interpersonal skill. The success of the students in learning processes can
be identified by these dimensions.
Departing from the above description, this research purposes can be formulated as
follows:
Ø To analyze the relationship between IAB, IU, and SDL?
Ø To formulate a strategy that can be used to improve student SDL index?
METHOD
Population and Sample
The population of the study included regular undergraduate students who registered the
semester exams in the second academic year of 2013 in Surakarta Regional Office of
31
Universitas Terbuka, Indonesia. The random sample was obtained in research sites. The
research sites were seven regencies of Surakarta namely Boyolali, Klaten, Karanganyar,
Sragen, Sukoharjo, Surakarta, and Wonogiri. According to Kline (2011) that “typical”
sample size in studies where structural equation model (SEM) is used is about 200 cases
and the same as Hoyle (1995) that stated as “practically reasonable sample size”. While
Bentler and Chou (1987) suggested the ratio sample size to number of free parameters
may be able to go as low as 5:1. Three hundred twenty students (320 samples) responded
to a questionnaire assessing their behavior related to the internet in the process of
learning.
Instrument
The survey on Internet Access and Usage in improving Self-Directed Learning was based
conceptually on the eleven factors. Specific questions were developed to measure selfdirected learning rate which was adopted from Williamson (2007). They were awareness,
strategy of learning, activity of learning, evaluation of learning, and interpersonal skill.
Internet access consisted of three main factors, i.e. cognitive, affective, and conative aspect
which each of them have three dimensions of questions: using, searching and communicating.
The Internet Usage contained three factors, i.e. learning, fulfilling information need, and
communicating. Each of them consists of 5 questions. While the environment factor was
composed of three factor i.e. availability of internet, social support, and environmental
barriers. Face validity of the questions was established by three expert reviewers.
Procedure
After obtaining approval from the university, survey were conducted. The data collected when
the students came to the classroom tutorial (face to face tutorial) places. Before data analysis
carried out, the research instrument was examined to get its validity and reliability. These
result of the test indicated that the instrument used were sufficiently valid and reliable; with
each indicator had a count r > r-table (0.1946) and with Cronbach alpha values = 0.919.
Data Analysis
In order to get the map of relationships among the variables, SEM method was applied using
AMOS 22. Because the result of multivariate test on the variable was non-normally distributed,
bootstrapping method was applied, and resample was set to 500. The final result of model
showed that Bollen-Stine bootstrap p = 0 .112, it meant that the model had a good fit.
RESULTS AND DISCUSSION
Account and Access Equipment Ownership
From the analyzing data, it found generally that students owned equipment sufficient enough
for them to access the internet, and it was only 6.9% of the students who do not have access
to this equipment. However, it did not reduce the spirit of challenge them to access the
internet in fact that half of the students who do not have the equipment have internet
accounts (Table 1). To access the internet, they utilized internet café or internet available in
the workplace. One fifth (21.3%) of the number of students did not have an account, although
most have internet access equipments. This means that some students were not accustomed
to communicating via the internet.
Table: 1
Number of students according to ownership of internet accounts and access equipments
Access Equipment
Ownership
No equipment
Cellular phone
PC+Tablet+Laptop
All kind of devices
Total
(%)
No internet
account
10
39
5
14
68
(21.3)
Email
8
66
12
41
127
(39.7)
Internet account ownership
Email
Email+Facebook
+Facebook
+Twitter
3
1
38
12
18
2
36
21
95
36
(29.7)
(11.3)
Total
22
155
37
106
320
(100)
(%)
(6.9)
(48.4)
(11.6)
(33.1)
(100.0)
32
Variable Index: Environmental Factors, Internet Access, and Internet Usage
The capability of students to access the internet was quite good, the students’ knowledge
and willingness to access these media was high, the ability of the student to access the
internet, however, was still in a medium rank (Table 2). Environmental factors were
generally considered to be high with low resistance/barriers. It discovered that students'
communication with other people using the internet rather low, while the level of the
students to exploit the information in the university website was in a medium level. It can
be concluded that environmental factors were sufficient to support height student access
level, but it could not maintain the level of internet usage.
Table: 2
Variables and Score Values: Environment factors, Internet Access Behavior, Internet
Usage
Variables
Score Value(%)
Environmental factors
Availability of internet
57.70
Social supports
68.13
Environmental Barriers
34.65
Internet Access Behavior
Cognitive/ knowledge
75.28
Affective/ attitude
83.16
Conative/ ability
56.49
Internet use
Information need
36.09
Learning activity
27.60
Communication
28.56
Level of availability of internet facilities are generally inadequate. These findings are
similar to the study reported by Rye and Zubaidah (2008) in the Bangka Belitung Islands.
It was thought to relate to the availability of telephone networks in the regions where
they lived. Family support was an important element for the advancement of student
education. With the support of family, students could be better motivated to learn.
Support was generally due to economic problems, given that the costs used to access the
internet is not cheap (Omotayo, 2006).
Confirmatory Factor Analysis of Access and Use of Internet, and Environment Factors
Using bootstrap method in AMOS version 22 and setting to be 500 resample, this analysis
generated a model of confirmatory analysis as shown in Figure 1. It found that the model
had a negative variance (eF2= -69,9), so variance value had to be changed into smaller
(0.005). It found that there were 3 indicators which had loading factors < 0.5. These
indicators had to be dropped for the next analysis.
33
Figure: 1
Confirmatory factor Analysis of Full Model
In order to get a model with valid indicators, some indicators had to be dropped. The final
result of confirmatory factor analysis can be seen in Figure 2.
Figure: 2
The Final Result of Confirmatory factor Analysis of Access and Use of Internet
34
Model of Access and Use of Internet, and Environment Factors
The final result of model showed that Bollen-Stine bootstrap p = 0.056, it meant that the
model had a good fit. As represented in Table 3, the model enjoys good fitness based on
the above criteria. RMSEA equals 0.038 which is smaller than 0.8 and the indices GFI,
AGFI, and CFI are all greater or near 0.90; therefore the model shows a good fitness and
is confirmed.
Table: 3
Goodness of Fit of Access and Usage of Internet Model
CMIN
DF
P
350.73
23
9
0.00
CMIN/DF
RMR
GFI
AGFI
CFI
1.467
33.882
0.92
2
0.89
3
0.96
9
RMSEA
0.038
Figure 3 was the final model of Access and Usage of internet. This model illustrates that
to improve the rate of the students’ internet usage, it needs to maintain environmental
factors, however, these factors such as: home internet facilities, family support,
environment barriers are personal condition that can not be reached by the institution.
This model also reveals that the behavior of access that can be used to improve the use of
the internet is the ability to search the information through the internet. Searching in the
internet capability is an important aspect to be improved in order to increase their
internet use.
Students had enough knowledge to access the internet and they agreed to use internet,
but they had inadequately abilities to access it. The students were capable of searching
information on the internet. It was the basis for students to develop themselves in the
use of the internet. This condition was a pretty good starting point for further
development.
Figure: 3
Final Model of Access and Use of Internet
35
Students in the use of the internet for the benefit of the learning process was still
deficient. These findings confirmed what has been studied by Peou et.al. (2011) in
Cambodia. Online exercise was still underutilized by students, and it was suspected that
students preferred to use offline exercises provided in their textbook for lower cost. That
the use of online tutorial was at a low level showed that the students were not yet
accustomed to taking the advantage of application. It was assumed that student still
preferred traditional ways of learning, classroom tutoring.
Students still rarely used email to communicate better with friends, faculty, and academic
staff UT. This finding was similar to Daulay (2008) which stated that students were less
communicate.
The Relationship among the Internet Access and Use, Self-Directed Learning, and GPA
In order to identify the relationship among the internet access and use, self-directed
learning, and GPA, the data were correlated using SPSS. It found that students in
accessing the internet was positively correlated with the use of the internet and self
directed learning, but not positively correlated with GPA. Internet usage correlated with
self directed learning but not correlated with GPA, while self directed learning was
positively correlated with GPA (Table 4). Therefore any change in internet access
behavior and internet usage will affect students’ self directed learning. The effect on
internet access behavior to GPA was indirectly. It is similar to Chen and Fu (2009) who
found that the search through the internet helps improve GPA.
Table: 4
Correlation matrix between Internet access, Internet usage,
Self-directed learning, and GPA (N=320)
Spearman’s
Internet
Internet Self-Directed
Variables
rho
Access
usage
learning
Internet access
Corr. Coef.
1
0.469**
0.307**
Sig. (2.
0.000
0.000
tailed)
Internet usage
Corr. Coef.
1
0.178**
Sig. (2.
.001
tailed)
Self-directed learning Corr. Coef.
1
Sig. (2.
tailed)
GPA
Corr. Coef.
Sig. (2tailed)
GPA
0.040
0.447
0.010
0.870
0.135*
0.015
1
.
Strategy to Improve Self Directed Learning
Importance and Performance Analysis
According to Pike (2004) the importance-performance analysis techniques could be used
to assist in decision-making according to priority. Using scatter plot graphic in SPSS, this
analysis results a matrix formed by the two axes, namely, the X axis was the score
values, while the Y axis was the loading factors. The matrix formed four quadrants, i.e.
quadrant-1 and quadrant-2 had a high priority, quadrant-3 and quadrant-4 had a low
priority.
In general, internet access behavior was a group of attributes that need to be maintained
and receive the highest priority in improvement, while internet usage especially in the
aspect of learning was the next priority needs to be increased (Figure 4).
36
Specification:
itn1 =home internet facility
itn3 = café availability
itn4 = network availability
supp1 = family support
supp2 = government support
barr2 = distance to cafe
barr4 = barrier access time
cog2 = internet knowledge
cog3 = searching knowledge
cog4 = communication knowledge
aff2 = internet access willingness
aff3 = searching willingness
aff4 = communication willingness
con2 = internet ability
con3 = searching ability
con4 = communication ability
info1 = education systems
info2 = enrollment information
info3 = exam / tutorials schedule
info4 = course syllabus
info5 = online bookstore
learn1 = online course guiding
learn2 = enrichment of materials
learn3 = online exercise
learn4 = digital library
learn5 = Online tutorial
com1 = email to colleague
com2 = email to lecturers
com3 = email to staff
com4 = discussion forum
com5 = participate in facebook
Figure: 4
Matrix of Importance Performance Analysis on Indicators
Attributes in first quadrant were generally dominated by the half of the group variable of
internet usage. This attributes had a high importance but low in performance. This
condition illustrated that these attributes should be encouraged to be improved.
Attributes in second quadrant were a group variable of internet access on all aspects,
cognitive, affective, and conative. The group had both high importance and performance.
This condition described that these attributes should get the first priority for further
development. While attributes in quadrant-3 and quadrant-4 were groups of
environmental factors and the internet usage. This condition had both low in importance
and performance. This exemplified that these attributes were in a low priority.
Strategy to Improve Self- Directed Learning
By improving access and use of the internet was expected to result in increased students’
self-directed learning, which in turn will affect the student achievement index or GPA.
Based on the analysis that has been outlined, it can be formulated a strategy in order to
improve student self-directed learning.
Increasing Internet Access
The access devices were tools that must be absolutely available so that students could
access the internet. As alternatives, the students could rent these devices at the internet
cafes or other ways that could be managed by the students. While UT as the source of
information which serves disseminating information through the media should make the
absorption rate of information better. To increase it, UT had to pay attention to the
facilities covered by the students, cellular phones were generally available. Therefore, the
application in accordance with their internet devices should be considered to be
developed more comprehensively.
37
The ability of searching plays an influential aspect for the improvement of self-directed
learning. Searching information capability needs to get serious attention from UT
institutions. This capability will allow students to obtain information quickly, as well as
select information related to their needs. Regional Offices, who serves as the
representative of the university, already provided training on how to access and use of
the internet to the students during the first year they enroll UT, however, these
capabilities should be developed in more practical.
Improving Internet Usage
To improve students in using the internet, UT need to do things as follows:
To accomplish the information need is the basic requirement that the student learning
process can take place. UT as an institution has prepared a variety of information to meet
the needs of students. To improve the internet usage rate, UT as the information source
should apply more intensive socialization through meetings in Regional Offices or in
student study groups to learn about the features that are available in the Website UT.
This way will result increasing of student knowledge in the available information more
efficiently.
The internet usage for learning dimension is an important aspect in distance education.
UT institutions fully understand that the internet has characteristics best suited to
distance education system. The low level of internet usage in the dimension of learning is
the consequence of failure devices used by the students that cannot retrieve the
information available. Therefore, it needs the development of internet program which is
more accessible by cheaper equipment and affordable for students.
Internet usage for the communication needs is also an aspect that is no less important.
The low level of the communication resulted in low student motivation to learn. The low
of internet use in communication aspect can be fixed by the use of social media
(Facebook or Twitter) as an alternative medium. Social media can solve the problem of
technological limitations. Too large access charges lead to weaken the response rate of
the server computer. Similarly, the addition of a new feature to the system that’s already
established would increase to the load of the server computer.
CONCLUSIONS
Based on the results and discussion that has been described can be summarized as
follows:
Ø
Ø
Ø
Ø
Low levels of access equipment availability is a major factor for the lack of
internet usage among UT students in the remote area. Access equipment owned
by students, cellular phones, do not reach adequately the information provided
by UT.
The students’ searching capabilities including the aspects of knowledge,
willingness, as well as ability, have a positive association with the students in
using the internet. The lower capability of students in searching information
becomes the one of
factors that can determine the weakness of study
completion.
The level of internet usage in searching information and in learning dimensions
generally remains at a low level. Since the internet usage has positively
correlation with self-directed learning, the very low learning dimension in
internet usage will affects the students’ self directed learning..
The strategy which is expected to enhance students’ SDL is aimed at
strengthening the ability of searching information, increased the use of the
internet on aspects of learning by using less expensive access equipment, and
the development of the use of social media as a second media to cope with
technological problems.
38
RECOMMENDATIONS
Based on the results and conclusions of research can be put forward the following
suggestions:
Ø
Ø
Ø
In order to solved the problem of the low rate of internet usage with the
condition of limited access devices, UT should develop an extension application
that aims at expanding internet access and it should be strengthened to the
devices which have been already owned by most of the students. Most devices in
Indonesia from the cheapest to the most expensive ones (cellular phones or
tablets) use “android” application, for that reason UT should take notice to this
application.
In order to increase self-directed learning it is necessary to strengthen the
capability of students in searching the internet since SDL has positively
correlation with internet searching capability. For that reason, Surakarta
Regional Office and study groups should conduct comprehensive training on
“how to search the information through the internet”, so that students can
realistically use the internet for searching information.
The use of social media is directed to be applied as second media for the purpose
of their learning process. The students as adult people generally fond of using the
social media e.g. facebook, twitter, or others to make contacts with their
colleagues by means of cellular phones. By this, they can update their friends in
their environments. To insert learning purposes to this “easy touch” media
hopefully can overcome the limitations and cost of existing media technologies.
Therefore it is necessary to develop the management information so that
students can be more intense in communicating both with the tutor and other
interested parties as well as obtaining information immediately.
BIODATA and CONTACT ADDRESSES of the AUTHORS
Djoko RAHARDJO was born in Surakarta, Indonesia on June 25, 1958. He
graduated from Magister of Librarian and Information Study, Faculty of
Humanities, University of Indonesia in 2004. When he wrote this article he
was a doctoral candidate of Development Communication Study Program at
Bogor Agricultural University. He is a lecturer in Communication Science
Department, Universitas Terbuka Indonesia. His main interests are
communication media and distance education.
Djoko Rahardjo, M. Hum
Universitas Terbuka, Indonesia
Faculty of Social and Political Science
Jalan Cabe Raya Pamulang, Tangerang Selatan, Indonesia
Email: rahardjo@ut.ac.id , dj.rahardjo@gmai.com
Prof. Dr. SUMARDJO was born in Sukoharjo Indonesia on February 25,
1958. He graduated from the Bogor Agricultural University, Department of
Communication / Extension Development in 1999. He was professor of
extension development at the Faculty of Human Ecology, Bogor
Agricultural University. He graduated master of science in rural sociology
Bogor Agricultural University in 1988. He serves as the head of the
Research Center for Conflict Resolution and Social Empowerment. The main interest in
the research is education development, cyber extension, community development, and
conflict resolution.
Prof. Dr. Sumardjo
Bogor Agricultural University, Indonesia
Jalan Dramaga, Bogor Indonesia
Email: sumardjo252@gmail.com
39
Djuara P. LUBIS was born in 1960. He received his PhD in Development
Communication from University of the Philippines, College of Development
Communication in 2000. Since 1985 he has been working as lecturer in
Bogor Agricultural University, Indonesia, and serves as head of
Development Communication Study Program.
Dr. Djuara P. Lubis
Bogor Agricultural University, Indonesia
Jalan Dramaga, Bogor Indonesia
Email: djuaralubis@gmail.com
Dr. Ir. Sri HARIJATI, MA. was born in Madiun, East Java, Indonesia in 1962.
She completed her doctoral program in the field of "extention of
development" at Bogor Agricultural University in 2006. She works at
Universitas Terbuka since 1988 on The Study Program of Agribusiness. She
has been working as an online Tutor for several agricultural extension
cources. Universitas Terbuka is an Indonesia university that implements
open and distance education system. She is interested in areas of research
in online learning.
Dr. Ir. Sri Harijati, MA.
Faculty of Mathematics and Natural Sciences, Universitas Terbuka, Indonesia
Jalan Cabe Raya, Pondok Cabe, Pamulang
Tangerang Selatan, Banten, Indonesia.
Fax: (62)021 7434691
Phone: (62)021 7490941
E-mail: harijati@ut.ac.id
REFERENCES
Bentler, P.M. and C.-P. Chou. (1987). Practical issues in structural modeling. Sociological
Methods & Research 16(1): 78-117
Bucy, EP., and Newhagen, JE. (Ed) (2004). Media access: social and psychological
dimensions of new technology use. London (GB): Lawrence Erlbaum Associates, Inc.
Chen, SY. and Fu, YC. (2009) Internet use and academic achievement: gender differences
in early adolescence. Adolescence, 44 (176), 797-812
Daulay, P. (2008). Analysis of the contents of an interactive discussion topics Open
University student in the feature "Online UT Communications Forum". Scriptura 2,
135-149
Dogruer N, Eyyam R, and Menevis I. (2011). The use of the internet for educational
purposes. Prosedia- Social and Behavioral Sciences 28, 606-611
Hoyle, RH. Editor. (1995). Structural Equation Modeling: Concepts, Issues, and
applications. London(GB): Sage Publications
Kline, Rex B. (2011). Principles and practice of structural equation modeling 3rd ed. New
York(US): The Guilford Press
Moore, MG, Kearsley, G. (2012). Distance Education: A system view of online learning.
Edition-3. Belmont(US): Wadsworth
Omotayo, BO. (2006). A survey of Internet access and usage among undergraduates in an
African University. The International Information & Library Review, 38, 215-224
40
Peou, C. and Lwin, M. (2011). Integrating the internet into Cambodian higher education:
exploring students' internet uses, attitudes and academic utilization. International
Journal of Emerging Technologies and Society 9 (2), 95-115
Pike, S. (2004). The use of repertory grid analysis and importance-performance analysis
to identify determinant attributes of universities. Journal of marketing for higher
education, 14 (2), 1-14
Rye SA, Zubaidah I. 2008. Distance education and the complexity of accessing the
internet. Open Learning. 23(2), 95–102. DOI: 10,1080/02680510802051897.
Stanciu, V. and Inca, A. (2014). A critical look on the student's internet use- empirical
study. Accounting and Management Information systems, 13 (4), 739-754
Williamson SN. (2007). Development of a self rating scale of self-directed learning. Nurse
Researcher. 14(2), 66-83.
41
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 4
QR CODES IN EDUCATION AND COMMUNICATION
Dr. Gurhan DURAK
Necatibey Faculty of Education
Balikesir University, Balikesir, TURKEY
E. Emre OZKESKIN
Open Education Faculty
Anadolu University, Eskisehir, TURKEY
Dr. Murat ATAIZI
Communication Sciences Faculty
Anadolu University, Eskisehir, TURKEY
ABSTRACT
Technological advances brought applications of innovations to education. Conventional
education increasingly flourishes with new technologies accompanied by more learner
active environments. In this continuum, there are learners preferring self-learning.
Traditional learning materials yield attractive, motivating and technologically enhanced
learning materials. The QR (Quick Response) Codes are one of these innovations. The
aim of this study is to redesign a lesson unit supported with QR Codes and to get the
learner views about the redesigned material. For this purpose, the redesigned lesson unit
was delivered to 15 learners in Balıkesir University in the academic year of 2013-2014.
The learners were asked to study the material. The learners who had smart phones and
Internet access were chosen for the study. To provide sectional diversity, three groups
were created. The group learners were from Faculty of Education, Faculty of Science and
Literature and Faculty of Engineering. After the semi-structured interviews were held,
the learners were asked about their pre-knowledge about QR Codes, QR Codes’
contribution to learning, difficulties with using QR Codes about and design issues.
Descriptive data analysis was used in the study. The findings were interpreted on the
basis of Theory of Diffusion of Innovations and Theory of Uses and Gratifications. After
the research, the themes found were awareness of QR Code, types of QR Codes and
applications, contributions to learning, and proliferation of QR Codes. Generally, the
learners participating in the study reported that they were aware of QR Codes; that they
could use the QR Codes; and that using QR Codes in education was useful. They also
expressed that such features as visual elements, attractiveness and direct routing had
positive impact on learning. In addition, they generally mentioned that they did not have
any difficulty using QR Codes; that they liked the design; and that the content should
include both superficial and in-depth information.
Keywords: Mobile learning, QR Code, Communication, Distance education
INTRODUCTION
It is possible to say that wider use of the Internet and the decrease in the prices of
mobile devices has increased the use of these devices. People can work without any
restriction of place and make use of these devices for different purposes. According to AlKhalifa (2011), one of the most important aspects of mobile phones is their ability to
access the Internet anywhere, which makes it possible to reach the information at any
time they need. Mobile, namely ubiquitous learning is reshaping the learning
environment. From SMSs to Smart Phones, it has changed the way of interaction
42
between learners and the learning materials. Learners can reach learning objects (video,
text, sound etc.) faster than ever before. Since correspondence learning, hard copy
materials (course books) are the base materials of learning for open and distance
learning courses at Anadolu University (“Acikogretim Sistemi - Tarihcesi,” 2012).
According to ABI research (2013), there were 1.4 billion smart phones in the World. A
raport about the use of smart phones, which was published in 2014, shows that the
number had reached to 1.75 billion (eMarketer, 2014). Another study revealed that 89%
of the smart phones are used all day (Smartphone users around the World, 2012).
Figure 1 presents the reasons for use of smart phones in the second half of 2011 around
the World. According to the data presented in the Table, smart phone owners use their
phones for gaming, which is followed by social networks, music and news. Using smart
phones for educational purposes is about 11%.
UsesofSmartPhones
communication
entertainment
music
11
20
26
34
39
games
44
56
64
Figure 1:
Uses of Smart Phones
Figure 2 presents the monthly data use for 2013 and 2014. According to the data, there
was an increase of 69% in a year. Figure 3 shows the total Internet traffic data in 2000
and mobile Internet traffic data in 2014. According to Figure 3, mobile traffic data in
2014 were thirty times more than the total Internet traffic data in 2000.
43
20.000.000
18.000.000
16.000.000
14.000.000
Web/Data/VoIP
12.000.000
Video
10.000.000
8.000.000
AudioStreaming
6.000.000
FileSharing
4.000.000
2.000.000
0
2015
20152
2016
2017
2018
2019
Figure: 1
2015 – 2019 Mobile data traffic by application TB by month (Cisco, 2015)
When the graph in Figure 4 is examined, it is seen that two-third of the mobile data
traffic will be of videos.
THEORETICAL BACKGROUND
This study is grounded upon the Theory of Diffusion of Innovations and Theory of Uses
and Gratifications. The data in this study were interpreted on the basis of these theories.
Theory of Diffusion of Innovations
The Theory of Diffusion of Innovations put forward by Rogers is based on four factors:
innovation communication channel, time and social system. According to Rogers (2003),
this diffusion is a process of communication via certain channels between the members
of the social system regarding the “new”.
In his theory, Rogers defined ‘innovation’ as an idea, an application or an object
considered to be new by an individual or organization. An innovation does not have to be
a concept or a design that is definitely unknown. It is enough that the individual or
organization has not used it before (Berger, 2005). There are five phases in Roger’s
model: Knowledge, persuasion, decision, implementation and confirmation.
Ø Knowledge: The individual gets informed about the innovation and its use.
Ø Persuasion: The individual evaluates the positive and negative aspects of the
innovation and shapes his/her attitudes accordingly.
Ø Decision: In this phase, the individual decides to accept or reject the innovation.
Ø Implementation: This phase exists if the decision phase is completed positively.
Ø Confirmation: The Individual affirms and strengthens the adoption decision (Orr,
2003).
44
REJECT
Knowledge
Persuasion
Decision
Implementation
Confirmation
ACCEPT
Figure: 2
The innovation-decision process (Rogers, 1995)
Theory of Uses and Gratifications
The theory of Uses and Gratifications was first announced by Elihu Kats. According to
Katz, research on communication always focused on the question of ‘What does media do
for people?’ but the real question should actually be ‘What people do with media?’
(McQuail & Windahl, 2010, p.167).
Thereare
socialand
needs,which
psychological
generate
originsof
resultingin
need
expectations of
themassmedia
differential
orother
patternsof
sources,which
mediaexposure
leadto
gratificatioon
andother
(often
unintended
consequences
Figure: 3
The Uses and Gratifications approach (McQuail & Windahl, 2010, p.168)
In many studies based on the theory of Uses and Gratifications, gratifications obtained
were perceived as motivations necessary for certain internet activities. Studies in related
literature demonstrated that gratifications mostly included searching for information,
entertainment, surveillance, communication between individuals, identity, acquiring
status and gains (Charney and Greenberg, 2001; LaRose, Mastro and Eastin, 2001;
Papacharissi and Rubin, 2000).
QR CODES
QR Codes consist of black modules arranged in a square pattern on a white background.
They are designed to decode the data quickly. It is quite easy to create and use these
codes (Pons, 2011).
Using QR Codes for education is another way of using the Internet. Quick Response (QR)
codes are versatile. A piece of long multilingual text, a linked URL, an automated SMS
45
message, a business card or almost any information can be embedded into the twodimensional barcode. With moderate equipped mobile devices, QR Codes can connect
users to the information quickly and easily (LAW, SO, & 蘇永華, 2010).
Since 2011, using QR codes has been used in different forms. According to comScore
MobiLens (2011), 1 out of 5 smart-phone owners in U.S. scanned QR codes. Canada and
Germany both saw near 16% of smart-phone owners scanning QR codes in a month, while
the UK and Spain (home to the most penetrated smart-phone markets) saw just 12% of their
participants scanning QR codes. (Source: comScore MobiLens, 3 mon. avg. ending Dec-2011)
QR codes are used in a wide range of areas like media, street banners, all places leading to
web sites, music, video and social networks (Arslan, 2011). According to Walsh and Andrew
(2011), some of the beneficial uses of QR Codes include bridging printed materials to
electronic materials, reaching voiced materials, opening embedded videos, providing libraries
with external resources and reaching appropriate help.
QR Codes in Education
It could be stated that studies on use of QR Codes in education were generally conducted in
the field of mobile learning. Review of the related literature revealed that mobile devices
were used while using QR Codes. According to So (2008), the most important aspect of
mobile learning is the triology of ‘location independence’, ‘time independence’ and
‘meaningful content’. These three basic features are among characteristics of mobile learning,
and they differ from e-learning and web-based learning due to these features (Law & So,
2010).
The rising speed of mobile technology is increasing and penetrating all aspects of human life.
Therefore, this technology plays a vital role in learning different dimensions of information.
Today, a clear shift from teacher-centered learning to student-centered learning causes
students to find technology more effective and interesting than ever before (Miangah, 2012).
In an experimental study conducted on the use of QR codes in education (Rikala &
Kankaanranta, 2012), the views of 76 learners and of their teachers from four different-level
schools were determined. The results of the study revealed that the learners were eager and
motivated to use the QR codes. As for the their teachers, they approached cautiously to the
use of QR codes in education and mentioned the likelihood of various difficulties to be
experienced in relation to the preparation of lesson units and time. In addition, in the study, it
was found that QR codes could motivate learners and draw their attention to class since these
codes support learning and provide opportunities both for independent learning and for
cooperative learning.
In another study carried out by McCabe and Tedesco (2012), QR codes were used via smart
phones for direct connection with the subjects within the scope of the course of mathematics.
In the study conducted with 14 learners, all the learners reported positive views about the QR
codes prepared for the course of mathematics. In such a course process, 83% of the learners
stated that they prepared for the following lesson better and did their homework more
productively, and 67% of them stated that there was an increase in their course marks and
that they found it easy to use QR codes. In addition, as revealed by the most important
finding obtained in the study, 83% of the learner experienced less stress when they studied
for the lessons with the help of QR codes. According to the learners, the reason was that it
was instantly possible to access the necessary information via QR codes without having to
ask their peers or teachers.
Hernández-Julián & Peters (2012), in their study conducted to compare doing homework
online with doing homework on paper, found that an electronic environment could make it
easier to access an instructional material and that it did not significantly influence learning.
Al-Khalifa (2011) developed a Mobile Snapshot Response system with QR Codes. The system
aimed at helping improve the communication between teachers and their students. Rivers
(2010) designed a task-based QR Code system for English language teaching. In the study,
the researcher explained how the system was developed, applied and tested. It was found in
46
the study that the learners enjoyed and benefited from the system while using it to carry out
the course activities. Liu, Tan and Chu (2007), in their study, developed a learning system to
improve learners’ English language levels with the help of QR Codes. The study revealed that
the QR Code system helped learn English.
Chen, Teng, Lee and Kinshuk (2011) conducted a study to allow access to digital materials
through QR Codes in paper-based reading tasks. The results suggested that direct access to
digital resources using QR codes does not significantly influence students’ reading
comprehension.
In their study, Ozcelik and Acarturk (2011) aimed at reducing the spatial space between
printed and online resources using QR Codes. In this empirical study carried out with 44
university students, the students were divided into two groups (paper + mobile phone and
paper + computer). In the study, it was concluded that thanks to QR codes found in course
books, mobile devices contribute to learning since it is easily possible to access information
online.
Baker (2010) used QR Codes in his study titled “Making Physical Objects Clickable: Using
Mobile Tags to Enhance Library Displays”. The researcher reported that libraries should
contain both physical and electronic media and that the mobile labeling technology between
these two environments will provide a solid basis for new generation libraries.
Hwang, Wu, Tseng and Huang (2011) developed a learning platform using QR codes via cell
phones which are low-priced and which have a camera and internet connection. This
empirical study showed that the learners using the platform demonstrated meaningful
improvements in terms of learning efficiency and learning achievement.
Designing a Lesson Unit Supported with QR Codes
In this study, QR Codes were added to a lesson unit of Computer-101 course book for
Anadolu University Open Education Faculty. As can be seen on figure 7, we created a
twitter account, a Facebook support page and QR links to the digital form of the course
book. As Bolter & Grusin (2000) mentioned, hypermedia aims at addressing multiple and
different senses of human. Use of more senses for hearing, seeing, smelling and
touching, learning increases learning. Instead of the medium, the instructional methods
cause the learning (Clark & Mayer, 2008), but using different media provides ability to
use different strategies.
Figure: 4
Cover page showing Twitter and Facebook Support pages
47
In Figure 8, there are two different QR Codes from the lesson unit? The upper one leads
to a video about the subject, and the other leads to a Wikipedia page.
Figure 9: Google images and Flash videos
Figure: 8
Using QR Codes in the lesson unit
In Figure 9, the QR Codes link to Google images and Flash videos.
Figure: 9
Google images and Flash videos
METHODOLOGY
The present study was designed as a case study. According to Creswell (2009), case
study is a qualitative approach in which the investigator explores a bounded system (a
case) or multiple bounded systems (cases) over time through detailed, in-depth data
collection involving multiple sources of information (e.g., observations, interviews,
audiovisual material, documents and reports) and reports a case description and casebased themes.
In this study, the researchers redesigned a lesson unit of the course book by adding QR
codes. The QR codes linked the learner to web sites, applications and social networks
related to the subject to be taught.
Participants
The participants in the study were 15 students from Faculty of Education, Faculty of
Science and Literature and Engineering Faculty of Balıkesir University in the academic
year of 2013-2014. In the study, the purposeful sampling method was used. In this
48
method, the researcher decides whom to include in the study and chooses the
participants most appropriate to the purpose of the research (Balcı, 2004).
The students who were chosen for the study met the criteria of having a “smart” phone
and having access to the Internet using their phones. These students were divided in
three groups:
Ø Group 1: Second-grade students from the Department of Computer and
Instructional Technologies in Necatibey Education Faculty
Ø Group 2: Third-grade students from the Department of Mechanical Engineering
in of Engineering Faculty
Ø Group 3: Students from the departments of Physics, Chemistry and Biology in
Faculty of Science and Literature
The purpose of choosing these groups was to analyze different perspectives of students
from different departments.
Data Collection
In this study, the researchers aimed at determining the learners’ views about the lesson
unit supported with QR Codes. For this purpose, semi-structured interview questions
were prepared. According to Ozguven (2004), semi-structured interviews provide an
opportunity to make some changes during the interview for unpredictable situations.
The process of preparing the interview questions began with draft questions and continued
by getting expert opinion. After expert opinions, the necessary changes were made, and the
interview questions were applied to three students as a pilot study. The purpose of the pilot
study was to understand if the questions were clear, open-ended and consistent with the aim
of the study.
In line with the purpose of the study, there are six questions:
Ø What was your level of knowledge about the subject before the study? After this
lesson unit, what do you think your level of current knowledge about the subject is?
Ø Did the QR Code supported lesson unit have positive influence on your learning?
How effective it was on your learning?
Ø What should the content of QR Codes be? (Text, Links to videos, texts, audios or
images)
Ø What problems did you experience while using the QR Codes?
Ø What do you think about the design of QR Codes on pages? What are your
suggestions?
Ø Should QR Codes be used for details or for enhancement? (Enhancement; with same
difficulty but with different perspectives, like a simple video, detailing; further
information for whom it may concern)
Data Collection Process
Interviews were held in one of the researcher room in Necatibey Education Faculty main
campus. Total of 15 students participated the study. In the first phase, the participants
were informed about aim of the research. During the meeting, detailed information was
given to the participants about the purpose of the study and about the research method.
The participants were also informed about such topics as installation of the necessary
software, link to the support page and contact information. The students were asked for
their consent and informed that the interview would be recorded and the recordings
won’t be used for any other purpose.
Following the first meeting, the course material (the computer course lesson unit
supported with QR Code) was given to the participants, and they were asked to study the
material for two weeks. In addition, a group was formed on a social network website,
and the students joined to this group. The aim of the group was to provide technical
support for the learners having trouble with QR Code application.
49
After two weeks, the time and place for the interviews were determined according to the
participants’ choices. Each interview took approximately five minutes. After the
interviews, the audio records were transcribed. According to the pre-prepared coding
draft, the questions and the students’ answers were analysed and reviewed.
Data Analysis
For the analysis of the data, inductive coding and descriptive analysis were used.
Inductive coding was used to reveal the concepts from the data and the connections
between the concepts. In descriptive analysis, the data are summarized according to
previously-set themes. For the purpose of emphasizing the views, direct quotations are
frequently used. The findings obtained are interpreted based on the cause and effect
relations (Yildirim and Simsek, 2008).
The researchers, without making any changes on the records, converted them into
written texts. For validity issues, an expert was asked for his opinion. According to
Yildirim and Simsek (2008), if more than one researcher analyzes the data together,
coding reliability must be studied. It is a must to reach .70 or higher for the reliability of
the data.
The researchers and the expert independently coded the data into appropriate themes.
The codings were compared, and it was found that since the reliability value was higher
than .70. Thus, the coding was found reliable. The data, which were placed according to
the interview chart, were defined, and the results obtained were supported with direct
quotations.
FINDINGS
After the analysis, the data were coded, and the themes were created. The findings were
interpreted according to the theories of Diffusion of Innovations and Uses and
Gratifications. The findings obtained via the research questions were as follows:
Awareness of QR Code technologies, types and aims of using QR Codes, QR Code
contribution to learning, and proliferation of QR Codes.
Awareness of QR Code Technologies
When the participants were asked about their awareness of QR Code technology, the
following findings were obtained:
Table: 1
Awareness of QR Code
Themes
No knowledge
Awareness
Advertisements
Medicine Boxes
Posters
TV – Internet
Frequency (f)
6
3
5
3
2
50
Types and Aims of Using QR Codes
According to participants’ answers about their preferences of using QR Codes and about
what their contents should be, the following findings were obtained:
Table: 2
Types and Aims of Using QR Codes
Frequency (f)
Themes
Preferences of use
Video
Image
Leading to social networks
Audio files
Download links
Preferences to content
Surface information
Deep information
Surface and deep information
14
5
7
4
5
3
1
11
When the participants’ views about using of QR Code were analyzed, it was found that
almost all of the students agreed on video directing. The other ideas were linking to
images, social networks, audio files and download links.
On this topic student named Alper mentioned:
“... I prefer video and social networks. Because there are already images
and texts in the book, but (using) videos wasn’t not possible. By using QR
Codes it’s now possible to use videos. Also, I think social network sites
used by a lot of people are easier and useful in terms of reaching the
necessary information.”
Most of the participants came to an agreement that separate QR Codes should be defined
both for surface information and for detailed information abusing QR Codes. Regarding
this, a student named Berk said:
“I think there must be both of them. Everyone should find something in an
environment addressing large populations. There could be different levels
of QR Codes.”
QR Code Contribution to Learning
The participants were asked about if using QR Codes for education had positive effect on
their learning. If so, which features of QR Codes were contributing to their learning? The
findings are presented in the Table below.
Table: 3
QR Code Contribution to Learning
Themes
No positive effect on learning
Positive effect on learning
Visuals
Ease of use
Direct leading
Attractiveness
Updatable information resource
Frequency
15
9
5
8
9
5
51
About the reasons and positive effects on learning, all of the participants shared the
same idea that QR Code supported lesson unit had positive effects on learning. When the
reasons were investigated, the following themes were found: positive effect of visuals,
ease of use, direct leading, attractiveness, and updatable information resource. A student
named Mansur said:
“Of course it has positive effects on learning. It is more interesting than an
ordinary book, so we can spend more time. In addition, there is an easier
and updatable content. It is quickly updatable. I think I prefer someone
teaching me to reading. That’s why I found it useful”.
Proliferation of QR Codes
The participants were asked for their ideas about proliferation of QR Codes to examine
whether they would use QR codes or not; whether using QR Codes were effective; which
factors would be the causes and which factors would restrain the use. The Table shows
the findings obtained.
Table: 4
Proliferation of QR Codes
Themes
The factors that would restrain the use
Difficulties and technical problems in the process of transition to new
technologies
Lack of academic staff who know how to use QR Codes
Preference of different technologies
Lack of necessary equipment
Need for technological knowledge
It will be effective to use QR codes
Frequency
Boredom with course books can be avoided
Direct links reduce the loss of motivation
Using multiple media together enriches the content
8
7
11
5
10
2
9
14
In addition, the participants listed the reasons for not using this technology as follows:
lack of teachers/academic staff who know how to use the technology; other available
technologies to prefer, lack of necessary equipment to use the technology, and if so,
there is a need for technological knowledge.
When the problems regarding the use of QR Codes in the lesson unit were examined, it
was found that most of the learners did not experience any problem. Those who had
problems reported that they experienced problems regarding fixing the cam angle,
resolution and connection issues. The participants favoring the use of QR Codes reported
that QR Codes acted like multimedia and that they could thus help reduce the routinized
structure of books. In addition, according to the learners, they experienced less
motivation loss, and enriched content would have positive effect on learning. One
student, Alper, expressed his ideas as follows: “... when I become a teacher, I am
planning to use QR codes. They help make learning more meaningful. Direct linking to
the resources does not cause any loss of time helps reach where you want to We don’t
lose time searching on the net. In addition, videos and audios available are very helpful.”
Mansur said “I think it’s favorable. Young people may get bored while reading books, I
think so, and I prefer this method.”
52
DISCUSSION
This study aimed at identifying the views of the participants about the QR Code
supported lesson unit. The results revealed that the participants achieved a consensus on
the positive effects of QR Code on learning. They stated that they would use QR Codes in
the future. This result could be explained with the theory of diffusion of innovations.
According to the theory of innovations, throught five stages of the theory students got
informed about QR Codes if they haven’t before, developed positive attitudes, accepted
the innovation, impletmented by using the QR Code application and confirmed the would
like use it in the future. In addition, the finding obtained is parallel to those reported in
other studies conducted by Susono & Shimomuro (2006), Liu, Tun & Chu (2007), Hwang,
Wu and Huang (2011) and Law & So (2010). According to the findings, participants find
QR Codes effective in terms of visuals, ease of use, direct linking, attractiveness and
updatable information sources. In addition the results of other studies carried out by
Miangah (2012), Rivers (2010) and Law & So (2010) also support the results obtained in
the present study.
It was found that most of the participants were aware of QR Codes. Use of QR Codes in
education was considered to be an innovation. This result shows similarity with the
%65-response of ‘YES’ to the question of “Have you ever seen a QR Code before”
directed in a study titled QR Code Usage and Interest Survey conducted by MGH (2011).
The participants’ responses were listed as ads, medicine boxes and TV-internet. This
result is also consistent with the findings reported by MGH (2011).
The participants agreed that the QR Code technology should be used for the spread of QR
Codes. This finding is consistent with those obtained in other studies carried out by
Ozcelik and Acarturk (2011) and by Rikala & Kankaanranta, (2012). In this context, the
participants’ expectations and gratification of these expectations were effective.
The main factor preventing the use of QR Codes is the need for enough technological
knowledge to install and use the application. Other factors can be summarized as
difficulties in transition to a new technology, lack of academic staff who knows how to
use QR Codes, learerns’ preferencing other technologies, and lack of necessary
hardware. Mobile devices and improvements in Internet, both in terms of speed and
content, have positive influence on diffusion of QR Codes.
Similar findings were also obtained in a study carried out by Rikala & Kankaanranta,
(2012). The difference from the this study is Rikala & Kankaanranta (2012) mentioned
the probable difficulties to be experienced in preparing QR code contents and pointed
out that such applications were likely to take a lot of time and that there was a need for
more examples regarding its use.
The participants mostly shared the same idea about using the QR Codes reporting that
they preferred to access the videos. In addition, the participants also favored the feature
of being directed towards social networks that leads learners to cooperate. Depending on
this statement, it could be stated that the dimensions of communication and cooperation
are necessary for learning. The dimensions of communication (Al-Khalifa, 2011) and
cooperation (De pretro & Frontera, 2012) are findings obtained in studies conducted on
the use of QR codes in education. When considered from the perspective of institutions,
it could be stated on the basis of Uses and Gratifications Theory that the participants
were satisfied with easy access to the learning content, direct linking and accessing rich
content using QR Codes.
The diffusion of innovation theory has five phases namely knowledge, persuasion,
decision, implementation and confirmation (Rogers, 1995). In the knowledge stage, the
learners were mostly familiar with QR Codes. Although they mentioned that they had
never seen QR Codes in the field of education. The participants and the researcher
53
discussed whether using QR Codes for education would be effective or not. All of the
students stated that there will be positive effect on learning. This can be named as
persuasion stage.. At the decision phase, the participants were asked for the reasons
that made them use course material supported with QR Codes. It was found that rich
media, high motivation, ease of use, and direct link affected their choice of use. The
findings obtained in this phase were similar to those reported in other studies conducted
by Law & So (2010) and Rikala & Kankaanranta, (2012) (easy use and motivation).
During the two-week review of the lesson unit, all of the learners used all the QR Codes.
There is a time difference between users, some did it in a faster than the others. At the
confirmation phase, the participants were directed questions about whether they were
thinking of using QR Codes in the future. All of the students answered answered that if
possible they would use QR Codes in the future. The interviews revealed that using QR
Codes for education would be beneficial and attractive. That would have positive effect
on learning. This result is consistent with the view reported by Rikala & Kankaanranta
(2012) that learners want to re-experience QR code-aided learning and that such
applications better be used for education.
It is possible to say that the learners who had reviewed the QR Code supported lesson
unit experienced the confirmation phase. The participants previously had knowledge
about what the QR Code is, what is it used for and how it can be helpful for learning.
They expressed positive opinions about increasing QR Code use for educational purposes.
In addition, it is also possible to say that QR Codes completed its diffusion among the
learners who reviewed the lesson unit.
Conclusion
CONCLUSION
Its’ possible to argue that augmented reality applications offer novel interations between
human and environment using mobile devices. The ubiquity of information systems
dilutes the boundaries of electronic and non-elecronic tools, devices and environments.
The era of information societies requires processing, transmitting and storing more data
and information in an increasing trend. QR Codes can contain more information when
compared to a regular barcode. Digital equipments like camera equipped mobile devices
and related applications lead the proliferation of QR Codes. On the other hand the
printed or the paper-based materials are still essential for deployment of information like
books, newspapers, research papers, letters etc. Using QR Codes on printed materials
like course books may enhance the attractive and elucidative aspects of printed
materials.
Although not many related studies have been conducted in the field of education, they
are generally used for supportive purposes. The research on QR Codes shows that they
were favored because of direct linking, merging rich contents and making them more
enjoyable. Motivation is one of the key factors of learning for open and distance-learning
learners. QR Code supported enjoyable learning environments may help learners to
maintain their motivation. QR Codes especially used in libraries are becoming more
common worldwide by uses and gratification (of QR technology?). It acts as a bridge
linking the physical environment to the virtual environment. As in the rest of the World,
In terms of Turkey, it is generally used in health-related environments, ads and bulletins.
Although it is easier to use QR Codes, it is not possible to use them without technological
necessities. It is also possible to argue that being accustomed to a technology may make
the new technology easier to learn and use. In this perspective the use of QR Codes
would increase in line with the increase in the related technologies like smart phones
and tablets.
54
BIODATA and CONTACT ADDRESSES of the AUTHORS
Dr. Gurhan DURAK has been working as a lecturer in Computer Education &
Instructional Technology department at Balıkesir university since 2006. He
recieved B.S and M.S degree in Computer Education & Instructional
Technology Department at Balıkesir university. He has completed his
doctoral degree on Distance Education at Anadolu University. He gives
lessons about instuctional design, technology integration and distance
education. He interested in online learning, instructional design,
educational social networking sites, computer programming and distance
education.
Gurhan DURAK
Balikesir University
Necatibey Faculty of Education
Balıkesir TURKEY
Phone: 90-266-2412762 ext: 150
Email: gurhandurak@balikesir.edu.tr
Emrah Emre OZKESKIN is lecturer at Open Education Faculty,
Anadolu University. He graduated from Çukurova University Faculty
of Education, English Language Teaching Department in 2001. He
received his master degree in Computer and Instructional
Technologies from the same university. He is also a Distance
Education PhD candidate at Anadolu University. His research areas
are adaptive learning environments, social network analysis and
learning analytics.
Lecturer Emrah Emre OZKESKIN
Department of Distance Education, Anadolu University,
Yunusemre Campus, 26470, Eskisehir, TURKEY
Phone: +90 222 335 0580 / 2704
eMail: eeozkeskin@anadolu.edu.tr
Dr. Murat ATAIZI is an associate professor in Communication Sciences
Faculty at Anadolu University, Turkey. His research studies are
communication technologies, problem solving, creativity, distance
learning, and gamification in education and communication. His
researches resulted in many articles and multiple chapters in
published books, which investigate communication and educational
communication context. He is currently managing a number of
projects focused on using games in communication education and
universal design in distance learning. Currently he teaches several
graduate and undergraduate courses on communication technologies,
creativity, problem solving, and distance learning both at the communication sciences
faculty, and social sciences institute.
Assoc. Prof. Dr. Murat ATAIZI
Communication Sciences Faculty, Anadolu University,
Yunus Emre Campus, Eskisehir, TURKEY, 26470
Fax: +90 222 3204520
Phone: +90 335 0581-5334, +90 542 5947244
Email: mataizi@anadolu.edu.tr
55
REFERENCES
ABI (2013). Q4 2013 Smartphone OS Results: Is Google Losing Control of the Android
Ecosystem? Retrieved from: https://www.abiresearch.com/press/q4-2013smartphone-os-results-is-google-losing-con.
Anadolu University (2012). The History of Open Education. Retrieved August 20, 2014,
from http://w2.anadolu.edu.tr/aos/aos_tanitim/aos.aspx
Al-Khalifa, H.S. (2011). An M-Learning System Based on Mobile Phones and Quick
Response Codes. Journal of Computer Science 7 (3): 427-430.
Arslan, M. (2011). Kare kodlar ile hayatimiz degisecek [QR Codes will change our lives].
Bilim ve Teknik, 44 (523), 78- 79.
Baker, L. (2010). Making physical objects clickable: Using mobile tags to enhance library
displays. Journal of Library Innovation 1(2):22-28.
Balci, A. (2004). Sosyal Bilimlerde Arastirma: Yontem, Teknik ve Ilkeler [Research in
Social Sciences: Methods, Techniques and Principles],(4.Baskı). Ankara: Pegema
Yayıncılık.
Berger, J. I. (2005). Perceived consequences of adopting the Internet into adult literacy
and basic education classrooms. Adult Basic Education, 15(2), 103–121.
Bolter, J. D., & Grusin, R. A. (2000). Remediation : understanding new media. Cambridge,
Mass.: MIT Press.
Charney, T., & Greenberg, B.S. (2001). Uses and gratifications of the Internet. In C.A. Lin
& D. J. Atkin (Eds.). Conzinunicatiorz teclznology and society: Audience adoptioiz
and uses of the new inedia (pp. 379-407). Cresskill, NJ: Hampton.
Chen, N. S., Teng, D. C. E., & Lee, C. H. (2011). Augmenting paper-based reading activity
with direct access to digital materials and scaffolded questioning. Computers &
Education, 57(2), 1705–1715.
Cisco. (2015). Cisco Visual Networking Index: Global Mobile Data Traffic Forecast
Update, 2014–2019 (White Paper). Retrieved from
http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visualnetworking-index-vni/white_paper_c11-520862.pdf
Clark, R. C., & Mayer, R. E. (2008). E-learning and the science of instruction : proven
guidelines for consumers and designers of multimedia learning. San Francisco, CA:
Pfeiffer.
Creswell, J.W. (2009). Research Design: Qualitative, Quantitative, and Mixed Methods
Approaches (3.ed.). Los Angeles: Sage Publications, Inc.
De Pietro, O., & Fronter, G. (2012). Mobile Tutoring for Situated Learning and
Collaborative Learning in AIML Application Using QR-Code. In 2012 Sixth
International Conference on Complex, Intelligent, and Software Intensive Systems
(pp. 799-805).
Dogan, A. (2012). Hanehalki Bilisim Teknolojileri Kullanım Arastirmasi [Households Use
of Information Technologies Research], Retrieved from
http://www.tuik.gov.tr/PreHaberBultenleri.do?id=10880#
56
eMarketer. (2014). Smartphone Users Worldwide Will Total 1.75 Billion in 2014.
Retrieved from: http://www.emarketer.com/Article/Smartphone-UsersWorldwide-Will-Total-175-Billion-2014/1010536#sthash.aW4Ti7aR.dpuf.
Hernández-Julián, R., & Peters, C. (2012). Does the Medium Matter? Online versus Paper
Coursework. Southern Economic Journal, 78(4), 1333–1345.
Huang, H. W., Wu, C. W., & Chen, N. S. (2012). The effectiveness of using procedural
scaffoldings in a paper-plus-smartphone collaborative learning context. Computers
& Education, 59(2), 250–259.
Hwang, G. J., Wu, C. H., Tseng, J. C. R., & Huang, I. (2011). Development of a ubiquitous
learning platform based on a real-time help-seeking mechanism. British Journal of
Educational Technology, 42(6), 992–1002.
Intel Corporation. (2012). Intel Genc Turkiye Arastirmasi [Intel Young Turkey Research].
Retrieved from: http://www.slideshare.net/gayekokten/genc-turkiye-arastirmasi.
LaRose, R., Mastro, D. A., & Eastin, M. S. (2001). Understanding Internet usage: A social
cognitive approach to uses and gratifications. Social Science Computer Review, 19,
395-413.
Law, C. & So, S. (2010). QR codes in education. Journal of Educational Technology
Development and Exchange, 3(1), 85-100.
LAW,C.Y., SO, W.W. S., & 蘇永華. (2010). QR codes in education. Journal of Educational
Technology Development and Exchange, 3(1), 85–100.
Liu, T., Tan, T., & Chu, Y. (2007). 2D Barcode and Augmented Reality Supported English
Learning System. Proceeding of the 6th IEEE/ACIS International Conference on
Computer and Information Science (pp 5-10). IEEE Computer Society
McCabe, M. Tedesco, S. (2012). Using QR Codes and Mobile Devices to Foster a Learning
Environment for Mathematics Education. International Journal of Technology
Inclusive and Inclusive Education,1 (6), 37-43.
Mcquail, D., Windahl, S. (2010). Iletisim Modelleri [Mass Communication Theory] (6.ed).
(Çev: K.Yumlu). Ankara: İmge Kitabevi Yayınları
MGH.(2011). QR Code Usage and Interest Survey. Retrieved from:
http://cn.cnstudiodev.com/uploads/document_attachment/attachment/11/qr_co
de_stats_3_23_11.pdf.
Miangah, T. M. (2012). Mobile-Assisted Language Learning. International Journal of
Distributed and Parallel systems, 3(1), 309–319. doi:10.5121/ijdps.2012.3126
Ozcelik, E., & Acarturk, C. (2011). Reducing the spatial distance between printed and
online information sources by means of mobile technology enhances learning:
Using 2D barcodes. Computers & Education, 57(3), 2077–2085.
Ozguven, I. (2004). Gorusme Ilke ve Teknikleri[Interview Principles and Techniques].
Ankara: PDREM Yayınları.
Papacharissi, Zizi and Alan M. Rubin (2000) “Predictors of Internet use”. Journal of
Broadcasting &Electronic Media, 44 (2), 175–196.
Pons, D. (2011). QR Codes in Use: The Experience at The UOV Library. Serials-24 (3), 4756.
57
Rikala, J., & Kankaanranta, M., 2012. The Use of Quick Response Codes in the Classroom.
In 11th Conference on Mobile and Contextual Learning (pp.148-155).
Rivers, D.J., 2010. Utilizing the Quick Response (QR) Code within a Japanese EFL
environment. J. Jalt Call Sig, 5: 15-28.
Rogers, M. E. (2003). Diffusion of innovation (5.ed.). New York: The Free Press.
So, S. (2008). A Study on the Acceptance of Mobile Phones for Teaching and Learning
with a group of Pre-service teachers in Hong Kong. Journal of Educational
Technology Development and Exchange, 1(1), 81-92.
Susono, H., & Shimomura, S. (2006). Using Mobile Phones and QR Codes for Formative
Class Assessment. in A. Méndez-Vilas, A. Solano Martín,, J.A. Mesa González & J.
Mesa González (Eds.). Current Developments in Technology-Assisted Education.
Badajoz, Spain: FORMATEX.
Uluyol, C., & Agca, R. K. (2012). Integrating mobile multimedia into textbooks: 2D
barcodes. Computers & Education, 59(4), 1192–1198.
doi:10.1016/j.compedu.2012.05.018
Walsh, Andrew (2011) Blurring the boundaries between our physical and electronic
libraries: Location aware technologies; QR codes and RFID tags. The Electronic
Library, 29 (4). pp. 429-437. ISSN 0264-0473
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Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 5
TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY
ICT APPLIED IN COMPUTER SCIENCE
Dr. Jose CAPACHO
Systems and Computer Science Engineering Department
Universidad del Norte
Barranquilla, COLOMBIA
ABSTRACT
The main objective of this paper is to show a set of new methodologies applied in the
teaching of Computer Science using ICT. The methodologies are framed in the conceptual
basis of the following sciences: Psychology, Education and Computer Science. The
theoretical framework of the research is supported by Behavioral Theory, Gestalt Theory.
Genetic-Cognitive Psychology Theory and Dialectics Psychology. Based on the theoretical
framework the following methodologies were developed: Game Theory, Constructivist
Approach, Personalized Teaching, Problem Solving, Cooperative Collaborative learning,
Learning projects using ICT. These methodologies were applied to the teaching learning
process during the Algorithms and Complexity – A&C course, which belongs to the area of
Computer Science. The course develops the concepts of Computers, Complexity and
Intractability, Recurrence Equations, Divide and Conquer, Greedy Algorithms, Dynamic
Programming, Shortest Path Problem and Graph Theory. The main value of the research is
the theoretical support of the methodologies and their application supported by ICT using
learning objects. The course aforementioned was built on the Blackboard platform
evaluating the operation of methodologies. The results of the evaluation are presented for
each of them, showing the learning outcomes achieved by students, which verifies that
methodologies are functional.
Keywords: Methodologies for virtual learning, virtual education, ICTs, virtual learning
platforms, virtual assessment.
INTRODUCTION
The theoretical development of the research in relation to the teaching methodologies
supported by ICT has the following phases: (i) Foundations of the behaviorist theory; (ii)
Gestalt theory; (iii) Foundations of Genetic- Cognitive Psychology; iv) Bases of the
Dialectical Psychology; and v) Bases of Computer Science.
The research integrates theoretical part with the practice, as represented by the
construction of the virtual course under the Blackboard platform. Finally, the research uses
teaching methodologies, through the platform, based on the above-mentioned theories, in
order to ensure students’ learning in virtual spaces supported ICTs.
THEORETICAL BASIS OF THE METHODOLOGIES
Pavlolv and Skinner are the main representatives of the behaviorist or associating approach
regarding to classical and instrumental conditioning respectively. In behaviorism, human
behavior receives the influences of the external world, which act as enhancers of it.
Education becomes a technology represented by a sequence of actions consisting of
mechanical stimulus- response - reinforcements, aimed at achieving the conditioning of the
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conduct of the subject. This conception is based on the principle "man is the product of the
environmental reinforcing contingencies" (Perez, A., 1995, p. 37).
The conditioning involves a sequence of mechanical stimulation (S) presented to the
subject, waiting for a response (R) and giving a reinforcement (E), generating a repetitive
cycle of sequences S/R/E/ . . . S/R/E. The relationship of this cycle to a space of virtual
training is represented by tutorial-type learning environments of virtual training,
exercising and practice, or conditioning software, among others. The above mentioned
environments are represented by learning objects, which integrate theoretical concepts
with practice making the students learn about real world concepts. These learning objects
can be built into the platform through games. Real and complex world cases in virtual
spaces such as: “Design and implementation for location-based learning games” (Melero
Gallardo, 2014); “The use of virtual worlds, with text-based, voice-based and a feeling of
‘presence’ naturally is allowing for more complex social interactions and designed learning
experiences and role plays, as well as encouraging learner empowerment through
increased interactivity” (De Freitas, Rebolledo-Mendez, Liarokapis, Magoulas, &
Poulovassilis, 2010); or “Pervasive augmented reality games to experience tourism
destinations” (Linaza, Gutierrez, & García, 2013).
The Gestalt theory is interpreted as the figure and ground to give meaning to the student's
learning, assessed via an observable behavior (a final exam). The Gestalt approach views
the conduct as an organized whole (Perez, A., 1995, p. 41). Then, a platform supported by
ICTs, in order to comply with processes of virtual training, is a system with hardware and
software components, comware (communications) to which it is necessary to add the
orgware (human talent) or the organization of the entire system of virtual training; if one
of the parties fails, the system does not work. Considering the virtual space as a whole, the
problem-solving teaching methodology supports the more complex learning; this is
confirmed by the fact that: "An important educational application of Gestalt theory is in the
area of productive thinking (problem solving) ". (Duncker, 1945; Luchins, 1942;
Wertheimer, 1945 cited by Schunk, D., 1997, p. 57) .Thus, in a holistic sense, the virtual
spaces of training through the teaching methodologies set out; allow the development of
higher learning in the subject.
In cognitive genetic psychology the two basic functional invariant of the intellectual
functioning of the subject are the organization and adaptation. Assimilation and
accommodation are the bases of the adaptation. The constant operation of these allow the
formation of units of knowledge calls diagrams, whose development in the time form
systems of knowledge and allow the subject to pass from a concrete thought to a formal
one, in its biological-intellectual development . One of the support to better understand
Piaget's theory has its basis on the Psychoanalytic theory of transference “…by regarding
transferences as schemas in which assimilation predominates over accommodation"
(Wachtel, 1980). The student in the learning process initially has some specific structures
of knowledge. The student interacts with the platform supported by ICT and if she/he
understands the structures of knowledge presented in the virtual course, then these
diagrams are assimilated into her/his mind. This brings about the change of concrete
cognitive structures to formal ones which corresponds to the stages of development of the
subject (Hipsky, 2008), and the virtual learning of the student. Based on Piaget’s
postulates, the course of A&C uses the personalized learning supported by ICT (Keane,
Keane, & Blicblau, 2014; Lyashenko & Frolova, 2014) in order to evaluate the change of the
cognitive structures of the student when interacting with the virtual course.
For the Dialectical Psychology based on the materialist philosophy the concept of psyche is
"(a) The psyche is a function … (b) the psyche of man is social,” (Montealegre, R., 1992, p.
11). Then, if the psyche of man is social, then the subject learns through the culture and
the interaction with the other (Anh & Marginson, 2013). The culture is present in the form
of signs through the digital network. These signs are stimuli-means for the subject, within
which is the human language and accordingly the language contained in the virtual course.
60
It is important to mention that the language in the ICT impacts the cognitive domains of
the subject’s audio, vision, touch, and smell. Therefore, "the main factor in the formation
of concepts, and its generative cause, is a specific use of words as functional instruments".
(Vygostky, L. 1995, new edition of the book Thought and Language in charge of Alex
Kozulin p. 125). The signs or functional tools of language in the network supported by ICT
allow the student to activate the Zone of Proximal Development - ZPD. The
interrelationship of the ZPD with the ICTs is based on the fact that the cognitive functional
structures of the brain are built in the ZPD or area of knowledge construction; and this area
is influenced by the virtual learning space, generating in this way the student's learning
influenced by the virtual course. The application of the learning in the interaction with the
other strategy based on Vigostky’s postulates is performed in the course of A&C using the
methodology of learning by projects. The projects are constructed based on the contents
of the virtual course, the information of the Internet macro network, and the interaction
between the students and the lecturer in charge. (Mukama, 2014).
Constructivism is based on the Cognitive genetic psychology (Piaget), and on the dialectic
psychology (Vigostky). In constructivism, learning is achieved by establishing relations
between the new knowledge and knowledge structures already existing in the mind of the
subject. In this sense, the design of the learning environment should allow the learners
explore their preconceptions and interact with the virtual space supported by ICT; besides,
it should generate new knowledge in the student, and finally, validate the new knowledge
generated by the student through the network, with the teacher's guide, or with their
peers, using learning communities. (S. Sergis, Zervas, & Sampson, 2014).
In the virtual teaching-learning process, Constructivism must be understood not only as a
philosophy but also as pedagogy. Then, it is necessary to associate constructivist teaching
that comply with the process of social learning to virtual level. Thus, constructivist learning
involves that the student must commit themselves to the social discourse using the
network, and validate the status of truth of the concepts presented in the virtual course,
for the students will generate their own concepts and their contribution to the construction
of knowledge. The social discourse in the network makes it possible for the apprentice:
understand other approaches in the resolution of problems, argue their solution, to
negotiate their ideas, expand or decrease the complexity of the problems, validate the
solution of problems in terms of effectiveness and efficiency, project new learning
experiences and research of constructivist nature (virtual worlds) (Shieh, 2012; Kotsilieris
& Dimopoulou, 2014).
Collaborative learning is based on Vigostky’s Social and Cultural theory. The virtual course
is a communication bridge between the student and the world, through the Internet. This
network enables the communication of the pupil in the virtual course and with other virtual
courses, providing opportunities to the student to interact with social and cultural contexts
different from which they belong to (Dabbagh & Kitsantas, 2012). In this sense students’
learning is not only influenced by their preconceptions but by the culture in which they
have been trained before applying to the virtual course. Based on the
apprenticepreconceptions, the collaborative learning is achieved through social interaction
(Dalgarno & Lee, 2010) that is presented in the learning process of the subject in their
relationship with the other through the communication media, in this case the virtual
course supported by ICT. The construction of knowledge in the subject has aspects both
individual and social, allowing an active participation of the student and a more
constructive role in the learning process. Therefore, the collaborative learning is an
approach that allows the subject be aware of the process of acquiring their cognitive
structures. As an active students, they must observe, compare and contrast their learning
with that of their colleagues, through the socialization of the work as a team to achieve
both their personal understanding as their sense of identity through social interaction
(Hughes, 2007).
The basics of Computer Science are related to the following areas: i) Software Engineering,
as a basis for the construction of the virtual course learning objects. ii) Programming
61
languages needed to program the virtual learning environment supported by ICT. iii)
Databases, to manage the status of student learning to navigate the virtual course. iv)
Computer Networks, for the operation of the course under the macro virtual Internet. v)
Security in computing, in order to meet security processes data stored in the course. vi)
Operating Systems in order to manage both the virtual course within the Blackboard
platform, and management processes processing requirements of both users (students) in
the virtual learning and teachers in virtual teaching. vii) Quality standars, to be met by the
construction of the virtual course supported by ICT, such as SCORM and IMS.
DEVELOPMENT OF METHODOLOGIES SUPPORTED BY ICT IN THE BLACKBOARD PLATFORM
The development of the methodologies proposed in this research paper will be applied
using the virtual course Algorithms and Complexity – A&C, designed (Capacho, J, 2004)
and programmed (Cure, V., & Fandiño, E (2005)) in the the Blackboard platform. In
development it is important to mention that the course – A&C was designed in Web_CT;
but as Web_CT was acquired by Blackboard, the virtual course – A&C is currently running
on this platform.
The teaching methodology of the subject Computers, complexity and intractability – CCI is
Game theory which is based on the behaviorist approach. The Game has the following
steps: 1) Presentation of the topics of CCI. 2) Activation of drill and practice games,
structured on learning objects within the Blackboard platform. 3) Operation of the object
of learning by the student. 4) Evaluation of the student learning or Assessment. 5)
Reinforcement given to the student via the learning object. 6) Decision on the level of
student learning. This decision allows: 7) Browse again learning objects or alternatively 8)
continue with the next module of the course of A&C. It should be borne in mind that each
game has a difficulty level, which represents the highest or lowest learning achievement
acquired by the student during the game.
The application of the methodology is shown in Figure 1, below:
Game theory with difficulty levels
Game theory using mazes
Figure: 1
Virtual learning using Game Theory.
Greedy algorithms module was developed based on the Gestalt theory, applying the
methodology of problem solving in virtual environments. The steps of this method are: 1)
Student applies previous knowledge to new situations. 2) State the problem to be solved
algorithmically. 3) Use the basic skills for the construction of greedy algorithms. 4) Define
the figure and ground of the resolution of the problem (Human Computer Interface). 4)
Translate the algorithms in a high-level languages (Java). 5) Run the program (JAVA). 6)
Evaluate the results generated by the program. 7) Improve the program in terms of
response time and memory space used.
The results of the interfaces for the problems solved by Greedy Algorithms: Make Change
and Memory Management in Operative systems are shown in Figure 2.
62
Figure: 2
Methodology of problem solving in virtual environments
The problem of the shortest path in A&C was developed based on the postulates of Piaget's
theory, and the teaching methodology used was the personalized teaching supported by
ICT. The steps in this methodology are: 1) Organization of the learning structures in the
virtual course on the problem of the shortest path. 2) Explore the student‘s preconceptions
on the topic of algorithmic cases of the shortest route problem, or student’s concrete
knowledge structure. 3) Interaction of students with learning objects related to the topic.
4) Assimilation and accommodation of the virtual environment content structures with
students’ cognitive structures. 5) Self assessment of student’s knowledge structure change
through the same learning objects. 6) Assessment of the student’s learning by the
professor. 7) Design the student's learning improving plan in the virtual environment.
The evidence of the use of the personalized teaching using ICT is represented by: 1)
Conceptual map of the organization of the shorter route problem on the virtual course
(Figure 3. 2) Test exploring student’s preconceptions. 3) Use of learning objects for the
shortest route (Figure 4). 4) Check the assimilation of knowledge structures in the student,
through the construction of a Java program (Figure 5). 5) Assessment and improvement of
student’s learning process.
63
Figure: 3
Conceptual map of the shorter route problem (Shortest Path Problem).
Figure: 4
Learning object for the study of the Shortest Path Problem.
Figure: 5
Check student learning using personalized teaching (Communication interface in JAVA for
the Shortest Path Problem).
64
Project based approach has its foundations on the Dialectical Psychology and Vigotsky’s
postulates, and it was used in the Module Graphs Theory with the following steps: 1)
Navigate the contents of the virtual module Graph Theory applications. 2) Interact with
learning objects (Figure 6) module related to the coloring of graphs and Ford and
Fulkerson’s algorithms. 3) Review research articles of the Association for Computing
Machines and the IEEE Computer Society (ACM/IEEE-CS) related with the development of
the module. 4) Write a representative essay of the theoretical and practical part of the
reviewed article. 5) Socialize the writing by placing it in the forum of the Blackboard virtual
platform. At this point student’s learning improves due to the interaction with their peers
and professor in the virtual course. 6) Build a second version of the writing based on the
results obtained in the forum. 7) Assessing student learning content in the final writing
essay. This not only represents the student’s research level in Graph theory but also
knowledge threshold applying Dialectical Psychology concepts in virtual spaces.
Figure: 6
Learning object representative of Graph Coloring.
65
The constructivist approach was implemented in the teaching methodology of the module
‘Recurrence Equations’ with the following steps: 1) Interaction of the student (knowing
subject) with the virtual course.2) Exploration of the initial student knowledge structures.
3) Interaction of students with recurrence equations learning objects (Figure 7).. 4)
Constructivist activities implementation (social discourse among participants using the
network in order to understand and transform student learning with their peers and
teacher). Socialization of virtual classroom activities supported by ICT. 5) Generation of
cognitive imbalances in the student. 6) Socialization of the module learning through the
network and between peers. 7) Assessment of student learning in the virtual module. The
results of the progress in the student's learning in solving recurrence equations are shown
in Figure 8 (Difficulty levels by solving the equations: i) Easy O(n) , ii) Intermediate O(2n+1)
, iii) Difficult O(n2)). Solving recurrence equations by constructivism, allowed students
identifying the preconceptions of this type of equations, investigating the theoretical
methods of solving recurrence equations, and obtaining the solution of the equation (T(n))
and the order of complexity (O(n)).
Figure: 7
Learning object supporting the resolution of recurrence equations.
66
𝑻 𝒏 = 𝑻 𝒏 − 𝟏 + 𝟏, 𝑺𝒊𝒏 > 𝟏
𝑻 𝒏 = 𝟏, 𝑺𝒊𝒏 = 𝟏
𝑻 𝒏 = 𝟒 ∗ 𝑻
𝒏
+ 𝒏, 𝑺𝒊𝒏
𝟐
≥𝟐
𝑻 𝒏 = 𝟐𝒏𝟐 − 𝒏
𝑻 𝒏 = 𝒏
𝒂𝒏 = 𝒂𝒏1𝟏 + 𝒂𝒏1𝟐
𝒂𝟎 = 𝟏𝒚𝒂𝟏 = 𝟏
𝑻 𝒏
= 𝑪𝟎 𝟐𝒏 + 𝑪𝟏 (−𝟏)𝒏
𝒂𝒏 ≅ 𝑶(𝟐𝒏9𝟏 )
𝑻 𝒏 ≅ 𝑶(𝒏𝟐 )
Figure: 8
Student progress using the constructivist approach.
𝑻 𝒏 ≅𝑶 𝒏
Recognizing the difficulties of the collaborative learning with ICT in educational practice
because of the time to develop the activities and the evaluation of the learning of students
(Fung*, 2004), this teaching methodology was used in the course of A&C in the module
Dynamic Programming - DP, carrying out a collaborative project of coding algorithms in a
programming language on DP. The method of teaching virtual collaborative projects to
develop the theme of Dynamic Programming is supports by conceptual maps and learning
objects. One of these objects shows the resolution of the Knapsack Problem. The problem
is given a backpack of capacity M, fill its capacity with the combination of N objects. Each
object has a weight (Pi) and a utility value (Vi). The aim is to fill the Knapsack so that the
gain of all objects carried in the backpack is maximized. These contents should be studied
by students with the guidance of the teacher and the virtual tutor before applying the
collaborative project. The learning object Knapsack Problem is shown in Figure No. 9.
Figure: 9
Learning Object: Knapsack Problem.
67
The collaborative project was structured as following: 1) The class was divided into
subgroups of students, who were equivalent in their academic performance in accordance
with the previous grades of Dynamic Programming topic. 2) Students and professor identify
problems feasible to be solved by Dynamic Programming. 3) State the problem to be solved
in the project. 4) Solve the problem algorithmically by using Dynamic Programming. In this
step, the student receives reinforcement guides by the assistant professor (Rua, 2015). 6)
Encode the problem to be solved in Java language. 7) Socialize the results of the problem
through the network in the forum. 7) Improve problem algorithmic solution, in accordance
with the recommendations of the professor and fellow-students of the class. Interface of
one of the reinforcement guides for the collaborative project is shown in Figue 9.
Figure: 9
Matrix Chain Product using Dynamic Programming (Sedgewick, 1992, p. 598).
The main objective of Product Chain Matrix is to find the minimum number of scalar
operations of a set of matrices, which can multiply. Given the matrices A34 B43 C32 D25 E54
F46 G63 H32, then the minimum number of scalar multiplications is 196. The optimal
parentización is (A(B(C((((DE)F)G)H)))).
Keep in mind that mathematically the number of ways in which you can parentizar n
variables is equal to Catalan Number. This number is represented by the mathematical
expression
𝟒(𝒏1𝟏)
𝑵𝑪 =
𝟐
𝒏∗ 𝝅∗𝒏
FUTURE RESEARCH
The virtual teaching methodology presented in this paper has a formal support in
Psychology, Education and Computer Science. Therefore, the following step is to do an
analysis of the relationship that currently exists between the theories of psychology and
education with the learning processes in virtual spaces supported by ICT. If this
relationship is made, it can be ensured that the process of virtual learning is done with an
educational, pedagogical and teaching sense, aiming at achieving a significant student
learning. The proven teaching methodologies ensure the student's learning from an initial
state to a final state of learning, i.e. since before interacting with the virtual course until
after receiving the support of the course. Therefore, in the process of virtual training it is
required intermediate states of student's learning, where the points of improvement of the
teaching-learning virtual process can be identified. The course was built in the Blackboard
68
platform with connection to the Java programming language; objects work in the domain
of the vision, then, it is important to investigate and build learning objects in the domains
of touch and smell associated with the Algorithms and the Theory of Complexity.
CONCLUSION
The research process to create and test teaching-learning methodologies applied to the
learning in virtual spaces supported by ICT, leads to conclude: i) The research was carried
out in time series of the year 2011 to 2014 (8 semesters). ii) In these years around 175
students were training in the subject Algorithms and Complexity - A&C, with a maximum
of 30 students and a minimum of 15 students per course. iii) Taking into account the status
of learning of the pretest (before using the virtual module) and those of the post- test (after
learning with the support virtual module), students achieved their best performance in the
module ‘Greedy Algorithms’; (iv) The methodology with the best student learning
performance level was that of problem solving, with an efficiency of 70 % (Figure 10). The
reasons of this qualitative performance are: Allow solving complex problems using the
computer (Traveling Salesman problem, in Computer Science). Verify the theoretical
results with those shown in the computer. Designing communication interfaces in the
platform supported by ICT. Improve the programming language JAVA in Greedy
Algorithms; v) The maximum increase in average of learning achieved by students was 43.8
per cent of the pretest to the test. vi) The minimum increase in average of learning was
21.5% in the topic of computers, complexity and intractability. (vii) The average of the
total increase of learning supported by the platform Blackboard was 22.3%.
2014 02
2014 01
2013 02
2013 01
2012 02
2012 01
2011 02
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Computers,
Complexity
and
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P : Pre-Test
T : Test
PIL : Percentage Increase in e-Learning
Figure: 10
Results of assessment in teaching and learning methologies supported by ICT applied in
Algorithms and Complexity.
The qualitative results of applying game theory are: i) A high level of motivation. ii)
Learning at student’s own pace, according to the choice of game difficulty level. iii) The
ability to receive feedback from the game in order to improve their learning. iv) Students’
highest level of attention to handle learning objects in the domain of audio, vision and
touch. However, the difficulties in using the methodology are: High response time of
learning objects for large values of input data (n >> 1 million); lack of stability in the
69
operation of the game, because of the type of student computer browser. It is of utmost
importance to note that the above problems are technical ones in the process of
communication between the server hosting the virtual course and the student computer,
and are not relevant to the virtual educational concept of the game.
The use of Gestalt theory applied to the process of learning with ICT gave the following
qualitative results: i) A high interest from students. This interest is evidenced by the use of
algorithm in solving practical problems. ii) Allows the design of human-machine
communication interfaces. iii) Makes possible the practical resolution of problems by using
a programming language (Java), which is motivating for students for the possibility of
designing software elements. iv) Students can check the results through operating results
JAVA programs. The aforementioned qualitative results validate the high performance of
students in the module Greedy algorithms. The actions to improve the application of this
methodology are: homogenize students’ learning level at the beginning of the virtual
module; and a higher level of attention of the virtual tutor to students in order to develop
the problems of high level of complexity related to operating systems or computers´
networks using algorithmic.
Applying personalized teaching (based on Piaget’s principles) using ICT in virtual
methodology brings about the following results: i) Students’ understanding of the
conceptual structure of shortest path problem module. This is evidenced by the use of
concept maps and the correct organization of teaching content in a tree structure. ii)
Students’ learning achievement from a concrete thinking to a formal one, evidenced by the
fact of 32.3% increase in learning. This implies student’s formal thought to achieve the
learning object requirements (Figure 5.). Although, the methodology is appropriate to
virtual education, it is necessary to take into account that the virtual tutor should design
an outline for each student, greatly increasing the professor’s and virtual tutor’s times to
attend students.
The implementation of the project-based methodology in algorithms course allowed the
starting of research processes in algorithmic complexity. This is one of the most difficult
virtual methodologies. The difficulty is justified not only by the research level but also for
technological resources required. Based on the above mentioned, the qualitative analysis
of the project-based methodology allows in virtual education: Review the state of the art
of the topic of the project that the student is virtually developing. Motivate the students
because they themselves selected algorithmic topic to research in complexity. Writing a
research paper from the undergraduate generates multidisciplinary interaction between
undergraduate and graduate level training because students participate competitively for
the best paper at the time of socializing research results in the virtual classroom as part of
Psychology Vygotsky dialectic. Students then expect feedback to generate a second version
of the research paper. Finally this virtual learning approach demands a high amount of time
for the teacher to guide and correct the state of development of all research papers of
students.
This methodology was applied to assess the students’ learning output according to ABET
(American Boarding for Engineering and Technology) Standard h). This standard is related
to the competencies the student must learn to understand the impact of engineering
solutions in a global, economic, environmental and social context.
The related results use a rubric, and for the first half of 2015 used the scales: Very poor,
poor, good and very good for a sample of twenty two research projects. Regarding the
standard mentioned the results are: i) In global and environmental contexts: 9% very poor,
0% poor, 50% good, and 41% very good. ii) Meanwhile the relevant results values for
economic and social contexts are: 5%very poor, 0% poor, 23% good, and finally, 73% very
good. The need for linking this methodology in this paper is to demonstrate the importance
of ensuring the quality of training students in learning processes in virtual spaces using the
project-based methodology, and to make relevant that virtual actions are essential to
support international accreditation processes.
70
Applying the constructivist approach supported by ICT is a challenge when it is used in
Algorithms. The challenge is to get students preconceptions evolve from a state of early
learning to a final moment of learning. Before starting the virtual module, all students have
different preconceptions. These are supported by the mathematical knowledge. The
structure of the process is that this knowledge is different in all students. Then, starting
from different bases all students must achieve the same response to solve the equation of
recurrence. Therefore, the approach application time is high, and it is also high the diversity
of mathematical approaches to reach the same response. This was the reason why the
advancement of learning level was not as high as it was expected. The level of learning
achieved in the approach was 22.3%.
Collaborative projects methodology implemented in the virtual Dynamic Programming
module produced the following results in qualitative terms: Students integrated theoretical
and practical strengths in project groups. Development time of projects in the JAVA
programming was shorter than when programmed individually. Solving problem results are
most effective. The time of consultations to virtual tutor and teacher decreased
considerably when making virtual collaboration projects. Then, students classified the
methodology functional and useful as an activity prior to a real job in a company.
Aditionally, the teaching methodologies presented in this paper meet the teaching
competencies and learning methods in accordance with the UNESCO suggestion. They also
help constructing virtual courses that increase both knowledge and learning of the
curriculum in both virtual and face-to-face modalities. (S. E. Sergis & Sampson, 2014).
BIODATA and CONTACT ADDRESSES of the AUTHOR
Jose CAPACHO is an assistant professor at the Universidad del Norte
(Barranquilla , Colombia). He did his doctoral studies at the University of
Salamanca (2008) (Spain), in Learning Processes in Virtual Spaces.
Professor Capacho earned his Master studies in Education at the Pontificia
Universidad Javeriana (Colombia, 1996). His undergraduate was made in
Systems Engineering in the Universidad Industrial de Santander – UIS
(Colombia, 1982). Professor has over 30 years of service at Universidad
del Norte. During this time, as Coordinator of the System Program, he has
led projects of National and International Accreditation of the System Program
(Universidad del Norte), with institutions such as the Colombian National Accreditation
Council (NAC) (1998,2005,2012);and the Agency Accreditation Board for Engineering and
Technolgy (2003, 2005). As a teacher he has participated in the renewal accreditation
process of the System Program with ABET Accreditation International (2013, 2014).
Jose CAPACHO
University del Norte, Barranquilla, COLOMBIA
Phone: 57 3509379
Email: jcapacho@uninorte.edu.co
REFERENCES
Anh, D. T. K., & Marginson, S. (2013). Global learning through the lens of Vygotskian
sociocultural theory. Critical Studies in Education, 54(2), 143-159.
Capacho, J. (2004). Design: Course of Algorithms and Complexity supported by ICT.
Universidad del Norte (Barranquilla, Colombia). Department of Systems
Engineering.
Cure, V., & Fandiño, E. (2005). Programming: Course of Algorithms and Complexity
supported by ICT. Universidad del Norte (Barranquilla, Colombia). Department of
Systems Engineering.
71
Dabbagh, N., & Kitsantas, A. (2012). Personal Learning Environments, social media, and
self-regulated learning: A natural formula for connecting formal and informal
learning. The Internet and higher education, 15(1), 3-8.
Dalgarno, B., & Lee, M. J. (2010). What are the learning affordances of 3-D virtual
environments? British Journal of Educational Technology, 41(1), 10-32.
De Freitas, S., Rebolledo-Mendez, G., Liarokapis, F., Magoulas, G., & Poulovassilis, A.
(2010). Learning as immersive experiences: Using the four-dimensional
framework for designing and evaluating immersive learning experiences in a
virtual world. British Journal of Educational Technology, 41(1), 69-85.
Fung*, Y. Y. (2004). Collaborative online learning: Interaction patterns and limiting
factors. Open Learning: The Journal of Open, Distance and e-Learning, 19(2),
135-149.
Hipsky, S. (2008). Piaget’s Developmental Stages. Information Resources Management
Association.
Hughes, G. (2007). Diversity, identity and belonging in e-learning communities: some
theories and paradoxes. Teaching in higher education, 12(5-6), 709-720.
Ingram, N. R. (2014). Time past: impacts of ICT on the pedagogic discourse in the
Interactive project. Technology, Pedagogy and Education, (ahead-of-print), 1-18.
Keane, T., Keane, W. F., & Blicblau, A. S. (2014). Beyond traditional literacy: Learning and
transformative practices using ICT. Education and Information Technologies, 113.
Kotsilieris, T., & Dimopoulou, N. (2014). The evolution of e-learning in the context of 3D
virtual worlds.
Linaza, M. T., Gutierrez, A., & García, A. (2013). Pervasive augmented reality games to
experience tourism destinations. En Information and Communication
Technologies in Tourism 2014 (pp. 497-509). Springer.
Lyashenko, M. S., & Frolova, N. H. (2014). LMS projects: A platform for intergenerational
e-learning collaboration. Education and Information Technologies, 19(3), 495513.
Melero Gallardo, J. (2014). Design and implementation techniques for location-based
learning games.
Mukama, E. (2014). Bringing Technology to Students’ Proximity: A Sociocultural Account
of Technology-Based Learning Projects. International Journal for Research in
Vocational Education and Training, 1(2).
Pérez, A. (1995). Los procesos de enseñanza-aprendizaje: análisis didáctico de las
principales teorías del aprendizaje. En J. Gimeno, y Pérez, A. Comprender y
transformar la enseñanza, (pp. 34-62). Madrid, España: Ediciones Morata, S. L.
Rua, M. (2015). Learning object: Matrix Chain Product. Assistant Professor of A&C,
Universidad del Norte (Barranquilla, Colombia). Department of Systems
Engineering.
72
Sergis, S. E., & Sampson, D. G. (2014). From Teachers’ to Schools’ ICT Competence
Profiles. En Digital Systems for Open Access to Formal and Informal Learning (pp.
307-327). Springer.
Sergis, S., Zervas, P., & Sampson, D. G. (2014). Towards Learning Object
Recommendations Based on Teachers’ ICT Competence Profiles. En Advanced
Learning Technologies (ICALT), 2014 IEEE 14th International Conference on (pp.
534-538). IEEE.
Shieh, R. S. (2012). The impact of Technology-Enabled Active Learning (TEAL)
implementation on student learning and teachers’ teaching in a high school
context. Computers & Education, 59(2), 206-214.
Schunk, D. (1997). Teorías del Aprendizaje. Mexico: Prentice-Hall Hispanoamericana, S.
A..
Sedgewick, R. (1992). Algorithms in C++. Addinson-Wesley Publishing Company, Inc.
Vygostky, L. (1995). Pensamiento y lenguaje. Barcelona. España: Nueva edición a cargo
de Alex Kozulín. Ediciones Paidós Ibérica S. A..
Wachtel, P. L. (1980). Transference, schema, and assimilation: The relevance of Piaget to
the psychoanalytic theory of transference. The annual of psychoanalysis.
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Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 6
INSTRUCTIONAL SCREENCAST: A RESEARCH CONCEPTUAL
FRAMEWORK
Muhammad Razuan ABDUL RAZAK
University Pendidikan Sultan Idris, MALAYSIA
Ahmad Zamzuri MOHAMAD ALI
University Pendidikan Sultan Idris, MALAYSIA
ABSTRACT
The literature review indicates that the benefit of screencast as an instructional media has
not clearly proved effective for all categories of students. This is due to the individual
differences in processing the information. Inadequate screencast design will cause strain to
students’ cognitive process which might impede learning. This shortcoming can be reduced
by imposing principles of reducing the external processing in screencast design. However,
the exact design effectiveness of screencast also depends on the cognitive style and learning
style of the students. The cognitive style will ultimately affect how information is processed
in the students’ memory structure. Students will also easily process the given information, if
it is performed in accordance with their dominant learning style. Taken together, this article
discusses the conceptual framework design of screencasts for instructional purpose.
Key words: Cognitive style, instructional media, learning style, screencast.
INTRODUCTION
Multimedia technology usage in the teaching makes learning process more fun as well as it
facilitates understanding of a content more effectively (Fook, Sidhu, Nursyaidatul & Norazah,
2011). This process becomes more comfortable with the availability of Internet access that
allows learning to be done online anytime and anywhere (Loch, 2011). This as a result has
opened a new dimension to the process of distance learning which appeared to be beneficial
for both instructors and students (Ahmad Zamzuri, Khairulanuar, Mohammad & Salman
Firdaus, 2011).The effective teaching and learning process would obviously make the
conveyed knowledge and skills more meaningful (Lloyd & Robertson, 2012) and this can be
achieved sufficiently if suitable instructional media is used (Baghdadi, 2011).
One of the multimedia-based instructional media is screencast; the medium that will be the
main focus of the conceptual framework design of this study. Screencast is a digital video
that displays a part or the entire capture of the computer screen, where the narration or
voice may be included to describe the activity on the screen (Udell, 2005). The use of
screencast as instructional media in the teaching and learning process is important,
especially in learning the use of a software application (Brown, Luterbach, & Sugar, 2008;
Carr & Ly, 2009; Lloyd & Robertson, 2012). This is due to the screencast’s capability in
creating an identical presentation condition in every learning sessions (Carr & Ly, 2009).
Thus, the use of screencast is perceived useful as an additional resource to aid students in
learning the software applications independently and effectively (Ahmad Zamzuri et al.,
2011).
74
Although screencast is beneficial for independent learning, its use has not been proven
effective for all categories of students. This is because the perception of students in the
process of selecting information needed for effective learning is different from one learner to
another (Bailey, 2012). This is due to the students’ dissimilar cognitive style in translating
the obtained course contents into easy to understood information (Ahmad Rizal & Yahya,
2008; Renumol, Janakiram & Jayaprakash, 2010). In addition, the manner of information
selection also depends on the learning styles of the students which was formed since their
early childhood (Rosniah, 2007). Therefore, this conceptual framework will look at the
impact of different multimedia elements in screencast presentations on learning of students
with different cognitive styles and learning styles.
INSTRUCTIONAL SCREENCAST
Screencast is derived from the terminology used by Jon Udell in 2005, which refers to digital
video presentation (Fancett-Stooks, 2012). It was widely used for all levels of students from
the lowermost up to tertiary (Fraser & Maclaren, 2012; Winterbottom, 2007). Thus,
screencast is an effective method in explaining the procedure of computer-based work,
especially the features of particular software application (Brown et al., 2008; Carr & Ly,
2009; Lloyd & Robertson, 2012).
Findings from previous researches clearly indicate that screencast as an instructional media
has positive impact on its users, which includes instructors or students at any level (Ahmad
Zamzuri et al., 2011; Bailey, 2012; Budgett, Cumming, & Miller, 2007; Fancett-Stooks, 2012;
Fraser & Maclaren, 2012; Kraft, 2009; Lloyd & Robertson, 2012; Loch, 2012; Mullamphy,
Higgins, Ward, & Belward, 2010; Oehrli, Piacentine, Peters, & Nanamaker, 2011; Peterson,
2007; Pinder-Grover, Millunchick, & Bierwert, 2008; Rocha & Coutinho, 2010; Winterbottom,
2007). By using screencast, information can be delivered and processed effectively compared
to conventional printed media (Lloyd & Robertson, 2012). The usage of printed media
involves complex cognitive processes in the memory structure. This is because, printed texts
have to compete with the illustrative presentations which have to go through the same visual
channels (Mayer, 2005a). Therefore, by using screencast, the load of the working memory of
the visual channel and the verbal channel can be minimized to facilitate learning more
effectively.
However, the question arises is, will all the students from the same class will get identical
benefits from the developed screencasts? This is because, from various screencast design,
none are more prominent between one another, which might due to different cognitive
ability of students (Oehrli et al., 2011). This happens because only limited information can be
processed in the working memory at one time; based on the principle of limited capacity of
working memory (Mayer, 2005a; Jong, 2010). Therefore, in order to reduce the load in the
working memory throughout the learning process, instructional material developer must
take into consideration on how to reduce external processing (Mayer, 2005b; Oud, 2009).
External processing is the integration of the external information (extraneous material) with
the essential information (essential material) in an instructional medium (Mayer, 2005b). By
reducing the extraneous materials, students can focus in processing the essential material
without being burdened with unwanted external information. However, the question arises
again, whether the verbal assistance (narration and text) serves as extraneous material or
essential material in achieving the objectives of the screencasts presentation, especially in
learning software applications.
Basically, screencast presentations integrated with narration or text will facilitate the
learning process (Oehrli et al., 2011). This elements serve as additional information in the
75
screencast to ensure effective learning (Fancett-Stooks, 2012). Thus, the inclusion of text
along with screencast or screencast with recorded narration helps in emphasizing the
understanding of software application (Fancett-Stooks, 2012). However, text can only
contribute to learning improvement for students who tend to learn through visual or lack of
learning through listening (Educause, 2006). This is contrary to a study by Bailey (2012),
which stated that screencast gives an advantage to students who learn better by seeing and
hearing from students who learn through reading. Bailey's (2012) study was supported by
Nafaidilah (2012) who found that the use of narration in screencast application is necessary
to ensure its effectiveness. However, Nafaidilah (2012) did not cover the effect of text or
combination of narration and text in screencasts in her study.
Diverse modalities in screencasts can actually deliver a better understanding of learning than
narration or text alone (Ozsvald, 2010). This can be done through the addition of subtitles or
narration in the language that is easily understood by majority of users (Ozsvald, 2010).
However, the study by Veronikas and Maushak (2005), did not support this assumption.
Veronikas and Maushak (2005) found that there were no significant differences on the use of
a combination of narration and text in the screencasts instead screencasts with narration or
text only. This is because students tend to learn in a multimedia approach in diverse
modalities to help them get a better understanding (Veronikas & Maushak, 2005). The
question is whether the diversity of modalities in screencast really affects in improvement of
practical skills of students, especially in learning software application?
The usage of screencasts with diverse modalities is said to have a positive impact, however,
the imbalance of the effectiveness in learning a software application still exist (Bailey, 2012;
Educause, 2006; Fancett-Stooks, 2012; Nafaidilah, 2012; Oehrli et al., 2011; Ozsvald, 2010;
Veronikas & Maushak, 2005). This is due to the fact that its usage will provide a high load to
the working memory or short-term memory based on the diversity of the information
presented as text, graphics, audio and movement which will be processed simultaneously
(Bétrancourt, 2005). Thus, by reducing the load of the working memory, the students'
attention can be diverted to important information in the process of learning. As such, this
framework will focus on the design of the screencast with various modality strategies in
reducing external processing to assist in meaningful learning.
Cognitive Style and Learning Style
Beside the design aspects, cognitive style is an important element that needs to be
considered in the study on the effectiveness of instructional media. This is because, most of
the instructional media developers often assume that every students will learn in the same
style (Riding & Sadler-Smith, 1997). This assumption has actually denied the importance of
individual differences in cognitive style outlook (Riding & Sadler-Smith, 1997). Cognitive
style is an individual approach in organizing and conveying information during the process of
thinking consistently (Riding & Sadler-Smith, 1997). Cognitive style can also be described as
an individual’s personality dimension that influences the attitudes, values and social
interactions (Zabedah & Wah, 2005).
Cognitive styles are categorized into two, which are Field Dependent (FD) and Field
Independent (FI) (Witkin, Moore, Goodenough & Cox, 1977). FI individuals are found to be
more likely to separate a bigger matter into smaller things (Azizi, Asmah, Zurihanmi &
Fawziah, 2005). Thus, it will enable them to analyse the smaller components compared to FD
individuals who view a component as a whole (Azizi et al., 2005). FI students are more
individualistic and requires no external reference to process information (Chen, Magoulas, &
Dimakopoulos, 2005). This is in contrast with FD individuals who are socially-orientated and
influenced by the opinions of others and needs external support to process information
76
(Chen et al., 2005). However, both FI and FD cognitive styles are interconnected with
specific abilities of students and often have a positive impact in computer-based learning
(Hall, 2000). This was supported through research by Angeli and Valanides (2004), who
found that the usage of text and visual modalities for FI students improved their
performance in learning compared to FD students. This outcome was also supported by
Jailani, Wan Mohd Rashid and Ahmad Rizal (2007), who found that the diversity of modality
in the development of an instructional media is able to increase FI students’ performance
compared to FD students. Therefore, FI students are found to have more benefits than FD
students through a complex mix of media in the instructional media (Chuang, 1999).
However the study by Angeli dan Valanides (2004), found that FI students do not show
significant effects of improvement on the performance compared to FD if the media only
integrates the text. The question that arises is whether FI and FD individuals will show a
different level of understanding in screencast learning methods.
The different cognitive styles is actually closely influence the learning depending on how the
instructors convey information of their lesson (Ahmad Rizal & Yahya, 2008; Renumol et al.,
2010). Students who fail to extract necessary information from the instructor will face
problem in translating the received information into meaningful understanding. This
consequently will be the factor of failure of students in the performance test. Thus, students
with different cognitive styles will definitely limit the information that they have received
and also processed. Therefore, instructional media such as screencast should be able to
provide a positive impact on students with different cognitive styles, during the teaching and
learning process (Renumol et al., 2010).
Beside cognitive style, the effectiveness of instructional media is also influenced by the
students’ learning style. Students’ learning style refers to the different skills of individuals in
processing information effectively (Mestre, 2012; Norasmah & Mohd Hasril, 2010). It is a
particular individual ability to process, store and retrieve all the received information (Felder
& Henriques, 1995). Thus, the developer of instructional media such as screencast should
also take into consideration the aspects of students’ learning styles in their design phase.
The formation of a students’ learning style actually happens through the learning process
that begins since early childhood (Rosniah, 2007). This formation process occurs naturally
and continues until the formation of individual learning styles. Hence, instructors need to
know their students’ learning styles to help them get a better understanding of a topic that is
being learnt (Alhosban, Fuad, Hamad & Mousa, 2011). This can be achieved if the instructor
practices the teaching styles that matches the students’ learning styles (Felder, 2010; Felder
& Silverman, 1988), which would eventually lead to the retention of new information
naturally in the memory structure (Bastable, 2008). The right usage of graphic processing,
text and audio in screencast is seen to meet the needs of the dominant learning styles of
students (Fancett-Stooks, 2012; Loch, 2012; Pinder-Grover et al., 2008; Rocha & Coutinho,
2010; Winterbottom, 2007). Therefore, it is important to carry out research to identify the
appropriate strategies to address this issue.
Learning styles of a student can be identified through studies related to the learning style
models including the learning styles model by Felder-Silverman (1995), Dunn and Dunn
(1979), Kolb (1984), Honey and Munford (1982) and VARK (Visual, Aural, Read or Write and
Kinesthetic) (2001). However, this study will concentrate on the VARK learning style,
because this learning style is significant to the multimedia-based instructional medias
(Norasmah & Mohd Hasril, 2010). Study by Yosep, Wawan Setiawan and Waslaludin (2012),
also supported the usage of VARK learning style because they are more dominant in
multimedia-based learning.
77
THEORITICAL FRAMEWORK
For the purpose of this study, the conceptual framework that was developed is based on the
Cognitive Theory of Multimedia Learning (CTML) (Mayer, 2005a), cognitive style and learning
style models. It is the multimedia principle in reducing the external processing (reducing
extraneous processing) which puts strain on the working memory, namely, the Principle of
Coherence, Principle of Signalling, Principle of Redundancy, Principle of Spatial Contiguity
and Principle of Temporal Contiguity (Mayer, 2005b). Besides, the theory of cognitive styles
is Field Independent (FI) and Field Dependent (FD) and VARK learning style.
Cognitive Theory of Multimedia Learning
CTML is based on students attempt to build a meaningful relationship between the words
and pictures (Mayer, 2005a). This is grounded on the three principles of cognitive science,
namely dual-channel assumption, limited capacity assumption and active processing
assumption (Mayer, 2005a). The principle of dual-channel assumption refers to working
memory that has auditory and visual channels. The principle of limited capacity assumption
refers to the internal system with limited working memory. The principle of active processing
assumption refers to the construction of knowledge in a meaningful way. When attention is
given to the relevant material, the compilation of mental model structure in a coherent form
is integrated with the existing knowledge to be registered in the long-term memory in
schema form (Mayer, 2005a).
There are three memory storages in CTML, namely sensory memory, working memory and
long-term memory. Sensory memory will store the presented media for only around 0.25
seconds. The working memory will select information from the sensory memory to be
processed and integrated with the existing information. It processes the presented media
and is generally in less than thirty seconds as well as can only process some part of media at
a time (Mayer, 2010). Meanwhile, the long-term memory stores information in the form of a
schema in an unspecified period of time.
The learning process will generally be restricted when the cognitive load increases as a result
of the working memory capacity reaching its limit (Jong, 2010). To overcome this problem,
Mayer (2009) has outlined twelve multimedia instructional principles namely, the Principle of
Coherence, Principle of Signalling, Principle of Redundancy, Principle of Spatial Contiguity,
Principle of Temporal Contiguity, Principle of Segmenting, Principle of Pre-training, Principle
of Modality, Principle of Multimedia, Principle of Personalization, Principle of Voice and
Principle of Image. Multimedia instructional principles according to Mayer (2009) can be
categorized in three cognitive load frames as shown in Table 1.
78
Table: 1
The Framework of Cognitive Load and Instructional Principles
Framework of Cognitive Load
Reducing Extraneous Processing
Principles Of Instruction
Principle of Coherence
Principle of Signalling
Principle of Redundancy
Principle of Spatial Contiguity
Principle of Temporal Contiguity
Managing Essential Processing
Principle of Segmenting
Principle of Pre-training
Principle of Modality
Fostering Generative Processing
Principle
Principle
Principle
Principle
of Multimedia
of Personalization
of Voice
of Image
The focus of this study is based on an outline of Reducing External Processing that involves
five principles which is Coherence, Signalling, Redundancy, Spatial Contiguity and Temporal
Contiguity. Thus, reducing the external processing is seen as the first process that should
take place before the process of managing important processing to encourage the process of
generative processing. This is because, this process occurs in the sensory memory before
being processed in the working memory and subsequently in the long-term memory. These
five principles are described and shown in Table 2.
Table: 2
Five Principles of Reducing the External Processing
Principles Of Instruction
Principle of Coherence
Description
Students will learn better if external elements are removed.
Example:
Issuing interesting but irrelevant statements or graphics used.
Principle of Signalling
Students will learn better if the signal to process the information is given.
Example:
Insert signals, signs or assertion of important information for students to show
what to do and how to organize them.
Principle of Redundancy
Students will learn better if information is not provided within the same sensory
channels.
Example:
Redundancy - print text and narration are presented simultaneously with the
display screen.
Non Redundancy - narration is presented simultaneously with the display screen.
Students will learn better if the printed text is near the graphics that corresponds
to reduce the need for visual scanning.
Example:
The text is placed close to the same part of the illustration (on paper) or animation
(on the screen).
Students will learn better if the narrative and animation displayed at the same
time to reduce stake memory.
Example:
Narration and animation are presented simultaneously than either individually
before presenting new text animation or animation before the new text.
Principle of Spatial
Contiguity
Principle of Temporal
Contiguity
79
Cognitive Styles
To produce meaningful learning, the development of instructional strategies should be
student-centred rather than technology-centred (Mayer & Johnson, 2008). It is
acknowledged that each student has different methods and styles in processing the
information given. For that reason, the cognitive style of the students in the learning process
is also different. As been discussed, cognitive styles of students are categorized into two,
Field Dependent (FI) and Field Independent (FI) (Witkin et al., 1977). FI students are more
individualistic and require no external reference to process information. This is in contrast
with FD individuals who are socially-oriented and influenced by the opinions of others and
need external support to process information (Chen et al., 2005). Table 3 shows the
individual differences in FI individual cognitive styles compared to FD individuals cognitive
styles in more detail.
Table: 3
Field Independent (FI) and Individual Field Dependent (FD) Individual differences
Individual Field Dependent
Field Independent
1. Fast isolate simple geometric form of
complex geometric shapes
2. Can overcome the effects of background
elements that interfere
3. Be analytical
4. Skilled in building the structure of a structure
that does not have structure
5. A short time completing task without much
offense
6. Need help to focus on matters involving
social
7. Inclined to have personal goals and
enforcement
8. Less influenced by criticism
9. Able to analyse situations and organize
things
10. More likely to solve problems without
instructions from outside and outdoor
observation
1.
Facing the difficulty to discriminate
2.
6.
Unable
to
overcome
the
effects
of
background elements that interfere.
Global Nature
Not skilled in building the structure of a
structure that does not have structure
Hours completing task but slightly more
correct
Has the advantage of social learning
7.
Requires self-goal structure and enforcement
8.
9.
Easily swayed by criticism
Looking globally and cannot organize things
3.
4.
5.
10. Need directions from outside to solve the
problem
VARK Learning Style
The VARK learning style is the second underlying theory of this framework. VARK learning
style is classified as students’ learning styles in four different modes which are visual, aural
(auditory), read / write, kinesthetic (Fleming & Baume, 2006). Fleming and Baume (2006),
classifies in visual category, students prefer to learn through charts, diagrams and pictures.
Aural category (auditory) is ideal for students who learn through discussions and listening.
While in The read/ write category students can easily access information through reading the
printed or written words, for example taking lecture notes. Finally kinesthetic category
students learn better through touching, feeling, seeing and hearing as well as to do their own
learning activities. With regards to this, the different cognitive styles and learning styles of
students demand that instructional materials to be developed in a more student-centred
manner.
80
CONCEPTUAL FRAMEWORK DESIGN
Based on the theoretical framework, the conceptual framework suggest screencast to be
developed based on five principles to reduce external processing as in Figure 1. Through
these five principles, the students’ learning process will occur when they are able to focus to
process essential information compared to processing both essential information and
extraneous information simultaneously. Thus, by applying the principle of Coherence and
Redundancy in the development of screencast, external information processing can be
minimized. Once this external information is minimized, next, the students’ focus and
attention to essential information could be improved through the Signalling Principle and
Spatial Contiguity Principle within an emphasis on the usage of appropriate images, text or
language. Lastly, through the Temporal Contiguity Principle, the needs of students’ working
memory in processing important information before it can be transformed into meaningful
information could be simplified by essential information presented simultaneously in the
visual channel and auditory channel.
Working Memory
Principles of
Reducing External
Processing
Screencast
Instructional Strategy
1. Screencast + Narrative.
2. Screencast + Text.
3. Screencast + Narrative + Text.
4. Screencast.
Mental Model
Redundancy
Field Independent
Field Dependent
Cognitive Style
Kinesthetic
Aural
Read/Write
Visual
Learning Style
Long Term
Memory
Schema
Practical skills
of students
Figure: 1
Conceptual Framework for Screencast Research
Essential information from the screencast will go through the selection process of words and
images. The sense of hearing will choose the sound of words in the form of narration and
visual sense will select the images in the form of screencasts and the text displayed on the
screen. Next, through the auditory channel and visual channel in working memory or shortterm memory, words and images will be compiled to form a mental model which will be
integrated with the existing knowledge of the students. The information from working
memory or short-term memory which is integrated with the students’ existing knowledge
will then be stored permanently in the long-term memory in the schema form. The schema
developed and stored in permanent basis in the long-term memory can be retrieved by the
students in solving the problems given in the practical skill tests or assignments. The
question arises, among the instructional strategies of screencasts, which can contribute
maximum effects to the perfection of the students’ mental model formation? Various
modalities that were used in the screencast presentation are likely to influence the students’
mental model formation. Thus, all four strategies suggested will probably may or may not
81
impose redundancy in the students’ memory structures. This can be seen from inconsistent
outcome of past studies Therefore, proper design of the screencasts can help in the
formation of accurate mental models and it will affect the formation of meaningful schema in
the long-term memory.
The formation of students’ mental models is also likely related to their cognitive style. FI
cognitive style students may not face problems in utilizing the four instructional strategies as
they prefer to solve problems without external instructions and external observation. This is
contrary with FD cognitive style students since they need specific and clear instructions to
solve the problems given. The question that arises here, is whether the FI students will easily
master the content of the delivered lessons compared to FD students, especially in mastering
the software through any screencast presentation strategies? Thus, the different cognitive
styles might produce different results for the four suggested instructional strategies of
screencast.
Apart from the different cognitive styles, the formation of mental models is also likely to be
influenced by students’ learning styles. This is because, students learning styles has been
formed at the early stages of childhood and subsequently forms their own learning styles
until adulthood. Hence, a students’ learning style will be influenced by their dominant
learning styles either visual, aural (auditory), read/write or kinesthetic. The question is
which are the students’ dominant learning styles that are used mainly in learning the
software? Therefore, by identifying the most dominant learning style, then, a more accurate
result in the construction of effective instructional strategies can be delivered.
Finally, the load of the working memory or the short-term memory of students would be
reduced through the use of appropriate principles of reducing the external processing in all
four screencast designs. Thus, the adequate design approach of text and narration usage in
the screencast should give maximum impact on students’ learning. This will assist them in
the formation of accurate mental models and then formation of perfect schemas in the longterm memory.
CONCLUSION
The use of screencast as an instructional material in the process of teaching and learning is
important, especially in studying the use of a software application. It has the ability to create
a delivery that equals the classroom lecture as well as useful additional resource in learning
the application independently and effectively. Results from previous studies have
acknowledged that screencasts can be used as an additional tool in teaching. However, its
use has not been proven effective for all the categories of students in the same class. This is
due to the students’ own perception which differs in terms of the selection of the required
information. It depends on the students’ cognitive style and learning style in forming and
translating the information into knowledge that could be easily understood. The conceptual
framework developed in this study can be a useful guide in addressing this matter. However,
the conceptual framework was developed merely based on literature reviews. Therefore, it is
important to conduct related studies to further affirm the framework. The studies that look
on the effects of various screencast designs on learning of students with different cognitive
styles and learning style is important to be discovered. Specifically, study in looking on the
relation and correlation between various screencast designs with various learning styles and
cognitive styles must first be established. Studies in looking on the interactions between
various screencast designs and various learning styles and cognitive styles are also
important. Finally, experimental studies in determining the ideal screencast design for
specific learning style and cognitive style are also important to further detail the conceptual
framework developed.
82
BIODATA and CONTACT ADDRESSES of the AUTHORS
Muhammad Razuan ABDUL RAZAK, born in Malaysia. Currently, a PhD
student in the Faculty of Art, Computing and Creative Industry,
University Pendidikan Sultan Idris, Malaysia. He has a Bachelor Degree
in Biological and Agricultural Engineering from University Putra
Malaysia and a Master in Education from University Tun Hussein Onn
Malaysia. His research interest is focused on Instructional Technology
and Multimedia Design. Has taught both face-to-face and online classes
in higher education for over 7 years.
Muhammad Razuan ABDUL RAZAK
Faculty of Art, Computing & Creative Industry
Universiti Pendidikan Sultan Idris
Tanjong Malim, 35900, Perak, MALAYSIA
Email: razuanrx@gmail.com
Dr. Ahmad Zamzuri MOHAMAD ALI, born in Malaysia. Currently, an
Associate Professor of Multimedia in the Faculty of Art, Computing and
Creative Industry, University Pendidikan Sultan Idris, Malaysia. He has a
Bachelor Degree in Electrical Engineering from University Teknology
Malaysia, a Master in Education from University Teknology Malaysia and
PhD in Multimedia Design from University Sains Malaysia. His research
and publication interest is focused on Multimedia Design and Instructional
Technology. Has taught both face-to-face and online classes in higher
education for over 15 years.
Assoc. Prof. Dr. Ahmad Zamzuri MOHAMAD ALI
Faculty of Art, Computing & Creative Industry
Universiti Pendidikan Sultan Idris
Tanjong Malim, 35900, Pera, MALAYSIA
Email: zamzuri@fskik.upsi.edu.my
REFERENCES
Ahmad Rizal M., & Yahya B. (2008). Gaya kognitif dan visualisasi pelajar melalui perisian
Multimedia. Masalah Pendidikan, 31(1), 181–192. Retrieved from
http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:GAYA+KOGNITIF+D
AN+VISUALISASI+PELAJAR+MELALUI+PERISIAN+MULTIMEDIA#0
Ahmad Zamzuri M. A., Khairulanuar S., Mohamad H., & Salman F. S. (2011). Does screencast
teaching software application needs narration for effective learning ? The Turkish Online
Journal of Educational Technology, 10(3), 76–82.
Alhosban, Fuad, Hamad, & Mousa. (2011). The effectiveness of aural instructions with
visualisations in e-Learning environments. Retrieved from
http://etheses.dur.ac.uk/3201/
Angeli, C., & Valanides, N. (2004). Examining the effects of text-only and text-and-visual
instructional materials on the achievement of Field-Dependent and Field-Independent
learners during Problem-Solving with Modeling Software. Educational Technology
Research and Development, 52(4), 23–36. doi:10.1007/BF02504715
83
Azizi Y., Asmah S., Zurihanmi Z., & Fawziah Y. (2005). Aplikasi kognitif dalam pendidikan.
Kuala Lumpur: PTS Profesional Publishing.
Baghdadi, Z. (2011). Best practices in online education : Online instructors, courses, and
administrators. Turkish Online Journal of Distance Education, 12(3), 109–117.
Bailey, J. (2012). Informal screencasting: results of a customer-satisfaction survey with a
convenience sample. New Library World, 113(1/2), 7–26.
doi:10.1108/03074801211199013
Bastable, S. B. (2008). Nurse as Educator : Nurse as Educator Principles of Teaching. (S. B.
Bastable, Ed.) (3rd ed.). Boston: Jones and Bartlett Publishers.
Bétrancourt, M. (2005). The Animation and Interactivity Principles in Multimedia Learning. In
The Cambridge Handbook of Multimedia Learning (1st ed., pp. 287–296). NY.
doi:10.1017/CBO9780511816819.019
Brown, A., Luterbach, K., & Sugar, W. (2008). The current state of screencast technology and
what is known about its instructional effectiveness. In Proceedings of Society for
Information Technology & Teacher Education International Conference.
Budgett, S., Cumming, J., & Miller, C. (2007). The role of screencasting in statistics courses.
In International Statistical Institute, 56th Session. Lisbon, Portugal. Retrieved from
https://researchspace.auckland.ac.nz/handle/2292/16851
Carr, A., & Ly, P. (2009). “More than words”: screencasting as a reference tool. Reference
Services Review, 37(4), 408–420. doi:10.1108/00907320911007010
Chen, S. Y., Magoulas, G. D., & Dimakopoulos, D. (2005). A flexible interface design for Web
directories to accommodate different cognitive styles. Journal of the American Society
for Information Science and Technology, 56(1), 70–83. doi:10.1002/asi.20103
Chuang, Y. R. (1999). Teaching in a multimedia computer environment: A study of the effects
of learning style, gender, and math achievement. Retrived from
http://imej.wfu.edu/articles/1999/1/10/
Educause. (2006). 7 things you should know about screencasting. Retrieved from
https://net.educause.edu/ir/library/pdf/eli7012.pdf
Fancett-Stooks, D. J. (2012). The efficacy of screencasting technology in the classroom.
Retrieved from https://docushare.sunyit.edu/dsweb/Get/Document-225433/fancettstooks_efficacy_screencasting_assembled.pdf
Felder, R. M., & Henriques, E. R. (1995). Learning and teaching styles in foreign and second
language education. Foreign Language Annals, 28(1), 21–31. doi:10.1111/j.19449720.1995.tb00767.x
Fleming, N., & Baume, D. (2006). Learning styles again: VARKing up the right tree !
Educational Developments, SEDA Ltd, 7(4), 4–7.
84
Fook, C. Y., Sidhu, G. K., Nursyaidatul Kamar M. S., & Norazah A. Z. (2011). Pre-service
teachers’training in Information Communication and Technology for The ESL classrooms
in Malaysia. The Turkish Online Journal of Distance Education, 11(3), 97–108.
Fraser, A., & Maclaren, P. (2012). Patterns of instruction: Using screencasts in the teaching of
Textile Design. In Proceedings ascilite Wellington 2012 (pp. 331–332).
doi:10.1007/s10798-005-4327-y
Hall, J. K. (2000). Field dependence-independence and computer-based instruction in
geography. Doctoral Dissertation, Virginia Polytechnic Institute and State University.
Jailani M. Y., Wan Mohd Rashid W. A., & Ahmad Rizal M. (2007). Field DependenceIndependence students and animation graphic courseware based Instruction. Retrieved
from http://www.academia.edu/download/30587759/medcejournal.pdf#page=22
Jong, T. de. (2010). Cognitive load theory, educational research, and instructional design:
Some food for thought. Instructional Science, 38(2), 105–134. doi:10.1007/s11251009-9110-0
Kraft, E. (2009). Screencasts as a learning resource to enhance a quantitative business
methods course. Business Education & Accreditation, 1(1), 65–78. Retrieved from
http://www.theibfr.com/ARCHIVE/BEA-V1N1-2009.pdf#page=67
Lloyd, S. A., & Robertson, C. L. (2012). Screencast Tutorials Enhance Student Learning of
Statistics. Teaching of Psychology, 39(1), 67–71. doi:10.1177/0098628311430640
Loch, B. (2012). Screencasting for mathematics online learning–a case study of a first year
operations research course at a dual-mode Australian university. In Teaching
mathematics online: emergent technologies and methodologies (pp. 43–59). Retrieved
from http://stan.cc.swin.edu.au/~lochb/download/Loch2011.pdf
Mayer. (2009). Multimedia Learning, Second Edition. Cambridge, UK: Cambridge University
Press.
Mayer, R. E. (2005a). Cognitive theory of Multimedia learning. In The Cambridge handbook
of multimedia learning (1st ed., pp. 31–48). NY: Cambridge University Press.
Mayer, R. E. (2005b). Principles for managing essential processing in multimedia learning:
Segmenting, pretraining, and modality principles. In Mayer, R. (Ed), The Cambridge
handbook of multimedia learning (169-182), Cambridge, UK: Cambridge Unibversity
Press.
Mayer, R. E. (2010). Applying the science of learning to medical education. Medical
Education, 44(6), 543–549. doi:10.1111/j.1365-2923.2010.03624.x
Mayer, R., & Johnson, C. (2008). Revising the redundancy principle in multimedia learning.
Journal of Educational Psychology, 100(2), 380-386. doi: 10.1037/00220663.100.2.380.
Mestre, L. S. (2012). Student preference for tutorial design: A usability study. Reference
Services Review, 40(2), 258–276. doi:10.1108/00907321211228318
85
Mullamphy, D. F., Higgins, P. J., Ward, L. M., & Belward, S. R. (2010). To screencast or not to
screencast. ANZIAM, 51(1), 446–460.
Nafaidilah N. (2012). Kesan Persembahan Video Screencast Dengan Narasi Dan Video
Screencast Tanpa Narasi Terhadap Pembelajaran. Unpublished master’s thesis,
Universiti Pendidikan Sultan Idris, Tanjung Malim.
Norasmah O., & Mohd Hasril A. (2010). Different perspectives of learning styles from VARK
model. In Procedia - Social and Behavioral Sciences (Vol. 7, pp. 652–660).
doi:10.1016/j.sbspro.2010.10.088
Oehrli, J., Piacentine, J., Peters, A., & Nanamaker, B. (2011). Do screencasts really work?
Assessing student learning through instructional screencasts. In ACRL Conference, 2011
(Vol. 30, pp. 127–44). Retrieved from
http://www.ala.org/acrl/sites/ala.org.acrl/files/content/conferences/confsandpreconf
s/national/2011/papers/do_screencasts_work.pdf
Oud, J. (2009). Guidelines For Effective Online Instruction Using Multimedia Screencasts.
Reference Services Review, 37(2), 164–177. doi:10.1108/00907320910957206
Ozsvald, I. (2010). The Screencasting Handbook. London: ProCasts.
Peterson, E. (2007). Incorporating screencasts in online teaching. The International Review
of Research in Open and Distance Learning, 3(3), 3–4. Retrieved from
http://www.irrodl.org/index.php/irrodl/article/viewArticle/495
Pinder-Grover, T., Millunchick, J. M., & Bierwert, C. (2008). Work in progress - using
screencasts to enhance student learning in a large lecture Material Science and
Engineering course. 38th Annual Frontiers in Education Conference, 1, 13–14.
doi:10.1109/FIE.2008.4720446
Renumol, V. G., Janakiram, D., & Jayaprakash, S. (2010). Identification of cognitive
processes of effective and ineffective students during computer programming, 10(3), 1–
21. doi:10.1145/1821996.1821998.http
Riding, R. J., & Sadler-Smith, E. (1997). Cognitive style and learning strategies: Some
implications for training design. International Journal of Training and Development,
1(3), 199–208. doi:10.1111/1468-2419.00020
Rocha, A., & Coutinho, C. P. (2010). Screencast and vodcast: an experience in secondary
education. In Proceedings of Society for Information Technology & Teacher Education
International Conference (pp. 1043–1050). San Diego, United States: Association for the
Advancement of Computing in Education (AACE). Retrieved from
http://repositorium.sdum.uminho.pt/handle/1822/10592
Rosniah M. (2007). Mengadaptasikan gaya pembelajaran pelajar ESL : Satu kajian kes pelajar
tahun satu di UKM. GEMA Online Journal of Language Studies, 7(1), 1–32.
Udell, J. (2005). What is screencasting. Retrieved from http://www.oreilly.com/pub/au/32
Veronikas, S., & Maushak, N. (2005). Effectiveness of audio on screen captures in software
application instruction. Jurnal of Educational Multimedia and Hypermedia, 14(2), 199–
205.
86
Winterbottom, S. (2007). Virtual lecturing: Delivering lectures using screencasting and
podcasting technology. Planet, (18), 6–8. doi:10.11120/plan.2007.00180006
Witkin, H. a., Moore, C. a. C., Goodenough, D., & Cox, P. W. (1977). Field-Dependent and
Field-Independent Cognitive Styles and Their Educational Implications. Review of
Educational Research, 47(1), 1–64. doi:10.3102/00346543047001001
Yosep, Wawan Setiawan, & Waslaludin. (2012). Model pembelajaran gaya belajar VARK
dalam mata pelajaran Teknologi Informasi dan Komunikasi berbasis Multimedia
interaktif, 1–6.
Zabedah A. A., & Wah, L. L. (2005). Pencapaian kemahiran membaca pelajar-pelajar
pemulihan sekolah rendah berasaskan kaedah fonetik. In Prosiding Seminar Pendidikan
JPPG (pp. 48–51).
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Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 7
ESSENTIAL COMPONENTS IN STRUCTURING ASYNCHRONOUS
DISCUSSION FORUMS
Dr. Moanes H. TIBI
Head of Computer Science Department
Faculty of Education, Beit Berl Academic College
Kfar Saba, Israel
ABSTRACT
Online learning has been used over the past decade in most disciplines at higher
education while the asynchronous online courses are one of the more popular modes of
conducting online learning. Within the asynchronous online course, the asynchronous
discussion forum plays an important role since it can replace the face to face interaction
of the traditional classroom. Since discussions are critical in any learning process, the
question is what are the essential components of the asynchronous discussion forum that
can make asynchronous discussions more effective for learning and knowledge
construction? This paper reviews the literature regarding the main elements and
components that makes an asynchronous discussion forum more effective for knowledge
acquisition and thereby increases the quality of online learning.
Keywords: Online Learning, asynchronous discussion forums, structured discussion
forums, online collaborative learning
INTRODUCTION
The principles of constructivism emphasize social interaction as a basis for knowledge
construction. Most educators agree that interaction and discussion between students and
their instructor and among the students themselves are critical in promoting and
enhancing online learning (Anderson, 2003; Curtis & Lawson, 2001; Gokhale, 1995;
Harasim, 2002; McAlpine, 2000; Muirhead & Juwah, 2004; Palloff & Pratt, 2007; Swan,
2002). According to Walls (2005), the lack of interaction and discussion is an important
impediment to the effectiveness of online courses. The most widely used asynchronous
tool for the purpose of increasing interaction, group discussion and collaboration among
participants in online courses is the discussion forum. Discussion forums are basically
used for establishing discussions focused on the content of an online course (Dringus &
Ellis, 2004; Trevino, 2015). They also allow the construction of collaborative knowledge
since learners can work together, exchange information and ideas, and comment on each
other's work (Markel, 2001; Preece, 2000).
Researchers have reported that while online discussions can facilitate deep learning, that
does not happen spontaneously; therefore careful and ongoing instructor mediation and
support is required (Al-Shalchi, 2009; Anderson, 2008; Lall & Lumb, 2010; Lee-Baldwin,
2005; Wu & Hiltz, 2004). It has been also argued that without proper structure and
management of the discussion forum, students may not achieve the expected learning
goals (Ali & Salter, 2004; Andresen, 2009; Biesenbach-Lucas, 2004; Ioannou, Demetriou,
& Mama, 2014; Nandi, Hamilton, & Harland, 2015; Salter & Conneely, 2015; Wozniak &
Silveira, 2004).
Consequently, the question is what are the main components of an asynchronous
discussion forum, which can make discussions more effective for high levels of learning
and knowledge construction?
88
MAIN COMPONENTS OF AN EFFECTIVE ASYNCHRONOUS DISCUSSION
It is clear that the process of Interactions and discussions is a critical component of any
learning process, especially when learning is conducted online via CMC tools, such as the
learning management system "Moodle" or other environments. Research also shows that
simply forming a discussion forum, providing the technology and topics for discussion is
not enough to ensure successful and effective online discussion and collaborative learning
(Andresen, 2009; Ioannou et al., 2014; Lall & Lumb, 2010; Nandi et al., 2015; Salter &
Conneely, 2015).
Following sections describe the main elements and components that need to be within a
discussion forum in order to make discussions more effective for knowledge construction
and collaborative learning (Figure 1). These components are based on the theory of
constructivism, on pedagogical principles and on principles of group interaction and
collaboration.
Figure: 1
Main components (MOC) of an effective asynchronous discussion.
Preparatory Instructions about Individual Participation
Clear and simple directions for online discussion and setting out expectations are
important in making student to student interactivity more effective (Mayne & Wu, 2011;
Wozniak & Silveira, 2004) and in helping and motivating students to contribute to the
discussions within the discussion forum (Al-Shalchi, 2009; Ioannou et al. ,2014; Lall &
Lumb, 2010; Roper, 2007). At the beginning of an online course students should receive
clear information about how they will be evaluated and other preparatory instructions
about the purpose of the discussion forum and how to use it. This information can be
described through the following main points:
 Assessment rubric: besides the important information regarding the course
content, resources and other information, the course syllabus needs also to show
the students how they will be evaluated during the course. Giving students clear
information about how they will be assessed during the course will provide them
with extrinsic motivation which, in turn, may have a positive effect on their
performance and learning outcomes (Dennen, 2000). The assessment rubric can
consist of a set of elements such as: (1) grade weight of the participation in the
discussion forums, (2) grade weight of the individual and of the group
assignments, (3) grade weight of the examination, and (4) grade weight of the
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final group project. In more details, for each assignment in the course students
should know about the score and the evaluation criteria of the assignment.
Purpose of the discussion forum: the purpose of using the discussion forum should
be clearly explained to students at the beginning of the course. Roper (2007)
claimed that instructors who establish clear expectations about the purpose of the
discussion forum and how to use it can expect to encourage richer online dialogue.
Also Rose and Smith (2007) argued that instructors must provide the students
with clear and simple directions for online discussions that do not cause any
confusion among the students. Usually, a discussion forum in an online course is
used for enhancing learning through in-depth discussion of the learning topics
(Dringus & Ellis, 2004). Students in online courses need to be encouraged to
exchange information and ideas with each other and to post their questions about
the learning materials to the discussion forum in order to get answers and support
from other students and from the instructor. Students need also to be asked to
participate actively and consistently in the discussion forum at whatever time of
day was most convenient for them and to relate their discussions to the readings
that were set for each week. In addition, students should be informed about the
importance of the quality and not the quantity of postings sent to the discussion
forum. In principle, students have to know that an educational discussion forum is
used only for discussing the learned materials and learning activities of the course
and it is not designed for having social discussions. Students may continue to
communicate with each other through different CMC tools such as E-mail and
other web messaging tools.
Instructions about using the discussion forum: the preparatory instructions
givento the students at the beginning of the online course should also include
basic rules about how to use the discussion forum. The purpose of these rules is to
preserve the order and organization of the discussions and can be summarized in
the following main points:
o When writing a response to a given message in the discussion forum, post
it as a reply to that message so that participants will find it easy to follow
the thread of a topic.
o When introducing a new topic, question or idea to the discussion forum,
post it as a new message that makes the subject of your message clear to
all.
o When quoting, use quotation marks and include the location of the original
text.
o Avoid “yes,” “no,” or repeated responses that clutter the forum and do not
add to the discussion. Since this is an educational discussion forum, it is
important to maintain the quality of posts rather than the quantity.
Instructions about Group Collaboration
As noted by Ikpeze (2007), group collaboration allows students to become active learners
rather than passive recipients of teaching and it helps to distribute the cognitive load
among the members of a group through the exchange of ideas. Students working in small
groups tend to learn more of what is taught and retain it longer than when the same
content is presented in other instructional design (Davis, 1993; Johnson & Johnson, 1986,
2004). In order to support online group collaboration the students of the online course
can participate in two levels of discussion groups. One level is the small group discussion
forum and the other level is the central discussion forum (Figure 2).
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Small
Group
Discussion
Forum
Small
Group
Discussion
Forum
Central
Discussion
Forum
Small
Group
Discussion
Forum
Small
Group
Discussion
Forum
Figure: 2
Levels of the discussion groups.
Small Group Discussion Forum
For each small group of students, a discussion forum can be specially established in order
to support students' interaction and collaboration around the learning subjects and group
learning activities. As a part of the instructions, students should be encouraged to discuss
the learning subjects and help each other's understanding of the materials of the course
as well as to exchange information and collaborate around the group learning activities.
The participation in a small group discussion forum is allowed only for the members of
that small group and not for other students. The instructor's role in the small group
discussion forums is to facilitate students' interaction with the materials and with each
other in their knowledge constructing endeavor. This role was described in Benfield
(2002) and Mazzolini and Maddison (2007) as a more constructivist "guide on the side"
role.
Small groups of students can be constructed according to the following main
characteristics:
 Group goal: it should be clearly stated to the members of each small group that
they should work together toward the building of a learning group and try to
maximize learning for each group member. Thus, students need to be guided to
work in their groups for the purpose of sharing and exchanging information and
knowledge in order to achieve a deeper understanding of the subjects taught and
to complete the required group learning activities.
 Group dynamic: the dynamic of the interaction and collaboration between the
students of each small group discussion forum can be determined by the group
members themselves. The instructor needs not to be involved in the dynamics of
the groups and should not assign roles for the group members. The instructor's
role in this case is more to observe and motivate the participation in the small
group discussion forums, while giving guidance and support to the students
whenever they request it. MacDonell (1992), suggested that the instructor who
aims to be conscious of group dynamic should adopt a more "democratic teaching
style and be prepared to step aside to give the learner a meaningful role" (p. 169),
only intervening when necessary.
 Group structure: group members shape the structure of their group within the
general rules and norms that were explained by the instructor at the beginning of
the online course. The instructor should not be involved in shaping the patterns of
relationships and interactions that can appear within a group.
 Group size: each small group can be composed of three or four students. Davis
(1993) claimed that, in general, groups of four or five learners work best. Felder
and Brent (1994) argued that "when students work in pairs, one of them tends to
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dominate and there is usually no good mechanism for resolving disputes, and in
teams of five or more it becomes difficult to keep everyone involved in the
process" (p. 6). Rau and Heyl (1990) mentioned that in larger groups it is difficult
to ensure that all members participate. It would seem that small groups made up
of three or four students are suitable for collaboration and therefore this group
size can be used for constructing the small groups in online courses.
Group selection: the concept of collaborative learning involves groups of students
working together as a team to solve a problem or complete an assignment
(Dillenbourg & Schneider, 1995; Garfield, 1993). Collaborative groups can be
formed using different concepts, such as self-selection, random selection, or
criterion-based selection (Gokhale, 1995). In selecting collaborative groups,
Garfield (1993) noted that the instructor may allow students to self-select groups
or groups may be formed by the instructor to be either homogeneous or
heterogeneous on particular characteristics. Collaborative groups need to be
heterogeneous since students working in small heterogeneous groups learn the
subject matter content, appropriate problem-solving and critical thinking skills, as
well as skills necessary to work together collaboratively (Roberts, 2004). Felder
and Brent (1994) suggested that the "drawbacks of a group with only weak
students are obvious, but having only strong students in a group is equally
undesirable" (p. 6). They claimed that strong groups have an unfair advantage
over other groups and that the members of a strong team tend to divide up the
homework and communicate only cursorily with one another, omitting the
dynamic interactions that lead to most of the proven benefits of collaborative
learning. On the other hand, in groups with mixed knowledge levels or abilities,
the weaker students gain from seeing how better students study and approach
problems. The stronger students who teach others often find that teaching
someone else leads to their own improved understanding of the material allowing
them to gain a deeper understanding of the subject (Felder & Brent, 1994;
Garfield, 1993). Therefor small groups of students can be formatted by the
instructor to be heterogeneous in the knowledge level. This way of forming the
small group assures at least that the best students in the class do not cluster
together, leaving the weaker ones to fend for themselves. The knowledge level of
the students can be determined according to a pre-test that can be given to all
students before starting the online course. It is also possible to determine the
knowledge level of the students according to their scores in a course that students
were required to take as a prerequisite.
Central Discussion Forum
As previously mentioned, besides the discussion forums that can be constructed for small
groups of students, a central discussion forum should be also established. In the central
discussion forum, all students from all groups are requested to participate actively. The
discussions in the central discussion forum should be administered by the instructor of
the course who needs to play an active, visible part in the forum discussions keeping
them on the right track. The increased number of postings to the central discussion forum
all over the course can make it difficult for the students to find specific information.
Therefore, for each central topic in the course a new central discussion forum can be
established in order to contribute to a clear and a better organization to the whole
process.
Instructors' Role in Organizing the Discussion
The instructor can organize the content of the discussion forum through questioning,
learning activities and feedback. Following are the descriptions of these components.
 Questioning: discussion questions encourage students to explore the topic and the
assigned reading more deeply (Bender, 2003) and are a critical means for
achieving learning objectives (Benson, 2007). The instructor should created
appropriate discussion questions and activities on different levels and kinds of
knowledge (know-what, know-how, and know-why) including higher order
questions that ask students to make comparisons, suggest causes and solve given
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
problems. Bender (2003) argued that higher order questions provoke constructive
thought and open the gates for meaningful discussion. The motivation for this
approach is constructivist in nature in that it assumes that student knowledge can
be drawn out through student-student and instructor-student interaction involving
the asking and answering of questions (Anderson, 2003; Gold, 2001; Markel, 2001;
Nandi et al., 2015; Salter & Conneely, 2015; Trevino, 2015; Weimer, 2013).
Additionally, the instructor can post a list of questions and problems to be solved
and refer each question to a different student. Students are then required to
response to these questions, as well as to make critique and comments on other
students' answers, within a given period of time in order to initiate a debate
around the learned subjects and thereby promote higher levels of thinking. This
questioning activity is more appropriate if the number of students enrolled in the
course is not large. Otherwise, the instructor can repeat this kind of activity during
the course while taking each time a different group of students with a different set
of questions.
Other types of clarification and support, such as offering explanations, clarification
of students' understanding and offering suggestions that guide and improve
deeper and further discussions, should also be made. This part of the discussion
needs to continue over the entire course aiming to encourage more interaction
among the participants in order to enhance knowledge acquisition on different
levels.
Group activities: Online collaborative learning aims to provide an environment that
supports and enhances online collaboration between students in order to enhance
students’ learning processes (Kreijns, Kirschner & Jochems, 2003; Weimer, 2013).
Despite the popularity of online collaborative learning, simply putting students
together in an online learning group and asking them to work collaboratively does
not guarantee that they will engage in meaningful collaborative inquiry (An, Kim &
Kim, 2008; Biesenbach-Lucas, 2004; Johnson & Johnson, 1986, 2004).
Fortunately, there is a growing literature describing how online collaborative
learning can be implemented successfully (Achtemeir, Morris & Finnegan, 2003;
Harasim, 2002; Ioannou et al., 2014; Schrum & Hong, 2002). The key appears to
be preparation by the instructor in scheduling collaborative learning activities
throughout the experience (Hiltz, 1997) including projects for co-production
(Harasim, 2002). Hiltz and Turoff (2002) suggested that collaborative learning
activities, which are well-suited for online environments, include debates, group
projects, case study discussions, simulations, role-playing exercises, the sharing of
solutions for homework problems, and the collaborative composition of essays,
stories, and research plans. However, in reality, most online collaborative work is
usually relegated to discussion forum conversations, in which students merely
generate a dialogue with each other about the weekly readings (An et al., 2008).
Although this type of activity can clearly be of relevance, the extent of actual
collaboration is usually limited, the reason why well-designed collaborative
learning activities need to be combined with online collaborative learning.
Small group discussion forums are basically designed in order to let students work
collaboratively on group tasks and projects and thereby increase their knowledge.
Each small group can receive well designed collaborative learning activities during
the course and use its own discussion forum as a place for work in order to
accomplish these activities. Results of each small group can then be posted to the
central discussion forum in order to allow for a wide discussion around the
activities between all students from all small groups. This opportunity can open
the gate for more meaningful discussions and can contribute to a deeper
understanding of the learned subjects as well as of the principles underlying the
performance of the activities suggested by each group since group members will
be requested to defend their proposed solutions in front of the other groups. The
whole process of such activities should be observed by the instructor with
feedback and support when it is necessary
Feedback: giving feedback to the students is important since it can help them to
reflect upon what they have learned and what they still need to know (Bender,
93
2003). Mazzolini and Maddison (2007) recognized that frequent instructor
participation is often assumed to encourage students' participation. Kearsley
(2000) argued that one factor that strongly affects the amount of student
interaction and participation is the level of instructor involvement. However, the
instructor needs to maintain a balance between too little and too much
participation and should therefore determine the appropriate time to jump in
(Mazzolini & Maddison, 2007). Thus, the instructor should not response to every
student post immediately when it is not directed to him in order to give other
students the opportunity to response and comment on each other posts. This, in
turn, can motivate the students to construct meanings through interaction with
each other. However, the instructor should participate regularly in the discussion
forum giving feedback, answers, new and follow-up questions and other
comments to the students, in order to keep discussions on track and to support the
learning process.
In addition to ongoing feedback the instructor can give a positive personal
feedback for each student at least once or twice during a semester. In this
feedback students can be informed about their level of participation. Students who
did not participated enough should be requested to participate more as well as to
explain to the instructor about the reasons for their low participation. This
personal feedback aims to motivate and help the students to be more active in the
discussion forum.
CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH
Online discussions are an essential part of online courses so the adoption of
communication technologies, particularly discussion forums, will continue to grow in
online learning environments. It is clear that discussion forums can achieve high levels of
learning, but this goal cannot be reached without proper preparations, structuring and
management of the discussion and especially intensive instructor interaction with the
learners. Using structured discussion forums, which involves problem and project based
learning activities, can help in building a community of learners which allows students to
become part of a vibrant learning community, rather than an just an independent learner.
In fact, the use of structured discussion forums in online courses can be as instructor
intensive (instructor to content, instructor to student and assessment of students) as the
traditional classroom, if not more. Thus, future work should aim to design and develop
better online collaborative learning management systems or platforms that support the
sharing and construction of knowledge more easily and effectively. Additionally, these
tools should support the instructor in assessing online collaboration and knowledge
construction processes. This in turn can reduce the amount of time spent by the
instructors on assessment allowing them to invest more time in designing the online
course including the teaching and learning activities.
BIODATA and CONTACT ADDRESSES of the AUTHOR
Dr. Moanes H. TIBI holds Bachelor's and Master's degrees in
Computer Science from the Rheinische Friedrich-WilhelmsUniversität Bonn in Germany. He earned his Ph.D. from Bar-Ilan
University. Dr. Tibi has been lecturing in this field since 1995
and has served as the head of the Computer Science Department
at Beit Berl Academic College since 2012. Over the years, he has
written various articles and books, participated in national and
international Conferences. His principal fields of research and
interest include developing teaching and learning models in
online environments, and exploring the effect of information
technologies on teaching and learning among students and on society in general. Lately,
He has been taking an interest in computer science teaching programs for young people.
94
Dr. Moanes H. TIBI,
Head of Computer Science Department,
Faculty of Education, Beit Berl Academic College,
Kfar Saba, Israel.
Phone: +97297473109
Email: tibi@beitberl.ac.il
REFERENCES
Achtemeir, S.D., Morris, L.V. & Finnegan, C. L. (2003). Considerations for developing
evaluations of online courses. Journal of Asynchronous Learning, 7(1).
Ali, S., & Salter, G. (2004). The use of templates to manage on-line discussion forums.
Electronic Journal on e-Learning 2(1), 11-18.
Al-Shalchi, O. (2009). The effectiveness and development of online discussion. (Electronic
version). MERLOT Journal of Online Learning and Teaching, 5(1), 104-108.
An, H., Kim, S., & Kim, B. (2008). Teacher perspectives on online collaborative
learning: Factors perceived as facilitating and impeding successful online group
work. Contemporary Issues in Technology and Teacher Education, 8(1). Retrieved
April 25, 2014 from http://www.citejournal.org/vol8/iss4/general/article1.cfm
Anderson, T. (2003). Getting the mix right again: An updated and theoretical rationale for
interaction. The International Review of Research in Open and Distance Learning ,
4(2). Retrieved March 02, 2014 from
http://www.irrodl.org/index.php/irrodl/article/view/149/230
Anderson, T. (2008). Towards a theory of online learning. (Electronic version). In T.
Anderson (Ed.), The theory and practice of online learning (2nd ed., pp.45-74).
Edmonton, AB: Athabasca University Press.
Andresen, M. A. (2009). Asynchronous discussion forums: Success factors, outcomes,
assessments, and limitations. Educational Technology & Society, 12(1), 249-258.
Bender, T. (2003). Discussion-based online teaching to enhance student learning: Theory,
practice and assessment. Sterling, Virginia: Stylus Publishing.
Benfield, G. (2002). Designing and managing effective online discussions. Learning and
Teaching Briefing Papers Series, OCSLD Oxford Brooks University. Retrieved Mai 01,
2014 from
http://www.brookes.ac.uk/services/ocsd/2_learntch/briefing_papers/online_disc
ussion.pdf
Benson, R. (2007). How to Develop Effective Discussion Questions - Part I: Introduction
and Discussion Question Objectives. An Online Learning Magazine for University of
Maryland University College Faculty. Retrieved Mai 01, 2014 from
http://deoracle.org/online-pedagogy/classroom-communication/effectivediscussion-questions-part-one.html
Biesenbach-Lucas, S. (2004). Asynchronous web discussions in teacher training courses:
Promoting collaborative learning—or not? AACE Journal, 12(2), 155-170.
Curtis, D. D., & Lawson, M. J. (2001). Exploring collaborative online learning. (Electronic
version). JALN, 5(1), 21-34.
Davis, B. G. (1993). Collaborative learning: Group work and study teams. In B.G. Davis
(Ed.), Tools for Teaching. San Francisco: Jossy-Bass Publishers. Retrieved March 10,
2014 from the University of California at Berkeley web site:
http://teaching.berkeley.edu/bgd/collaborative.html
Dennen, V. P. (2000). Task structuring for on-line problem based learning: a case study.
Educational Technology & Society 3(3), 329-336.
Dillenbourg, P., & Schneider, D. (1995). Collaborative learning and the internet. ICCAI.
Retrieved December 17, 2014 from
http://tecfa.unige.ch/tecfa/research/CMC/colla/iccai95_1.html
95
Dringus, L. P., & Ellis, T. J. (2004). Building the SCAFFOLD for evaluating threaded
discussion forum activity: Describing and categorizing contributions . 34th
ASEE/IEEE Frontiers in Education Conference. Savannah, GA. Retrieved September
10, 2014 from http://fie.engrng.pitt.edu/fie2004/papers/1080.pdf
Felder, R. M., Brent, R. (1994). Cooperative learning in technical courses: Procedures,
pitfalls, and payoffs. National Science Foundation Division of Undergraduate
Education. Retrieved March 10, 2014 from
http://www.eric.ed.gov/PDFS/ED377038.pdf
Garfield, J. (1993). Teaching statistics using small-group cooperative learning. Journal of
Statistics Education, 1(1). Retrieved September 26, 2014 from
http://www.amstat.org/publications/jse/v1n1/garfield.html.
Gokhale, A. A. (1995). Collaborative learning enhances critical thinking. Journal of
Technology Education 7(1). Retrieved January 11, 2014 from
http://scholar.lib.vt.edu/ejournals/JTE/v7n1/gokhale.jte-v7n1.html
Gold, S. (2001). A constructivist approach to online training for online teachers. Journal of
Asynchronous Learning Networks, 5(1), 35–57.
Harasim, L. (2002). What makes online learning communities successful? The role of
collaborative learning in social and intellectual development. In C. Vrasidas & G. V
Glass, Distance Education and Distributed Learning (pp. 181-200). Charlotte, NC:
Information Age Publishing.
Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks:
Some preliminary results. Journal of Asynchronous Learning Networks, 1(2).
Hiltz, S. R., & Turoff, M., (2002). What Makes Learning Networks Effective? (Electronic
version). CACM, 45(4), 56-59.
Ikpeze, C. (2007). Small group collaboration in peer-led electronic discourse: An analysis
of group dynamics and interactions involving preservice and inservice teachers.
Journal of Technology and Teacher Education, 15(3), 383-407.
Ioannou, A., Demetriou , S. & Mama, M. (2014). Exploring Factors Influencing
Collaborative Knowledge Construction in Online Discussions: Student Facilitation
and Quality of Initial Postings. American Journal of Distance Education, 28(3), 183195.
Johnson, R. T., & Johnson, D. W. (1986). Action research: Cooperative learning in the
science classroom. Science and Children, 24(2), 31-32.
Johnson, D. W., & Johnson, R. T. (2004). Cooperation and the use of technology. In D. H.
Johansson (Ed.). (2nd ed.), Handbook of research on educational communications
and technology (pp. 785-811). Mahwah, NJ: Lawrence Erlbaum Associates.
Kearsley, G. (2000). Online Education: Learning and teaching in cyberspace. Belmont, CA:
Wadsworth Publishing.
Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social
interactions in computer-supported collaborative learning environments: A review
of the research. Computers in Human Behaviors, 19, 335-353.
Lall, V., & Lumb, R. (2010). Successful design, development and delivery of online
courses: Lessons from operations management and global leadership. Indian
Journal of Economics & Business, 9(2), 377-384.
Lee-Baldwin, J. (2005). Asynchronous discussion forums: A closer lock at the structure,
focus and group dynamics that facilitate reflective thinking. (Electronic version)
Contemporary Issues in Technology and Teacher Education, 5(1), 93-115.
MacDonell, W. (1992). The role of the teacher in the cooperative learning classroom. In C.
Kessler (Ed.), Cooperative language learning: A teacher resource book. (PP. 163174). Englewood Cliffs, NJ: Prentice Hall.
Mayne, L., & Wu, Q. (2011). Creating and measuring social presence in online graduate
nursing courses. Nursing Education Perspectives, 32(2), 110-114.
Markel, S. L. (2001). Technology and education online discussion forums: It's in the
response. Online Journal of Distance Learning Administration, 4(2). Retrieved Mai
15, 2014 from http://www.westga.edu/~distance/ojdla/summer42/markel42.hml
Mazzolini, M., Maddison, S. (2007). When to jump in: The role of the instructor in online
discussion forums. Computers & Education, 49(2), 193-213.
96
McAlpine, I. (2000). Collaborative learning online. (Electronic version). Distance
Education, 21(1), 66-80.
Muirhead, B., & Juwah, C. (2004). Interactivity in computer-mediated college and
university education: A recent review of the literature. Educational Technology &
Society, 7(1), 12-20.
Nandi, D., Hamilton, M., & Harland, J. (2015). What Factors Impact Student – Content
Interaction in Fully Online Courses. I.J. Modern Education and Computer Science, 7,
28-35.
Palloff, R., & Pratt, K. (2007). Building online learning communities: Effective strategies
for the virtual classroom. Jossey-Bass Wiley. Retrieved from Google books database
Preece, J. (2000). Online communities: Supporting sociability, designing usability.
Chichester, UK: Wiley.
Rau, W. & Heyl, B. S. (1990). Humanizing the college classroom: Collaborative learning
and social organization among students. Teaching Sociology, 18(2), 141-155.
Roberts, T. S. (Ed.) (2004). Online collaborative learning: Theory and practice. Hershey,
PA: Information Science Publishing.
Roper, A. R. (2007). How students develop online learning skills. Educause Quarterly,
30(1), 62-65.
Rose, R., & Smith, A. (2007). Online discussions. In C., Cavanaugh & R., Blomeyer (Eds.),
What works in k-12 online learning (pp. 143-160). Washington, D.C.: International
Society for Technology in Education.
Rudestam, K. E. & Schoenholtz-Read, J. (Eds.) (2010). Handbook of Online Learning.
London: Sage publications, 2nd edition. Retrieved from Google Books database.
Salter, N., P., & Conneely, M. R. (2015). Structured and unstructured discussion forums as
tools for student engagement. Computers in Human Behavior, 46(1), 18-25.
Schrum, L. & Hong, S. (2002). Dimensions and strategies for online success: Voices from
experienced educators. Journal of Asynchronous Learning Networks, 6(1), 57-67.
Swan, K. (2002). Building learning communities in online courses: the importance of
interaction (Electronic version). Education, Communication & Information, 2(1), 2349.
Walls, C.M. (2005). Some strategies for balancing economies of scale and interaction in
online/distance education courses. E-Journal of Instructional Science and
Technology (e-JIST) 8(1). Retrieved June 11, 2014 from
http://www.eric.ed.gov/PDFS/EJ850357.pdf
Weimer, M. (2013). Structuring Discussions: Online and Face-to-Face. Teaching Professor
Blog. Retrieved June 20, 2015
from http://www.facultyfocus.com/articles/teaching-professor-blog/structuringdiscussions-online-and-face-to-face/
Wozniak, H., & Silveira, S. (2004). Online discussions: Promoting effective student to
student interaction. In R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds.),
Beyond the Comfort Zone: Proceedings of the 21st ASCILITE Conference, (pp. 956960)
Wu, D. & Hiltz, S. (2004). Predicting learning from asynchronous online discussions .
Journal of Asynchronous Learning Networks, 8(2), 139-152.
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Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 9
OPEN EDUCATIONAL RESOURCES (OER): OPPORTUNITIES AND
CHALLENGES FOR INDIAN HIGHER EDUCATION
Dr. Indrajeet DUTTA
College of Teacher Education, Bhopal
Maulana Azad National Urdu University, Hyderabad, INDIA
ABSTRACT
Creation of knowledge workers holds key for success of a country. Unfortunately, many of
the countries though having chain of human resources yet are unable to transform human
resources to their advantage as they face multiple challenges like poverty, poor economy,
poor infrastructure, limited access to education and inadequate technological growth.
Fortunately, India is one of among such countries in the recent past which has improved
its position in the world forum and has taken a big stride by transforming human resource
into knowledge workers. The entire credit goes to government of India, their schemes
and most importantly the people working tirelessly in the higher education institutions.
But, the percentage is very low.The reason is higher education of India is plagued with
several challenges like poor quality of teachers, poor infrastructure, poor libraries and
poor educational resources. Unless high quality of education both in terms of
infrastructure and academic is not provided and sustained in all higher education
institutes, it will be difficult to match with global world. One way it could be done at least
in academic front is developing and disseminating quality educational material among the
institutes of higher education. National Knowledge Commission has recommended that
problems of educational material to a large extent can be reduced by Open Educational
Resources (OER) and Open Access (OA). The easy and widespread availability of high
quality educational material will change the paradigm of teaching and learning and thus
improve the quality of education. Government of India has started several innovative
programs and schemes like SHAKSHAT, NMEICT, NPTEL, OSCAR, E-grid etc. related to
developing and disseminating educational resources. The national and global level are
tremendous but it comes with many challenges specifically in a country like India which
has a diversified population.The present paper will try to focus on the opportunities and
challenges with respect to OER in Indian higher education.
Key Words: OER, higher education, challenges, opportunities.
INTRODUCTION
“Open Educational Resources (OERs) are any type of educational materials
that are in the public domain or introduced with an open license. The nature
of these open materials means that anyone can legally and freely copy, use,
adapt and re-share them. OERs range from textbooks to curricula, syllabi,
lecture notes, assignments, tests, projects, audio, video and animation.”
- UNESCO, Home Page dated 2nd October2013
Over the past two decades the electronic revolution has changed the world scene. Never
in the history, has technology influenced education so much as it is doing today. In recent
years, the rate of technological change happened in electronic medium has never been so
fast, what is used to be two decades ago. Technology has changed our world in ways
previously unimaginable. No one has ever imagined that with a click of mouse the money
can be transferred one place to other place, one can talk live face to face via
mobile(3G)across the country, one can attend conferences, workshop almost virtually.
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Educators’ tryst with technology has a long history. The influence of technology in the
learning process starts right from the time of Thomas Edison in 1922 where he predicted
that “that the motion picture is destined to revolutionize our educational system and that
in a few years it will supplant largely, if not entirely, the use of textbooks”. With the
passage of time, use of technology has dominated educational discourse especially in the
21st century. The advent of internet has brought revolution not only in the field of trade
and commerce, technology, but also in the field of education. Many people would tend to
think education as perpetually lagging behind technology; but there are numerous
instances in history where education has provoked technical innovation. The present
society is often called “information society” or “knowledge Society” as, the development
in technology has led to the widespread diffusion of information that give rise to new
opportunities for learning. At the same time, the challenge of established views and
practices regarding how teaching and learning should be organised and carried out.
Higher educational institutions have been using the Internet and other digital
technologies to develop and distribute education for several years. Yet, until recently,
much of the learning materials were locked up behind passwords within proprietary
systems, unreachable for outsiders. The open educational resource (OER) movement
break down the barriers and thus encourage to use or share content. According to the
Hewlett Foundation:
“Open Educational Resources are teaching, learning, and research
resources that reside in the public domain or have been released under an
intellectual property license that permits their free use or re-purposing by
others.
Open Educational Resources (OER) is one of the ways of sharing the resources specifically
the faculty and the content by keeping it in public domain. The vision behind creating OER
is to lower the cost of educational materials, develop innovations and improve the quality
of content and thus it can be accessed anytime, anywhere and anyplace by anyone. The
easy and widespread availability of high quality educational resources will change the
paradigm of teaching and improve the quality of education for all students. In addition,
students will have access to inaccessible information as well as the knowledge on how to
access global educational resources. UNESCO believes that universal access to high
quality education is key to the building of peace, sustainable social and economic
development, and intercultural dialogue. Open Educational Resources (OER) provide a
strategic opportunity to improve the quality of education as well as facilitate policy
dialogue, knowledge sharing and capacity building. OER started its journey in 2001, when
Massachusetts Institute of Technology (MIT), in an unprecedented move, announced the
release of nearly all its courses on the internet for free access. The term Open Educational
Resources (OER) was coined at UNESCO’s 2002 Forum on Open Courseware and
designates “teaching, learning and research materials in any medium, digital or
otherwise, that reside in the public domain or have been released under an open license
that permits no-cost access, use, adaptation and redistribution by others with no or
limited restrictions. Open licensing is built within the existing framework of intellectual
property rights as defined by relevant international conventions and respects the
authorship of the work”. Thereafter, the number of institutions offering free or open
courseware increased. With the support of the Hewlett Foundation, UNESCO created a
global OER Community wiki in 2005 to share information and work collaboratively on
issues surrounding the production and use of Open Educational Resources. Open
Educational Resources (OERs) have become significantly important in education systems
across the world. They represent the efforts of a worldwide community, empowered by
the internet, to help equalize the access to knowledge and educational opportunities.
These are teaching, learning and research resources that reside in public domain that
permits their free use or customization by others (Bissell, 2007). According to Smith and
Casserly (2006), OERs are sharable assets. Between 2005 and 2007, a large community of
interest of more than 600 members from more than half of the 192 members states of
UNESCO took part in online discussions on OERs.The National Knowledge Commission
(NKC) recommended the increase the amount of Open Educational Resources (OER) and
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Open Access (OA).On its recommendation, Indian government has started several
innovative programmes like SHAKSHAT-(an academic portal), National Mission on
Education through Information and Communication Technology (NMECIT), National
Programme on Technology enhanced Learning (NPTEL), OSCAR(Open Source Courseware
Animations Repository), E-grid(E-Grid an educational portal is a project which is
supported by MHRD at IIIT, Kerala) etc. In India, OER movement is picking up and
government has realized its strength and that’s why it is investing huge amount of money
to develop quality OER in different disciplines and in different languages. It has entrusted
various elite institutions like Indian Institute of Technology (IITs), Indian Institute of
Management (IIMs), Indian Institute of Science(IIS), Indian Institute of Information
Technology(IIIT), National Institute of Open Schooling (NIOS), Indira Gandhi National
Open University (IGNOU), National Council of Educational Research and Training(NCERT)
and many other private organizations to create and develop teaching, learning and
research materials for students, research scholars and teachers for various levels of
education. Networking of libraries of universities is one such step in this direction.
Various foreign institutions and international organizations are also spending huge
amount of money to develop and store OER in the repository for educational use.
MAJOR INNOVATIVE INITIATIVES ON OER BY INDIAN GOVERNMENT
NMECIT
National Mission on Education through Information and Communication Technology is a
centrally sponsored scheme to leverage the potential of ICT, in providing high quality
personalized and interactive knowledge modules over the internet/intranet for all kind of
learners in higher education in anytime, anywhere mode. This scheme has two major
components one content generation and other connectivity along with provision for
access devices for institutions and learners. In this project requires all the universities
and the colleges of the country are to be connected. The universities are to be connected
with National Knowledge Network (NKN) and the colleges are to be connected with
broadband connectivity. This scheme was launched on February 3, 2009 by government
of India through its Union Ministry of Human Resource development. The objectives of
the mission are:
Ø Empowering and enabling students by ensuring equity and access to education
through the use of ICT;
Ø Connecting over 400 Universities and 22,000 Colleges all over India through
high-speed data networks;
Ø Improving faculty quality by using a unique synchronous training methodology;
Ø Ensuring equity by providing access to expensive equipment to students even in
remote corners through innovative use of ICT; and
Ø Making available e-content and educational videos created by the best teachers
across all disciplines for UG and PG classes.
The Mission provides an opportunity for all the teachers and experts in the country to
pool their collective wisdom for the benefit of every Indian learner and, thereby, reducing
the digital divide and reaching out hitherto deprived sections of the society in rural/
under-developed areas of the country. Under this Mission, a proper balance between
content generations, research in critical areas relating to imparting of education and
connectivity for integrating our knowledge with the advancements in other countries is
being attempted. It is an endeavour through which MHRD is synergising the efforts taken
by the educational institutions vis. IITs, UGC, NITs, CEC, IGNOU and other higher
education institutions in the country to develop world class content and educational
applications. Senior faculty members from different universities, research institutes and
institutions of higher learning are contributing to the development of e-learning
resources, virtual labs, open source applications etc. The Mission aims to extend
computer infrastructure and connectivity to over 26000+ colleges and 2000 polytechnics
in the country including each of the department of 419 universities/deemed universities
and institutions of national importance as a part of its motto to provide connectivity up to
the last mile. Connectivity to universities and colleges is in progress and as on date, 400
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universities and nearly 26000 colleges in the country have been connected (MHRD
Report, 2014). Under NMEICT till date almost 368 universities are connected through
National Knowledge Network.
NKN
This project is running under NMEICT. The NKN is a state-of-the-art multi-gigabit panIndia network for providing a unified high speed network backbone for all knowledge
related institutions in the country. The purpose of such a knowledge network goes to the
very core of the country's quest for building quality institutions with requisite research
facilities and creating a pool of highly trained professionals. The NKN will enable
scientists, researchers and students from different backgrounds and diverse geographies
to work closely for advancing human development in critical and emerging areas. The
target users for the NKN are all institutions engaged in the generation and dissemination
of knowledge in various areas, such as research laboratories, universities and other
institutions of higher learning, including professional institutions. NKN has already
connected 1038 institutions
and
aims
to
connect
over
1500
Institutions/Organizations/Laboratories under various categories throughout the country
(Home page of NKN, 2015).
SHAKSHAT
It is a landmark initiative of the Ministry of Human Resource Development (MHRD) to
develop a One Stop Education Portal for addressing all the education and learning related
needs of students, scholars, teachers and lifelong learners. It is a free portal launched by
the Hon’ble President of India on 30th October 2006. It contains many e-repositories for
school and higher education. The portal is expected to be the main delivery platform for
the contents developed under the National Mission on Education through ICT (NMEICT).
For Mission related information and to facilitate public scrutiny, feedback and
transparency for the projects undertaken by the Mission a new website has been created.
There are more than hundred projects ongoing under the NMEICT ranging from e-content
development, access to e-resources, development of software tools etc. In its home page
there are four navigation as SAKSHAT repository, picture gallery, SAKSHAT SAARC and
what’s new. Within Sakshat repository various links are provided wherein stakeholders
can access course wise e-content being developed for under graduate, post graduate,
engineering education programme are available prepared by eminent teachers in the form
of videos, animation, recorded lectures etc. For UG courses, Consortium of Educational
Communication (CEC) has been tasked for e-content generation. In phase-I, e-content for
19 UG subjects and in phase-II e-content for 68 subjects are being generated by the CEC
in collaboration with its media centres. For 77 PG subjects, e-content generation activity
has been assigned to University Grants Commission (UGC). The process of content
creation has been initiated for 72 subjects. Under NPTEL, free online courses for
engineering education are available. Apart from it spoken tutorial, talk to teacher and
Amrita Virtual interactive E-learning World (A-VIEW) virtual classrooms are also
operating.
NPTEL
NPTEL is a joint initiative of IITs and IISc funded by this Mission provides e-learning
through online Web and Video based courses in engineering, science and humanities
streams. The Mission of NPTEL is to enhance the quality of engineering education in the
country by providing free online courseware. Over 329 courses are complete and made
available in NPTEL website. More than 990 courses in various disciplines in engineering
and science are getting generated in phase-II of NPTEL A set of 5 separate DVDs
containing ready NPTEL course material--one each in the areas of Electrical, Civil,
Computer Science, Electronics and Mechanical Engineering were distributed to the AICTE
approved Engineering Colleges during the dissemination workshop for engineering
colleges of NCR Region held on 8th Oct 2013.
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EKLAVYA
Eklavya project launched jointly by IIT, Bombay and IGNOU on 26th January, 2003 aims
at a free exchange of knowledge and ideas, by placing all the relevant academic material
in the Open Source. The project has developed an Open Source Educational Resources
Animation Repository (OSCAR) to create a repository of web-based, interactive
animations for teaching various concepts and technologies. Its e-GURU programme
provides the students with a list of relevant and challenging projects, which encourage
them to think of innovative technical solutions to various real life problems and its eOUTREACH programme produces high quality digital text, audio, video and HTML contents
of educational value for wider dissemination. The e-CONTENT programme of the project
creates open source digital contents in Indian languages through translation and new
writing on topics of relevance to education for all levels (Gani, 2010).
OSCAR
OSCAR (Open Source Courseware Animations Repository) is an initiative of IIT Bombay to
build a large repository of web based interactive animations for teaching and learning of
science and technology based concepts.
E-Grid
Launched by IIIT, Kerala and supported by the MHRD, E-Grid portal has been designed to
increase and facilitate access to education resources by the educational community and
to facilitate collaboration, sharing of knowledge and best practices to improve the quality
of education and learning. The Digital Library of India project, being coordinated by the
IIS, Bangalore, along with Carnegie Mellon University, aims at digitising the books in
India. More than 450,000 books, including those in Indian languages, have already been
digitized under this initiative out of which about 220,000 are already available free on the
So far 21 centres spanning academic institutions, social organisations, and government
agencies have partnered in creating this repository of knowledge (Gani, 2010).
OPPORTUNITIES FOR INDIAN HIGHER EDUCATION
Today society is knowledge based and it is driven by knowledge workers. It has been said
that the society which can produce or create knowledge workers in coming decades will
govern the universe. Due to large force of young human resource, world has recognised
India as the potential knowledge superpower house. We have one of the fastest and the
robust economies of the world (average growth rate is 7%).Various social indicators like
health and care, employment, infrastructure, etc. are improving at a phenomenal rate. In
the last two decade, India has achieved much more than what the world has expected.
The quality of life has improved both in rural and urban set up. The reason of this high
achievement is due to good policies and programmes started by government. Another
reason being, common man has the access to education specifically at school level. But,
the task of converting large huge human resource (16-24 years) into knowledge workers
rests on the kind and quality of tertiary education being provided to the common man. If
we look at the past decade (2001-2011) there is a phenomenal growth not only in
number of institutes of higher education, but also in numbers of students enrolled in
higher education. As per the latest figure given almost 19% of total population in the age
group of 18-23 are studying in higher education in almost 712 universities, 36,671
colleges and 11,445 stand alone educational institutions in management, technical,
medical and other professional institutes(Educational Statics at a Glance,MHRD,2014).
Though, this number is well short of what is required as per the report of the National
Knowledge Commission (2006). It is an estimate this percentage will touch to almost
30% by the end of 2020. With such a huge expansion what is required is the quantitative
and qualitative expansion of resources-infrastructural, educational, technological human
and more so economical. Government has opened the private sector and thinking on the
lines of Foreign Direct Investment (FDI) in education sector. Several important bills
related to higher education has been pending in the parliament like Foreign Education
Institution Bill, National Accreditation Regulatory Authority for Higher Educational
Institutions, Education Tribunals Bill, Higher education and Research Bill which will pave
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new way to the higher education sector. Since equity, access and quality in higher
education is the prime concern of the government, therefore government has realized
that Information and Communication Technology(ICT) sector will play a crucial role in
expanding higher education and that’s why it has launched nationwide centrally
sponsored mission called National Mission on Education through Information and
Communication Technology (NMEICT) and National Knowledge Network (NKN) through
which universities are as well as colleges of higher education will be connected. National
Knowledge Network will connect all the universities whereas along with other projects
related to education like National Programme on Technology enhanced Learning (NPTEL),
Eklavya (An open educational portal of Indian Institute of Bombay), National Repository
of Open Educational Resource (NROER), etc has been launched to not only to connect the
higher education institutes but also help the stakeholders to access the good quality
educational resources material. Therefore, OER present a range of opportunities to
institutions of higher education, teachers and learners of higher education as well as
administrators of higher education.
Unlimited Opportunities for Creating Open Education Resources
In the recent years there is rapid technological advancement both in hardware as well as
in software. We have move beyond classrooms, textbooks and face to face teaching.
Today, we have classrooms which is almost virtual and education is available in the form
of e-material i.e. education is deeply influenced by technology. Today’s learner is access
to devices like I-Pad, smart phones, tablets coupled with 3G and 4G
technologies.Learning is highly individualized and self-paced.Furthermore, the growing
capabilities of the internet (site engines) has made knowledge explosion. But
unfortunately, all this technological development has reached tofew whereas majority of
the population has been deprived of it. This has been the case with Indian higher
education also. Majority of the students who are studying in higher education are in
colleges or in state universities. These colleges and universities face severe crunch of
good teachers and good educational materials. Due to absence of both these factors
students are the worst sufferers. Teachers and technological experts (both hardware and
software professional) have unprecedented opportunitiesfor creation of the OER material.
Apart from it there is whole lot of opportunities for other professionals’ right from technopedagogic specialist, editor, e-content developer to web developer. Recently in the report
of Evaluation Committee on NMEICT it has been reported that NPTEL programme was
launched in 2003 for creation of e-content for engineering, science and management
studies. Initially it was envisage to create 990+ web and video courses for both
undergraduate and post graduate courses but till date it was only 600 web courses were
created and rest is in progress. Moreover, report also indicated that creation of e-content
in other subjects and languages is most warranted. Therefore, in these areas too lot of
scope and opportunities is there to design e-content.
Massive Teacher Empowerment
In the institutes of higher education there is growing usage of technology enabled
teaching-learning.Learners are more familiar in usage of ICT in their learning process in
comparison to teachers. Thisincreasing usage of ICT is changing the learning landscape
rapidly. In this changing paradigm, there is growing need to bridge the gap between
learners and teachers. Hence, there is a massive opportunity for the teachers to empower
themselves in terms in order to get the full benefit of ICT based education scenario.
Breaking Language Barriers
India being a country with rich-multilingual diversity, it is commonly observed that a
large percentage of population is more comfortable with their regional languages rather
than English.Presently most of the educational material which has been developed in the
English language.If we are developing the educational material only in one language it
means we are depriving majority of our students from rich educational material.
Therefore, it is important that the content in English language is also made available in
regional languages either through translation or through creation in original language so
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as to have wider impact. This provides immense opportunity for content developers to not
only develop the content in other regional languages.
Equalization of Opportunities through Outreach Programmes
Indian higher education is suffering from inequality of learning opportunities. One hand
we have group of learners who are aware of these resources and have access to all kind
of technological facilities to access these educational resources. On other hand, there is
large group of learners who neither have the awareness on the availability of free
educational resources nor access to technological devices through which they access it.
Therefore, it is indeed important through mission such as NMECIT and NKN one can
reached to the unreached and publicise the importance of OER and orient the
learnershow to utilize it for their benefits. This will help the in bridging of gaps between
learners of “have” and “have not” and hence bring both the groups at par.
Private-Initiative
In last one decade there is an appreciable increase in the participation of private
enterprises in education sector. Big corporate houses are investing huge amount of
money in education. Many corporate houses like Wipro, HCL have set up their own
universities. These corporate houses are also the leading IT sector companies of India
which have global impact. Therefore, these companies can use their resources to create
such educational materials which could be help to government institutions also.
CHALLENGES FOR HIGHER EDUCATION
This vertical expansion requires consolidation at horizontal level. But, presently higher
education is facing several challenges like quality of higher education, faculty shortage;
quality teachers, unable to keep pace with market demands, poor quality of curriculum,
poor quality of research, poor quality of teaching etc. in majority of tertiary institutes.
Recently, in a survey it was reported that many of our top institutes like IITs, IIMs not
been in the top 200 list of universities in the world ranking. The reason is the teaching
and researches in Indian universities are far below the standard of European or American
and even among some of the Asian countries. If we compare it within our countries we
will find wide disparities in terms of quality of teaching, quality of research etc. India has
only fewer numbers of creditable institutes of higher education and it benefits fewer
numbers of students. Since large force of human resource (youths) are studying in
substandard institutions, transforming them into human capital is a challenge for Indian
education system. Unfortunately, that advantage cannot be sustained unless we upgrade
our education system. One area that is in desperate need of change is our higher
education network. Networking of higher education institutes will help these institutes in
more than one way. First, quality educational resources which is being created or stored
in their repository is available free of cost. Secondly, it will improve the teaching learning
standard in the universities or colleges which are suffering from poor quality of
educational resources. Thirdly, it will also meet the paucity of teachers. Fourthly, it will
enhance the capacity of students as well as teachers. Finally, it will enable students to
compete globally.
Transforming Higher Education Institutes into E-Hub Resources
India has one of the biggest higher education systems in the world. But sorry state of
affairs is that it has only a handful of quality institutes of higher education. Most of these
are engineering, science or management institutes. The entire responsibility of creating
these OER for other institute lies in the hand of these institutes. Among these are mostly
IITs, IISc and few regional engineering colleges. One of the greatest challengeis to equip
the faculty of the higher education and other human resources involved in it with
necessary skills so that they are able to create e-resources within their institutes across
the different courses and thus in the way make each institutes a hub of OER material.
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Sustainability
The development cost of open educational resources materials is high, but the much
higher translatable, measurable rewards resulting from an expansion of the OER universe
makes it a clear case for the government to ensure its sustainability. Initially, the
government can create a grant for the generation and distribution of OER material to
students and teachers from all over the country. Private industry should be the second
major source of funding for developing OER on an ongoing basis since the industry stands
to benefit immensely from the improved quality of education. Private industry should be
offered tax credits in return for funding and developing OER content. These partnerships
with private industry will help defray the costs of development of OER material.
High Capital
One of the biggest challenges related to OER is the infrastructural development which
Indian higher education system is facing. In last one a decade huge amount of money is
invested in higher education almost. Though, government of India is already sanctioned
4612crores in XI five year plans for the project NMEICT for development of e-learning
material, installation of infrastructure, usage of space satellites, broadband connectivity
etc to connect linkages institutions of higher education, development of repository
resources like Shodhganga-an open repository of doctoral theses submitted by students
in various universities in various disciplines, and INFLIBNET-Information and Library
Network Centre, an autonomous Inter-University Centre of the University Grants
Commission (UGC) of India. It is a major National Programme initiated by the UGC in
March 1991 with its Head Quarters at Gujarat University Campus, Ahmadabad. Initially
started as a project under the IUCAA, it became an independent Inter-University Centre
in June 1996. INFLIBNET is involved in modernizing university libraries in India and
connecting them as well as information centres in the country through a nation-wide high
speed data network using the state-of-art technologies for the optimum utilization of
information. It is set out to be a major player in promoting scholarly communication
among academicians and researchers in India etc (Inflibnet, Home page, 2015). Beyond
robust connectivity for access, infrastructure considerations for sustainable educational
impact through OER must support a variety of requirements – for development and
delivery of customized materials, providing tailored learning experiences, interoperable
applications as well as evaluation and governance. Design and technology considerations
often limit the productive use and adoption of OER, rendering tools incompatible with
infrastructure, content to be trapped in repositories, and ultimately limiting adaptation
and adoption as well as sustainability. This all require huge sums of money which in itself
is challenged where the spending on higher education is on reducing trend.
Developing Network-enabled Delivery Infrastructure
A national backbone that provides high-bandwidth connections and advanced networking
capabilities is critical for reliable access and quality. Connectivity with globalnetworks
like Internet2 in the United States is also essential for the kind of collaborationand
sharing that is recommended as an important element of the educational strategy.It is
important to recognize that while the Internet and high-performance networks arelargely
seen as relevant only in the context of advanced research, they are critical
infrastructurefor educational quality and access. The government’s lead in developing
thisinfrastructure, complemented by partnerships in the private sector to provide local
andinstitutional infrastructure, will be an important determinant of progress. In
recognitionof the urgency to develop an Indian Research and Education
Network/Knowledge Network, the NKC has developed detailed recommendations
whereby each connected institution will have at least of 1Gbps connectivity. This level of
connectivitywill advance open education activities nationally, and ensure global
connectivity as well.
Open Access and Issue of Intellectual Property Rights
Open Access is a term used to describe published academic papers, books, reports, and
other periodicals that are electronically available to readers without financial or
technological barriers. But, only a small proportion of the information generated
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throughout the world is in the open access domain. Recent studies have shown that Open
Access articles are cited 25-50% more than non-Open Access articles from the same
journal and year. The researchers are benefited due to the Open Access policies as their
research work gets widely disseminated and can be read by anyone with Internet access
without any restriction. Similarly books, articles, and art forms will enjoy worldwide
patronage when available in open access domain. In India, there are a large number of
educational materials like books, journals etc are in electronic form but they are held in a
few libraries scattered across the country and their content is not widely available to the
scholars and students of our country. Open Access will drastically change the availability
of these books and the knowledge contained in these texts. This will reduce the skewed
nature of libraries in India. Open Access also help by allowing socially and economically
disadvantaged individuals to access all the information if there is a free internet
connection. But open access of the educational material also brings in the concept of
intellectual property right. Normally it has been perceived, once the educational resources
developed by the author and puts it into public domain in the form of OER, it means the
author losses the ownership of the material. This fear resulted that many of the authors
do not put their materials into OER. This is actually not so.The author retains the
ownership of the material. In fact, OER is exploring new ways of creating, distributing
and sharing educational materials. It is not become anti-copyright. Instead, itbuilds on
different kinds of open licenses. The vision behind the creation of open licenses is a space
in the internet world, a creative commons, where people can share and reuse copyright
material without fear of being sued. This requires copyright owners to agree or give
permission for their material to be shared through a generic license that gives permission
in advance. Thus; it is no way an infringement into the intellectual property rights.
Globalization
The globalization of the world’s economies is leading to increased permeability of national
educational boundaries as well as greater emphasis on the internationalization of
curricula. The internationalization of higher education seems to be a double-edged
phenomenon, inducing growingcollaboration and growing competition among countries
and among institutional providers. The OECD’s Education Policy Analysis (2006a) reports
that cross-border higher education has grown significantly over the past decades and this
is expected to continue. This growth has been driven by several interlinked forces:
greater mobility of skilled workers in an increasingly knowledge-based economy; the
drive to develop export industries and expand international collaboration in higher
education; the need to build a more educated workforce in sending countries, where
study options may be limited; the desire of students andacademics to have international
experience and promote mutual understanding; and the decline in the cost of transport
and communications. According to Education Policy Analysis, this growth has, in turn,
fuelledgreater competition for students and academics between countries and higher
education institutions. At the same time, domestic higher education systems increasingly
face international pressures and competition, under voluntary harmonization agendas
under the pressures of international comparison, manifested byquality labels, ranking
efforts and consumer choice; or owing to theincreasing frequency of partnerships and
recognition agreements. Like theolder established research universities, higher education
institutions of alltypes increasingly see themselves not simply in terms of their domestic
roleor agenda but as actors in a global market.Through greater collaboration between
higher educational institutionsaround the world and enhanced reuse of learning
materials, both in theiroriginal form or translated or otherwise adapted, the phenomenon
of OERcontributes to the globalization of higher education. At the same time itincreases
competition between institutions by making teaching content and processes within
individual institutions visible to a potentially worldwide audience. Prospective students
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can be better informed not only by studyingthe general offer from institutions but also by
viewing the curriculum andlearning materials, and sometimes videotaped lectures, of
individualdepartments.
Demography
India has one of the largest populations in the age group of 18-25 years andincreasingly
concerned about the impact of demographic factors on higher education. With the
increasing participations of this age group in higher education, the demand for variety of
courses, more flexible delivery and tailor-made programmes are required. Moreover,
longer working lives with more career changes, and the possible growing enrolment of
learners beyond the age group of 25 years in higher education, might indeed be a
transformative force in the medium run. Most countries need to increase participation in
higher education, but higher education institutions generally have not so far been able to
meet this challenge. OER initiatives might serve higher educational institutions as
vehicles for outreach to non-traditional groups of students, widening participation in
higher education, and provide learning opportunities for those unable to use more
traditional offerings or who are not parts of the traditional groups of higher education
entrants. Such initiatives can bridge the gap between non-formal, informal and formal
learning. At the same time OER can be used by professionals for in-service training and
home study by older people, opening new lifelong learning strategies as a means of
tackling the challenges of aging societies.
CONCLUSION
OER movement is just started in India. The creation of open education materials in
various disciplines by the experts from the institutions of repute will help the teachers to
access these materials at the click of the mouse which will help them in classroom
teaching. Moreover, it is more beneficial for the students as they will get the opportunity
to hear the lectures from the teachers of international repute. Open educational resources
which are generally made web based are interactive in nature therefore it helps the
learner to interact didactically with the teachers and thus clarify the doubts
instantaneously. Moreover, it could be accessed from any remote area as it requires
internet connectivity. The additional benefit is that one can register oneself in these open
education resources portals for the different online courses (subject to availability of
course) and thus get additional certificates. It will be boon to those educational
institutions which lacks good library resources. Through NMEICT and NKN colleges and
universities can connect themselves and avail the facilities for their students and
teachers. The effort and support from government side is visible by launching NMEICT
and NKN along with allocating a substantial budget for it. Initiative from private
enterprises and corporate houses is what needed by the government to support and
sustained its efforts of making India hub of open educational resources. The biggest
challenge for the academic fraternity is to create open educational material for diverse
demographical population in diverse vernacular languages as majority of our students
belong to different vernacular medium. Another challenge is to make different
stakeholders aware of the different open educational resources available to them free of
cost. Last the learners and teachers need to utilize it to the optimum level. Since,
globalization has transform the education and its system therefore, it is indeed necessary
that we teachers collaborate, adapt and adopt, translate the educational resources with
the external world as it is very difficult to create all kind of materials. In all, one can say
success of OER movement means success for higher education.
119
BIODATA and CONTACT ADDRESSES of the AUTHOR
Dr. Indrajeet DUTTA is working as an Assistant Professor in the
constituent college of the Maulana Azad National Urdu University,
Hyderabad, India. He has just been awarded Doctoral Degree on
Educational Psychology from Guru Gobind Singh Indraprastha
University, New Delhi India on Parenting Style of Indian parents. He
has almost ten years of experience in teaching to undergraduate and
post graduate students. His area of research and interest is open
and distance learning; ICT based pedagogical practices in school and
teacher education, social psychology of parenting practices of
parents and education evaluation at school, higher and teacher education.
Assist. Prof. Dr. Indrajeet DUTTA
Maulana Azad National Urdu University,
School of Education & Training
College of Teacher Education
MHK ITC Campus
Bhopal-462001
Phone: +917552744515
Email: indraneet@gmail.com, phd.dutta@gmail.com
REFERENCES
Atkins,D.E., Brown,J.S., & Hammond, A.L. (2007) A Review of the Open Educational
Resources (OER) Movement: Achievements, Challenges, and New Opportunities,
California, USA.
Bisell,A.(2007). Some guiding principles for legal and technical interoperability in OER. In
proceedings of Open Education, Localizing and learning, Logan, Utah State
University, USA.
COL and UNESCO (2011) Guidelines for Open Educational Resources (OER) in Higher
Education, Commonwealth of learning, Canada.
COL and UNESCO (2012) Report on Survey on Governments’ Open Educational Resources
(OER) Policies, Commonwealth of learning, Canada
downloads/documents/wg_open_course.pdf.
Gani, A.(2010).Mapping open educational resources for access and equity in higher
education in India. Paper presented in Pan-Conference Commonwealth Forum of
Open Learning 24th-28th November Kochi, India. Retrieved
http://oldwebsite.col.org/pcf6/fp/zIN1110.doc.
Inflibnet (2015) Home page of Inflibnet Retrieved from http://www.inflibnet.ac.in/ on
22nd July 2015.
Kanwar, A. and Trumbic, S. U. (Ed.)(2011) A Basic Guide to Open Educational Resources
Commonwealth of Learning, Canada
MHRD (2011) Report of the Evaluation committee on NMEICT, GOI, New Delhi.
MHRD (2014) NMEICT: Document on Achievement
http://www.sakshat.ac.in/Document/Achievements.pdf
NKC (2007). Report of the working group on open access and open educational resources.
New Delhi, India: National Knowledge Commission, Government of India. Retrieved
October, 2013, from http://knowledgecommission.gov.in/
NKN (2015). Home page of National Knowledge Network
http://nkn.in/connectedinstitutes-nmeict.php Retrieved on 22nd July 2015
OECD (2006a). Education Policy Analysis: Focus on Higher Education Edition, OECD, Paris
OECD (2007) Giving Knowledge for Free: The emergence of open educational resources.
OECD publication, Paris, France
120
Smith, M.S. & Casserly, C.M. (2006).The promise of open educational resources. Change,
38(5).8-17.
UNESCO (2012). What are Open Educational Resources?
http://www.unesco.org/new/en/communication-and-information/access-toknowledge/open-educational-resources/what-are-open-educational-resourcesoers/
Vijay Kumar, M.S. (2009). Open Educational Resources in India’s national Development,
Open Learning: The Journal of Open, Distance and e-Learning, 24:1, 77-84 DOI:
10.1080/02680510802627860
William and Flora Hewlett Foundation. (2008). Open educational resources (OER) –
makinghigh quality educational content and tools freely available on the web.
Retrieved October,2013, from
http://www.hewlett.org/Programs/Education/OER/openEdResources.htm
121
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 8
CRITICAL COMPONENTS OF ONLINE LEARNING READINESS
AND THEIR RELATIONSHIPS WITH LEARNER ACHIEVEMENT
Dr. Harun CIGDEM
Department of Computer Technologies
Land Forces Non-Commissioned Officer Vocational College, Balikesir, TURKEY
Dr. Mustafa OZTURK
School of Foreign Languages
Hacettepe University, Ankara, TURKEY
ABSTRACT
This study aimed to examine the relationship between certain factors of online learning
readiness and learners’ end-of-course achievements. The study was conducted at a twoyear post-secondary Turkish military school within the scope of the course titled
Computer Literacy, which was designed and implemented in a blended way. The data
were collected from 155 post-secondary military students through an online
questionnaire. Three sub-scales of Hung et al.’s Online Learning Readiness Scale were
used to collect the data during the first two weeks of the course. Descriptive and
inferential statistics, such as Pearson correlation coefficients and linear regression
analyses were performed to analyze the data. The descriptive results of the study
indicated that students’ motivation for online learning was higher than both their
computer/Internet self-efficacy and their orientations to self-directed learning. The
inferential results revealed that the students’ end-of-course grades had significantly
positive relationships with their computer/Internet self-efficacy and self-directed
learning orientations. Finally, the students’ self-direction towards online learning
appeared to be the strongest predictor of their achievements within the course; whereas
computer/Internet self-efficacy and motivation for learning did not predict the learner
achievement significantly.
Keywords: Online learning readiness, learner achievement, blended learning, computer
literacy
INTRODUCTION
In this day and age, technology affects almost every aspect of our lives and continually
change the way we learn, teach, and work on the information. With the help of the
Internet technologies, e-learning or online learning that makes new instructional
practices convenient for students, which was not possible in traditional classroom
settings due to time and space constraints, has become a noteworthy method (Cigdem,
2015). Online learning can be described as an action of delivering course materials such
as lecture notes, videos, exams, and slides to the learners by devices using Internet
technology, although “e-learning”, and “distance education” have also been used.
Demiray (2011) has emphasized the importance of online learning and online learning
tools, for making better learning and teaching in higher education. Online learning has
become more and more popular as online technologies and improved educational
pedagogy have supplied educators with constantly enlarging opportunities to build high
quality, efficient, rigorous, and valuable instructive access to constantly increasing
numbers of students. There are many existing online learning tools such as Atutor,
Blackboard, Claroline, CanvasLMS and MOODLE that offer many educational tools.
98
MOODLE (Modular Object-Oriented Dynamic Learning Environment) is one of the learning
management systems (LMSs) which have been used most. MOODLE serves as a free open
source platform for LMSs and offers an environment that allows sharing course content to
support conventional instruction. It is flexible since it can be accessed anywhere as long
as student has a personal device with Internet connection such as smart phone, tablet or
computer. In a flexible learning environment, the content of a course is easier to access
for learners and learners are able to study at their own speed via the Web, and this plays
an important role on their achievement (Chen et al., 2009; Liao, 2007). As a result,
educational institutions have assigned great efforts to develop blended learning
environments, which stand for the use of key features belonging to face to face and
online instructional methods for learners to share and obtain information (Akkoyunlu &
Soylu, 2008; Cigdem & Topcu, 2013; Lynch & Dembo, 2004; Osguthorpe & Graham 2003;
Owston, York, & Murtha, 2013).
Many studies have found the positive results of blended learning, and also a positive
impact of blended learning on student achievement has been shown (Lee, Yoon, & Lee
2009). Escobar-Rodriguez and Mongo-Lozano (2012) claimed that learning–teaching
process has become better by using MOODLE. Martín-Blas and Serrano-Fernández (2009)
used MOODLE to prepare more interesting activities thus making the learning process
friendlier and more interesting for their learners. In the use of MOODLE there are some
difficulties appeared as a result of the lack of capabilities and skills for its use, that can
reduce these results or even turn down them (Paragia, Paragin, Jipa, Savu, & Dumitrescu,
2011). Online learning and MOODLE have been established in a number of faculties. Still,
many universities fail to take benefits of such attempts and face difficulties in achieving
effective strategies, as well as in delivery, efficiency, and acceptance of online courses
(Park, 2009; Wang & Wang, 2009).. Learners are considered to be the most important
elements of online learning processes (Aydin & Tasci, 2005). Learner needs and skills
should be central while designing and developing blended courses (Sahin & Shelley,
2008), when a course become unsuccesful to meet learner hopes and needs it may result
with reducing levels of learner participation and motivation (Bradford, 2011) However,
one of the key factors shaping the effectiveness of online learning environments is
readiness factor (Artino, 2009; Galy, Downey & Johnson, 2011; Kruger-Ross & Waters,
2013). Yukselturk (2009) found that online learning readiness was one of the strongest
predictors of satisfaction for students in online courses. Online learning readiness plays a
significant role to encourage learners to be involved in online learning activities. So
readiness for online learning readiness can be perceived as a crucial factor to be taken
into account in any development of online learning environments (Ilgaz & Gulbahar,
2015).
Although research studies in online learning has risen significantly in the last years, much
is still unknown regarding factors influencing learner achievement in these online
learning environments utilizing LMSs. There are many unanswered questions. One of
these questions is which the critical factors affect learner achievement in online mode of
blended courses. In this sense, learners’ online learning readiness along with online
contents must be reviewed carefully in order to improve the quality of those attempts,
and schools are to consider improving learners’ readiness to use online learning systems
more efficiently (Cigdem & Yildirim, 2014; Wang et al. 2009).
BACKGROUND OF THE STUDY
Online learning readiness can be described in three major features: choices for online
learning as opposed to face-to-face learning instructions; competence and confidence in
using the technological tools; and ability to learn seperately (Tang & Lim, 2013).
According to Guglielmino and Guglielmino (2003), online learning readiness can be
estimated by evaluating a user’s competency in using technological tools (Schreurs,
Sammour, & Ehlers, 2008). Within this framework, McVay (2001) focused on student
behaviors and attitudes to determine readiness, and Hung et al. (2010) added some new
99
dimensions to the readiness concept such as computer/Internet self-efficacy, learner
control, motivation for learning, online communication self-efficacy and self-directed
learning.
Bearing in mind that the learners’ pre-existing readiness for online learning might
influence their cognitions and actions regarding the online mode of blended learning
environments, it is essential to understand their online learning readiness. Therefore, in
this research, learners’ online learning readiness and its effects on blended learning
outcomes were investigated. Within this framework, these three major components were
discussed and examined in this study: self-directed learning, computer/Internet selfefficacy, and motivation for learning.
To start with the first one, Knowles (1975) defines self-directed learning as “a process in
which individuals take the initiative, with or without the help of others, in diagnosing
their learning needs, formulating goals, identifying human and material resources,
choosing and implementing appropriate learning strategies, and evaluating learning
outcomes” (p. 18). In this regard, self-directed learning has been characterized as an
active and constructive process by which learners make plans and set objectives prior to
learning, monitor their own progress during learning, and subsequently self-evaluate
their achievement after learning (Pintrich, 2000; Zimmerman, 2008). According to
Zimmerman (2002) self-regulated learning helps students learn more effectively and
performance better. Together with the increase in online enrollments, academicians have
started to show an interest in students’ academic motivation and self-regulation in online
courses (Artino, 2008; Dabbagh & Kitsantas, 2004). Students should manage time and
information effectively to be more active and responsible in their learning, complete work
on time, and participate in class works in online learning environments (Hung et al.,
2010).
Researchers have reached a consensus that students’ self-directed learning readiness has
been positively associated with students’ readiness for online study (Demir Kaymak &
Horzum, 2013) and achievement in online courses (Artino, 2008; 2009a; Lee, Shen, &
Tsai, 2008; Liaw & Huang, 2013; Paechter, Maier & Macher, 2010; Pintrich, 2000;
Puzziferro, 2008; Wang, Shannon & Ross, 2013; Yukselturk & Bulut, 2007). There are also
studies disconfirming the significant relationship between academic achievement and
self-regulation (Cigdem, 2015; Ergul, 2004).
As for the second component, motivation for learning encompasses learners’ all kinds of
movements towards and engagements with learning activities. As Wolters (2010)
clarifies, the primary factor that facilitates students’ persistence in their academic tasks is
their motivational beliefs. Motivated learners are attributed to have low latency and high
perseverance about task engagement (Artino & Stephens, 2009), and therefore, their
motivational orientation towards a task has significant influences on their performances
(Hung et al. 2010) and facilitate their efforts to get higher grades, awards, or prizes
(Baeten, et al. 2010; Hung et al. 2010; Saadé, He, & Kira 2007). Considering this chain,
learners’ motivational beliefs and self-regulatory behaviors would be related to the
nature of an online course and how that course relates to them personally (Artino,
2009b). With the rising of online modes of learning, educators and researchers have come
to figure out that self-regulated and highly-motivated learners are most likely to be
successful in blended learning. Since online learning appears as a sort of studentcentered environment, highly-motivated students possibly achieve better outcomes
(Baeten, Kyndt, Struyven, & Dochy, 2010).
The last component, self-efficacy is defined as “people’s judgments of their capabilities to
organize and execute courses of action required to attain designated types of
performances” (Bandura 1986, p. 391). In this context, users’ beliefs about their abilities
to use a technological tool to accomplish a specific task is known to be computer selfefficacy (Compeau & Higgins, 1995), which operates at two distinct levels: general
computing level and specific application level (Yi & Hwang, 2003) such as the Internet
100
use. It is claimed that task-specific self-efficacy might be used as a reliable indicator
predicting the task performance (Bandura 1986; Zimmerman 2000). That is why selfefficacy is critical to be identified before starting to implement a new technology.
Learners with higher self-efficacy towards learning through online courses are usually
considered to be more motivated, more persistent and better achievers in such courses
(Ergul, 2004; Linnenbrink & Pintrich, 2002; Lynch & Dembo, 2004). Moreover, learners
with lower self-efficacy are thought to hold negative perceptions related to requested
tasks, consider the tasks not as challenging but threatening and feel confused or even
lost when they meet new technologies (Simsek, 2011).
Technical skills including computers and the Internet have a connection with learners’
achievement and performance in online learning environments (Hung et al., 2010).
Although, learners’ self-efficacy regarding online learning is claimed to be a key predictor
of their achievement (Cigdem, 2015), some conflicting research indicated that selfefficacy of online technologies was either a poor predictor of success in online courses
(DeTure, 2004) or was not correlated with achievement at all (Puzziferro, 2008).
Nevertheless, a number of studies emphasized the role of self-efficacy in online learning
achievements. For instance, Joo, Bong, and Choi (2000) examined the relationship
between self-efficacy and learners’ achievement in a web-based instruction and found
that technological self-efficacy is a significant variable that determining learners’
achievement in distance education. Similarly, Wang and Newlin (2002) concluded that
performance in an online course can be predicted from self-efficacy for online
technologies. In Lynch and Dembo’s (2004) study, self-efficacy, among other factors, was
one of two main predictors of learners’ performance in a blended learning course. In
another study, Bell and Akroyd (2006) found that learners’ self-efficacy was one of the
primary predictors of achievement.
It is important to determine the factors that affect achievement of learners at blended
learning environment. Few studies exist in the literature about the influences of online
learning readiness and possible factors that influence the outputs of online learning
(Keramati, Afshari-Mofrad & Kamrani, 2011). Blended Computer Literacy course
achievement is based on students’ performances. Therefore, this study is conducted to
determine the relationship of online learning readiness factors and learners’ achievement
in blended Computer Literacy course that using MOODLE LMS.
Putting all the critical components portrayed above together, this study aimed to answer
the following research questions:
 What are military vocational college students’ perceptions about the following
dimensions of online learning readiness: (a) computer/internet self-efficacy, (b)
self-directed learning, and (c) motivation for learning?
 Is there any significant correlation between learner achievement and the three
dimensions (computer/internet self-efficacy, self-directed learning, and
motivation for learning)?
 Can learner achievement be predicted from computer/internet self-efficacy, selfdirected learning, and motivation for learning in a blended Computer Literacy
course?
METHODOLOGY
Research Context
This study was conducted at a two-year post-secondary Turkish military school within the
scope of the course titled Computer Literacy, which was designed and implemented in a
blended way. Course materials were deployed over the intranet on MOODLE.
Videos related to word processing software and spreadsheet were produced by the
lecturer. Students were able to review the videos at anytime and anywhere within the
college campus. The course lasted 15 weeks each of which included a 100-minute face-toface session. In each face-to-face session, the content of the week was presented to the
101
students and the students were left to practice word processing and spreadsheet
activities in computer laboratories. Students were allowed to read the content, download
the resources such as lecture notes, videos, slides and journal papers, and follow the
instructions to complete activities of the week at anytime they want. Screenshot example
of the course website is displayed in Figure 1.
Figure: 1
A Screenshot of Computer Literacy Website
Participants
As one of the researchers works as an instructor who gives the Computer Literacy course
in the research context, convenient sampling strategy was adopted and 155 postsecondary military students were included as the participants of the study. All of the
participants were male staying in the college campus as it was a military school. 60% of
them were studying at the department of Electronics and Communication Technologies
and the rest (40%) at the department of Automotive Technologies. A great majority of
the participants graduated from vocational high schools (n=126), and the others from
general high schools (n=29). Finally, most of the participants did not have a prior
experience on web-based education (n=120), while the remains had (n=35). As the study
was carried out in a military school with male students, the applicability and
generalizability of its findings are limited (see Table 1 for the demographic information of
the participants).
Table: 1
Demographics
Background
Dimensions
Academic program
n
(%)
Automotive Technologies
Electronics and Communication
Technologies
61
39.4
94
60.6
Type of High School
Vocational High School
General School (non-vocational)
126
29
81.3
18.7
Owning a computer
Yes
No
121
34
78.1
21.9
Web-based education
experience
Yes
No
35
120
21.9
78.1
Groups
102
Data Collection Tools
The data were collected through an online questionnaire consisting of two sections: (a)
items to gather demographic information about the participants and (b) items aimed to
measure the participants’ online learning readiness. The second section included items
adopted from Hung et al.’s (2010) Online Learning Readiness Scale (OLRS) which was
translated into Turkish by Yurdugul and Alsancak Sarıkaya (2013). Meaningful work on
developing and testing online learning readiness scales has been done. Hung et al. (2010)
declared a belief that McVay’s (2000) questionnaire was without an emphasis on selfdirected learning, motivation for learning, and learner control. So, Hung et al. (2010)
advanced their version of the OLRS to include these factors and other factors of computer
and Internet self-efficacy and online communication self-efficacy. They tested the
internal consistency and construct validity as well as confirming the factor structure. All
factors displayed adequate reliability and discriminant validity.
Although the original scale included five dimensions (computer/Internet self-efficacy,
self-directed learning, motivation for learning, learner control, and online communication
self-efficacy), the first three dimensions were used in the current study with the purpose
of measuring military students’ readiness for online learning. In order to ensure that the
items constitute a reliable scale, reliability analysis was performed for each dimension
and Cronbach’s alpha levels ranged from .75 to .80 (see Table 2 for the alpha values).
Table: 2
Cronbach’s Alpha Coefficients
Hung et al.
Items
(2010)
Dimensions
Computer/Internet
efficacy
Self-directed learning
Motivation for learning
self-
Current Study
3
0.736
0.797
5
4
0.871
0.843
0.750
0.771
RESULTS
In relation to the first research question investigating whether the participants are ready
for online learning, the findings obtained from descriptive analyses indicated that
students’ motivation for learning ( M=4.15) is higher than both their computer selfefficacy (M=3.55) and their self-directed learning inclinations (M=3.82) (see Table 3).
Table: 3
Descriptive Results
Dimensions
Computer/Internet self-efficacy
Self-directed learning
Motivation for learning
N
M
SD
155
155
155
3.55
3.82
4.15
1.0
.67
.69
In order to see the correlations between the factors of online learning readiness and the
participants’ course grades, Pearson correlation coefficients were conducted. At this
point, a p value of less than .008 (.05 / 6 = .008) was required for significance by using
the Bonferroni approach to control Type I error across the 6 correlations. The
correlational analyses revealed that the participants’ course grades had significantly
positive relationships with computer/Internet self-efficacy, r(153)=.21, p<.001, and selfdirected learning, r(153)=.32, p<.001. These findings could mean that as the
participants’ self-efficacy and self-directed learning orientations tend to increase, their
achievements in a blended course would also increase (see Table 4).
103
Table: 4
Correlations between Course Grades and Online Readiness Factors
Variable
Dimensions
Course Grades
Computer/Internet self-efficacy
Self-Directed Learning
Motivation For Learning
Pearson
Corr.
Sig.
(2-tailed)
N
.21
.32
.16
.011
. 001
. 050
155
155
155
As for the third research question, regression analysis conducted to see whether learner
achievement was predicted from the factors of online learning readiness put forward a
significant result indicating that course grades, which means meeting all the
requirements of the course and achieving the tests, were predicted only from the
following factor of online learning readiness: self-directed learning, R2=.104, F(3,151)
=5.873, p<.005 (see Table 5). The findings could mean that it is hard to explain learner
achievement through computer/Internet self-efficacy and motivation for learning as they
did not seem to be significant predictors of the Computer Literacy course grades of
military students. However, students’ inclinations towards self-directed learning
happened to significantly contribute to students’ course grades in the Computer Literacy
course, as it appeared as the most important predictor in the current study.
Table: 5
Regression Analysis Results
Variables
Computer/Internet self-efficacy
Self-directed learning
Motivation for learning
B
SE
β
t
p
1.408
8.030
-.280
1.625
2.711
2.432
.075
.287
-.010
.867
2.963
-.115
.388
.004
.908
DISCUSSION AND CONCLUSION
On the basis of the descriptive results of the study, military students seemed to be highly
motivated to learn thorough a blended design, as they rated the items pertaining to
motivation for learning more positively than the other two dimensions. This finding was
consistent with the related literature (Cigdem & Yildirim, 2014; Hung et al. 2010; Tang &
Lim, 2013) putting forward that students are ready for online learning processes.
However, in Hung et al.’s study (2010), the highest ratings were given by the participants
to the dimension of computer/Internet self-efficacy. In the current study, it was seen
that the participants could carry out their own study plan and have expectations from
their learning to some extend. Additionally, they could comfortably use the Internet as
well as online learning software. They also seemed to be confident in performing the
basic functions of office programs.
In order to design effective blended learning environments, it is crucial to examine what
would assist students’ learning and achievement as well as the characteristics of
successful learners (Yukselturk & Bulut, 2007). With the purpose of investigating what
factors of online learning readiness are able to predict learner achievement in a blended
computer literacy course, three dimensions were inquired within the scope this study:
self-efficacy, self-directed learning, and motivation factors.
Looking into the correlational analyses between the factors of online learning readiness
and learner achievement, it was seen that computer literacy course grades were
104
significantly and positively correlated with self-efficacy and self-directed learning factors.
As new generations of online learning technologies, such as videos, podcasts, and online
quizzes enter educational environments, being ready to use them for learning purposes
becomes a valuable skill because it means students can try different tools, and choose
which ones fit their needs best.
The results of regression analysis revealed that learner’s self-direction was the strongest
significant predictor of achievement in the Computer Literacy course. This point is similar
to the findings of Artino (2008; 2009), Lee, Shen, and Tsai (2008), Liaw and Huang
(2013), Paechter et al. (2010), Pintrich (2000), Puzziferro (2008), Wang, Shannon, and
Ross (2013), and Yukselturk and Bulut (2007). In this regard, students with higher levels
of self-direction towards the online mode of a blended learning course tend to have better
learning achievements. There are also studies (Cigdem, 2015; Ergul, 2004) contradicting
with this point as they did not claim learners’ self-direction as an important predictor of
achievement. As a suggestion, learners might improve self-directed learning skills,
especially for online mode of blended learning environment. It is also recommended that
learners need full support towards the use of LMS and manage their time for the LMS
participation.
Another striking point derived from the regression analysis is that self-efficacy and was
not a significant predictor of learners’ achievement. This finding justifies DeTure’s (2004)
and Puzziferro’s (2008) studies. As computer and the Internet technologies have been
upgraded over time, problems related to the use of such technologies seem to be
declining. Because of the continuing spread of technology usage across the educational
spectrum, today’s students enter colleges with a greater computer experience than their
predecessors. This point might be explained through such developments. At the first
weeks of the online learning process, learners should have known to how online learning
environment suitable their needs and also, they should have learnt what properties it has.
In addition to previous statements, LMS should be well performed and have friendlier use.
Also, the network technology is highly important if we implement such systems. If LMS
server has a breakdown, this will cause a problem to learner participation in online mode
of blended class. This issue will diminish learner motivation on online learning
participation. Hence, it will have a direct impact on learner’ achievement. Therefore, for
future research it should be discussed on usability of LMS and how to improve the
implementation of current system in higher education.
BIODATA and CONTACT ADDRESSES of the AUTHORS
Dr. Harun CIGDEM holds a bachelor’s degree in Computer Education
and Instructional Technologies and a master’s degree in Educational
Sciences from Uludag University. He received his PhD in Computer
Education and Instructional Technologies from Anadolu University in
2012. He is the administrator of Course Portal of Non-Commisioned
Officer Vocational College. He teaches operating systems, computer
networks, and system and network administration courses in the
college. His research interests involve instructional design, elearning, e-assessment and self-regulation.
Harun CIGDEM, Ph.D.
Turkis Land Forces Noncommissioned Officer School
Department of Computer Technologies
Cayirhisar, Balıkesir, TURKEY
Phone: +902662212350; +90 533 315 16 00
Email: hcigdem@gmail.com
105
Dr. Mustafa OZTURK holds a bachelor’s degree in Foreign Language
Education and a master’s degree in Educational Sciences from Middle
East Technical University. In 2007, he completed a non-degree postgraduate study in Learning, Learning Environments and Educational
Systems in University of Turku, Finland. He received his PhD in
Curriculum and Instruction from Middle East Technical University in
2014. He is currently conducting a postdoctoral research at Columbia
University Teachers College. His research interests lie in the areas of
curriculum studies, teacher education, language teaching, instructional
design, e-learning, and education for sustainable development.
Mustafa OZTURK, Ph.D.
Hacettepe University, School of Foreign Languages, Department of Basic English
Beytepe Campus, Cankaya, Ankara, TURKEY
Phone: +903122978085
Fax: +903122992158
Email: mustafaozturk@hacettepe.edu.tr
REFERENCES
Akkoyunlu, B., & Soylu, M. Y. (2008). A study of student's perceptions in a blended
learning environment based on different learning styles. Educational Technology &
Society, 11 (1), 183-193.
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality:
Predicting satisfaction with online training. Journal of Computer Assisted Learning,
24, 260−270
Artino, A. R. (2009a). Online learning: Are subjective perceptions of instructional context
related to academic success? Internet and Higher Education, 12, 117-125.
Artino, A.R. (2009b). Think, feel, act: motivational and emotional influences on military
students’ online academic success. J Comput High Educ
Artino, A. R., Jr., & Stephens, J. M. (2009). Beyond grades in online learning: Adaptive
profiles of academic self-regulation among Naval Academy undergraduates. Journal
of Advanced Academics, 20(4), 568-601.
Aydin, C. H. & Tasci, D. (2005). Measuring readiness for e-Learning: Reflections from an
emerging country. Educational Technology & Society, 8 (4), 244-257.
Baeten, M., Kyndt, E., Struyven, K. & Dochy, F. (2010). Using student-centred learning
environments to stimulate deep approaches to learning: factors encouraging or
discouraging their effectiveness. Educational Research Review, 5(3), 243–260.
Bandura, A. (1986). Social foundations of thought and action; a social cognitive theory .
Prentice Hall. Eaglewood Cliffs. NJ.
Bell, P. D., & Akroyd, D. (2006). Can factors related to self-regulated learning predict
learning achievement in undergraduate asynchronous Web-based courses?
International Journal of Instructional Technology and Distance Learning, 3 (10), 516.
Bradford, G. R. (2011). A relationship study of student satisfaction with learning online
and cognitive load: Initial results. Internet and Higher Education, 14(4), 217–226.
Chen, S. W., Stocker, J., Wang, R. H., Chung, Y. C. & Chen, M. F. (2009). Evaluation of selfregulatory online learning in a blended course for post-registration nursing students
in Taiwan. Nurse Education Today, 29 (2009), 704–709.
Cigdem, H. (2015). How does self-regulation affect computer-programming achievement
in a blended context? Contemporary Educational Technology, 6 (1), 19-37
106
Cigdem, H. & Topcu, A. (2013). Students’ perception of e-learning in the technical
vocational school. Science Journal of Turkish Military Academy, 23(2), 1-19.
Cigdem, H. & Yildirim, O.G. (2014). Effects of students’ characteristics on online learning
readiness: a vocational college example. Turkish Online Journal of Distance
Education-TOJDE, 15(3), 80-93.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a
measure initial test. MIS Quarterly, 19(2), 189–211.
Dabbagh, N., & Kitsantas, A. (2004). Supporting self-regulation in student-centered webbased learning environments. International Journal on E-Learning, 3(1), 40–47.
Demir Kaymak, Z.& Horzum, M. B. (2013). Relationship between online learning readiness
and structure and interaction of online learning students. Educational Sciences:
Theory and Practice 13 (3), 1792–1797.
Demiray, U. (2011). Distance education and eLearning practices: In Turkey and Eastern
countries. eLearning Papers, No. 24, April. Retrieved from
http://www.openeducationeuropa.eu/hu/download/file/fid/22301
DeTure, M. (2004). Cognitive style and self-efficacy: Predicting student success in online
distance education. American Journal of Distance Education, 18(1), 21-38.
Ergul , H. (2004). Relationship between student characteristics and academic
achievement in distance education and application on students of Anadolu
University. Turkish Online Journal of Distance Education-TOJDE, 5(2).
Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology
by business administration students. Computers & Education, 58, 1085–1093.
Galy, E., Downey, C., & Jhonson, J. (2011). The effect of using e-learning tools in online
and campus-based classrooms on student performance. Journal of Information
Technology Education, 10, 209-230.
Guglielmino, P. & Guglielmino, L. (2003). Are your learners ready for e-learning? In G.
Piskurich (Ed.), The AMA handbook of e-learning. New York: American Management
Association.
Hung, M., Chou, C., Chen, C. & Own, Z. (2010). Learner readiness for online learning:
Scale development and student perceptions. Computers & Education, 55, 1080–
1090.
Ilgaz, H. & Gulbahar, Y. (2015). A Snapshot of Online Learners: e-Readiness, eSatisfaction and Expectations. International Review of Research in Open and
Distributed Learning, 16 (2), 171-187.
Joo, Y., M. Bong, and H. Choi. 2000. Self-efficacy for self-regulated learning, academic
self-efficacy, and Internet self-efficacy in Web-based instruction. Educational
Technology Research and Development 48 (2), 5–17.
Keramati, A., Afshari-Mofrad, M. & Kamrani, A. (2011). The role of readiness factors in elearning outcomes: An empirical study. Computers & Education, 57(3), 1919-1929.
Knowles, M. (1975). Self-directed learning: A guide for learners and teachers. New York:
Association Press.
Kruger-Ross, M.J. & Waters, R.D. (2013). Predicting online learning success: Applying the
situational theory of publics to the virtual classroom. Computers & Education, 53,
761–774.
Lee, B. C., J. O. Yoon, & I. Lee. 2009. ‘‘Learners’ Acceptance of E-Learning in South Korea:
Theories and Results.’’ Computers and Education 53: 13201329.
Lee, T.H., Shen, P.D., & Tsai, C.W. (2010). Enhance students’ computing skills via
webmediated self-regulated learning with feedback in blended environment.
International Journal of Technology and Human Interaction, 6(1), 15–32.
107
Liao, Y. K. C. (2007). Effects of computer-assisted instruction on students’ achievement in
Taiwan: a meta-analysis. Computers & Education 48, 216–233.
Liaw, S. S. & Huang, H.M. (2013). Perceived satisfaction, perceived usefulness and
interactive learning environments as predictors to self-regulation in e-learning
environments. Computers & Education 60 (2013), 14-24.
Linnenbrink, E. A. & Pintrich, P. R. (2002). Motivation as an enabler for academic success.
The School Psychology Review 31(3), 313 – 327.
Lynch, R. & Dembo, M. (2004). Online learning in a blended learning context.
International Review of Research in Open and Distance Learning, 5(2), Retrieved
February 25, 2014 from
http://www.irrodl.org/index.php/irrodl/article/view/189/271
Martín-Blas, T., & Serrano-Fernández, A. (2009). The role of new technologies in the
learning process: Moodle as a teaching tool in Physics. Computers & Education, 52,
35–44.
McVay, M. (2001). How to be a successful distance learning student: Learning on the
Internet. New York: Prentice Hall.
Osguthorpe, R. T., & Graham, C. R. (2003). Blended learning systems: Definitions and
directions. Quarterly Review of Distance Education, 4(3), 227–234.
Owston, R., York, D., & Murtha, S. (2013). Student perceptions and achievement in a
university blended learning strategic initiative. Internet and Higher Education, 18,
38-46.
Paechter, M., Maier, B., & Macher, D. (2010). Students' expectations of and experiences in
e-learning: Their relation to learning achievements and course satisfaction.
Computers & Education, 54(1), 222–229.
Paragia, F., Paragin, S., Jipa, A., Savu, T., & Dumitrescu, A. (2011). The benefits of using
MOODLE in teacher training in Romania. Procedia Social and Behavioural Sciences,
15, 1135–1139.
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding
university students’ behavioral intention to use e-learning. Educational Technology
& Society, 12(3), 150–162.
Pintrich, P. R. (2000). A motivational science perspective on the role of student
motivation in learning and teaching contexts. Journal of Educational Psychology, 95,
667–686.
Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as
predictors of final grade and satisfaction in college-level online courses. American
Journal of Distance Education, 22(2), 72-89.
Saadé, R. G., He, X. & Kira, D. (2007). Exploring dimensions to online learning. Computers
in Human Behavior, 23(4), 1721–1739.
Sahin, I., & Shelley, M. (2008). Considering students’ perceptions: The distance education
student satisfaction model. Educational Technology & Society, 11(3), 216–223.
Schreurs, J., Sammour, G. & Ehlers, U. (2008). E-learning Readiness Analysis (ERA): an ehealth case study of e-learning Readiness. Int. J. Knowledge and Learning, 4 (5),
496-508.
Simsek, A. (2011). The relationship between computer anxiety and computer selfefficacy. Contemporary Educational Technology, 2(3), 177-187.
Tang, S. F. & Lim, C. L. (2013). Undergraduate students’ readiness in e-learning: a study
at the business school in a Malaysian private university. International Journal of
Management & Information Technology, 4 (2). 198-204.
108
Wang, A.T. & Newlin, M.H. (2002). Online lectures: Benefits for the virtual classroom. THE
Journal, 29, 17-22.
Wang, C., Shannon, D., & Ross, M. (2013). Students' Characteristics, Self-Regulated
Learning, Technology, Self-Efficacy, and Course Outcomes in Online Learning.
Distance Education, 34(3), 302-323.
Wang, W.-T. & Wang, C.-C. (2009). An empirical study of instructor adoption of webbased
learning systems. Computers & Education, 53, 761–774.
Wang, Q., Zhu, Z., Chen, L. & Yan, H. (2009). E-Learning in China. Campus-Wide
Information Systems, 26, 47–61.
Wolters, C. A. (2010). Self-regulated learning and the 21st century competencies.
Retrieved from:
http://www.hewlett.org/uploads/Self_Regulated_Learning__21st_Century_Compe
tencies.pdf
Yi, M., & Hwang, Y. (2003). Predicting the use of web-based information systems: Selfefficacy, enjoyment, learning goal orientation, and the technology acceptance
model. International Journal of Human-Computer Studies, 59, 431–449.
Yukselturk, E. & Bulut, S. (2007). Predictors for Student Success in an Online Course.
Educational Technology & Society, 10(2), 71-83.
Yurdugül, H. & Alsancak Sarıkaya, D. (2013). The scale of online learning readiness: a
study of validity and reliability. Education and Science, 38 (169), 391-406
Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary
Educational Psychology, 25, 82–91.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into
Practice, 41(2), 64–70.
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: historical
background, methodological developments, and future prospects. American
Educational Research Journal, 45 (1), 166–183
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Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2
Book Review 1
BOOK REVIEW
E-LEARNING PARADIGMS AND APPLICATIONS
Agent-Based Approach
Edited by Mirjana Ivanovic and Lakhmi C. Jain
Res. Assist. Hakan ALTINPULLUK
Department of Distance Education
Open Education Faculty
Anadolu University, Eskisehir, TURKEY
ISBN
978-3-642-41964-5 (Hardcover)
978-3-642-41965-2 (eBook)
Publication Date
2014
Publication Formats
e-Book (PDF) and Hardcover
Publisher
Springer
E-learning involves the use of digital technology
applications in learning and teaching processes, and grows
out of an interdisciplinary field, in which are contained a
variety different approaches and components. Since the
field of e-learning requires the use of high-level technology,
it is very much affected by technological developments.
Software agents are computer systems that have features
such as autonomy, reactivity, intentionality and
interactivity. The integration of software agents into elearning mediums strengthens e-learning systems and
allows for higher quality learning outcomes.
In this book, “E-Learning Paradigms and Applications:
Agent-based Approach”, which is the 528th volume of the
“Studies in Computational Intelligence” series, the focus is
on an agent-based approach, and shifts in e-learning
paradigms and innovative applications. Editorship of the
book has been jointly assumed by Mirjana Ivanovic´ from
the Department of Mathematics and Informatics at the
University of Novi Sad and Lakhmi C. Jain of the Faculty of Education, Science, Technology
and Mathematics at the University of Canberra. The book contains 9 chapters and 273
pages. In each chapter, e-learning applications are associated with different software
agents. The chapters reflect on the e-learning fields of robotics, artificial intelligence,
game-based systems, fuzzy-logic, mobile learning, augmented reality, virtual reality,
virtual learning environments, collaborative learning, grid services, pedagogical interface
agents, the importance of quality and fit-to-purpose open educational resources, new e-
122 assessment approaches in e-learning, and emotional agents. The applicability of innovative
ideas to e-learning systems is discussed in general throughout the book. The book argues
that educational practices supported by software agents improve the learning process and
produce positive learning outcomes.
In the first chapter of the book a system called RoboNewbie is introduced, which is a
product of artificial intelligence. Being different from other Robotics experiments, the
authors outline the RoboNewbie experiments to be lacking in danger, independent of any
special hardware, low cost and easy to understand. Since there are certain requirements
involved in making real robots, simulated virtual robots were used. The constructed
framework was used in e-learning environments and tested in different conditions and with
different participants. In this way the usability of e-learning systems integrated with
artificial intelligence and the field of robotics is proven. The RoboNewbie project can be
considered an impressive example of how (particularly simulated) humanoid robots will
enrich and strengthen e-learning environments.
In the 2nd chapter intelligent agents are designed and game-based modules are used for elearning purposes. It is claimed that intelligent agents and fuzzy logic are the most
important components for e-learning environments, and a game-based learning system is
built on these two foundations. The authors mention that this work, which is related to
intelligent agent models that are developed and used for adaptive game-based learning
and virtual learning environments, will be applied in learning management systems such
as Moodle. At the end of the study, it is observed that, according to the data gathered in a
Computer Science Course, game-based modules can be effective in e-learning processes.
In the 3rd chapter, based on the idea that e-learning could be a solution to protecting cultural
heritage, the authors introduce a mobile augmented reality-based e-learning system, which is
supported by social media integration. It is emphasized that when software agents are
integrated with artificial intelligence, some intelligent educational applications will be created,
and particularly narrative tools, digital storytelling and virtual reality applications are examples
of complex applications produced by software agents. In this chapter, in addition to software
agents, other components of the Agent-Based Learning Paradigm are elaborated in detail. In
this study, in which artificial intelligence elements are integrated with software agents, it is
concluded that software agents are effective in the development, application and assessment of
e-learning tools.
In the 4th chapter problems in inter-university collaboration and cooperation are emphasized,
and the virtual learning environment ITC-Euromaster (ITCEM) is introduced. In this study, which
was prepared as a case study, the objective is to enhance cooperation between ITCEM and
distributed students, and instructors living in different nations and continents, and to develop
effective e-learning environments.
In the 5th chapter, based on the notion that e-learning services should be scalable, flexible and
secured, Grid environments are introduced with the aim that geographically dispersed users
utilize their resources in a dynamic, distributed, and heterogeneous way. Within this context,
an agent-based e-learning framework for Grid services has been developed.
In the 6th chapter it is asserted that pedagogical interface agents could solve the problem of
deficiency in computer literacy, seen as one of the biggest problems in developing countries.
The authors applied pedagogical interface agents to adult learners to improve their computer
usage skills and reached the conclusion that, compared to traditional teaching methods, the use
of interface agents are more effective from the perspective of knowledge, attitude and
aspiration.
The 7th chapter discusses the importance of open educational resources and open courseware
for instructors and learners. It then underlines that learning materials in these resources should
123 be appropriate to requirements and should be of high quality. However, acknowledging that this
process is difficult, a system called MASECO has been developed. As a multi-agent system,
MASECO allows for the assessment and classification of educational materials, and provides
instructors and learners with high quality educational materials which are appropriate to
requirements. In addition to introducing MASECO the authors emphasize the importance of
quality assurance with regard to educational resources.
In the 8th chapter the authors concentrate on adaptive testing and an innovative assessment
approach in online learning. The adaptive testing in the developed online learning tool contains
some software agents and defines different behavioral patterns. The study presents clues
regarding how e-assessment systems will be constructed and how e-testing will be implemented
in e-learning systems.
In the 9th and final chapter, research is presented about how emotional agents are used in elearning environments. The author laments the difficulty of the group decision-making process,
and discusses personality, emotions and mood agents that are important in group-wide
decision-making processes. The author then tackles patience and experience as constituents in
emotional agents. The study offers an example of how emotional agents are used in e-learning.
E-learning is a field which can be used with many different technologies and which contains
many components. This book presents a variety of innovations in traditional learning methods,
and concentrates on new applications and paradigm shifts in regards to the field of e-learning,
all of which enrich current learning environments. The authors share their results and
experiences, obtained by the integration of software agents and e-learning tools. All the
chapters in the book have been prepared on the basis of an agent-based approach, but each
offers a different perspective. Different experiences and perspectives enhance the value of the
book, and provide a diversity of opinions. This book, which is grounded on discussion of how elearning systems can be made more effective and stronger via software agents, will be a highly
useful reference source, particularly for those who work or who want to work in the fields of
Computer Science, Open and Distance Education, and Educational Technology. Due to the
multidisciplinary nature of e-learning, this book has the potential to appeal to many different
audiences, including postgraduate students, instructors and researchers, in a diverse range of
fields.
BIODATA and CONTACT ADRESSES of the AUTHOR
Hakan ALTINPULLUK is a Research Assistant in Distance Education at
the College of Open Education of Anadolu University, Turkey. He
undertook undergraduate studies in the field of Computer Education
and Instructional Technologies (CEIT) between the years of 20052009 at Anadolu University. Also, he is currently a PhD candidate in the
Department of Distance Education at Anadolu University. Hakan
Altınpulluk continues to work in the field of Open and Distance
Learning, Augmented Reality, Mobile Learning, Massive Open Online
Courses, Personal Learning Environments, and E-Learning Systems.
Hakan ALTINPULLUK
Open Education Faculty,
Anadolu University, 26470 Eskisehir, TURKEY
Phone: +90 222 335 0580 #2432
E-mail: hakanaltinpulluk@anadolu.edu.tr
REFERENCES
Ivanovic, M., & Jain, L. C. (Eds.). (2014). E-learning paradigms and applications: Agentbased approach. Springer.
124 Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2
Book Review 2
BOOK REVIEW
EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS
Edited by Alejandro Pena-Ayala
Res. Assist. Aylin OZTURK
Department of Distance Education
Open Education Faculty
Anadolu University, Eskisehir, TURKEY
ISBN
978-3-319-02737-1 (Hardcover)
978-3-319-02738-8 (e-Book)
Publication Date
2014
Publication Formats
Hardcover and e-Book (PDF)
Publisher
Springer International Publishing
INTRODUCTION
Educational Data Mining (EDM) is a developing field based
on data mining techniques. EDM emerged as a combination
of areas such as machine learning, statistics, computer
science, education, cognitive science, and psychometry.
EDM focuses on learner characteristics, behaviors,
academic achievements, the process of learning,
educational functionalities, domain knowledge content,
assessments, and applications. Educational data mining is
defined by Baker (2010) as ‘‘an emerging discipline,
concerned with developing methods for exploring the
unique types of data that come from educational settings,
and using those methods to better understand students,
and the settings which they learn in’’. EDM is concerned
with improving the learning process and environment.
In this book, entitled “Educational Data Mining: Applications and Trends” and edited by
Peña-Ayala, computer-based learning environments such as e-Learning, LMS and MOOCs
are mainly considered. This book includes four parts and sixteen chapters that are prepared
with contributions of experts in different fields. In the first part of this book, EDM is
explained with a conceptual view. In the second part, applications of student modeling are
examined. In the third part, studies in the field of assessment are discussed. In the last
part, new trends in EDM field such as text mining and social network analysis are
mentioned.
125
This book is important in terms of explaining the theoretical base and sample applications
of EDM and leading new studies. In this book review, topics discussed in each section are
summarized and the importance of the book for researchers has attempted to highlight.,
Part 1: Profile
With a conceptual view of the EDM, as described in this section, it is indicated that valuable
information about learning process can be obtained by analyzing the raw data produced in
the educational systems. In e-learning systems by using DM techniques, new and different
paths can be found in the solution of learning problems, and also learner behaviors and
performance can be predicted.
The first section of the book consists of three chapters. In the first chapter, bibliographic
review of the studies conducted in EDM field is made. It is indicated that prediction and
clustering techniques are usually used in this field. In the second chapter, preprocessing of
educational data is examined. Main tasks and issues in the preprocessing of educational
data are explained with Moodle data. It is emphasized that preprocessing is one of the most
important phases for EDM. In this chapter, steps of preprocessing are explained, but in
addition, it is stated that there is no formula for this process. The third chapter illustrates
that EDM can support government policies for enhancing education. For this reason, an
application that includes EDM for enhancing learning quality performed in Mexico is
explained.
Part 2: Student Modeling
Student Modeling is one of the most important applications, especially for Computer-Based
Educational Systems. With Student Modeling, learning environments can be designed
according to learners’ needs and expectations. This part consists five chapters which are
focused on developing systems for identifying learners and estimate their performance
automatically with machine learning, especially in intelligent tutoring systems and
adaptive learning environments. Learner attributes such as learner characteristics,
behaviors, learning styles, educational experiences, personality, academic achievements,
learning system usage data, and assessment results are used for the development of these
systems. It is aimed to assist tutors and to increase the quality of education, learners’
satisfaction and achievement with these systems. It is emphasized that estimating
performance is especially important for determining at-risk students in the first years and
for retention of those students. It is stated that student models can be used in all learning
environments. However, using them especially in e-learning systems in which learners and
instructors are not in the same place can be more effective. In the fourth chapter,
knowledge discovery processes and development of the Student Knowledge Discovery
Software which is created with the determination of learner features has been explained.
Student performance is modeled using data mining techniques. In the fifth chapter,
automatic learner modeling is proposed towards detecting personality of the players with
data mining techniques in educational games. It is emphasized that determining learner
behaviors are important in order to develop user adaptable systems. In the sixth chapter,
it has tried to predict learners’ performance using the Multi-Channel Decision Fusion. In
the seventh chapter, the model which is developed in the study entitled “Predicting Student
Performance from Combined Data Sources” is tested in Open University (OU) modules. In
this chapter, it is emphasized that virtual learning environment activities are beneficial data
sources for predicting learner outcomes and it has been demonstrated that different
modules require different methods. In the eighth chapter, the accuracy of the learners’
answers by following their eye movements has been tried to estimate by using random
forest. It is indicated that estimates can be made, especially in e-learning systems,
intelligent tutoring systems, and online quizzes by using learners’ eye movements and
mouse clicks.
126
Part 3: Assessment
This section which consists of four chapters is focused on techniques that can be used in
the evaluation process. In the assessment process, learners’ domain knowledge
acquisition, skills development, and achieved outcomes are taken into account. In addition
to these, it is underlined that reflection, inquiring, and sentiments are significant for
computer-based educational systems. In the ninth chapter, a coherence analyzer is
designed to be used in an Intelligent Tutoring System. With this kind of work, learners can
evaluate their drafts early and simplify the reviewing process of the instructor. The tenth
chapter offers an approach to create test automatically. In this chapter, a model has been
developed by using EDM techniques to estimate the difficulty of the items in the computerbased tests. In the eleventh chapter, an instrument has been developed to support
instructors’ understanding of learner activities and visualize them. In the study, new
techniques for augmenting substantial pedagogical software have been developed. In the
twelfth chapter, a new approach to find the most dependent test items in learner response
data has been proposed. It is highlighted that students’ response data can be used to
identify what is learned by learners and it can also be used to discover the relationship
between the test items. These data can be used effectively in the development of the test.
Part 4: Trends
This part which consists of five chapters includes new applications in the field of EDM. In
particular, text mining and social network analysis (SNA) applications are described. In the
thirteenth chapter, evaluation of learners’ productions with text mining is described. The
ReaderBench software is used for this evaluation. The authors stated that text mining
techniques based on advanced natural language processing and machine learning
algorithms. Text mining software allow users for cohesion-based assessment, reading
strategies identification and textual complexity evaluation and to make a positive
contribution to evaluation process of instructors. In the fourteenth chapter, learners’
comments are evaluated by using statistical methods and text mining techniques. This kind
of studies can be used particularly for revealing views of learners in online learning
environments and MOOCs which have a high number of learners. In the fifteenth chapter,
an application for the use of SNA and data mining in the field of education was conducted.
Social network analysis becomes necessary in conjunction with the proliferation of the use
of social networks in educational environments. Learner interaction in e-learning
environments can be understood by using SNA methods. SNA is the methodical study that
examines relationships occurs in the connected actors from a social point of view. In the
sixteenth chapter, it is indicated that at-risk learners can be identified by analyzing users’
interaction data collected from LMS and MOOC platforms and thus learning processes can
be supported and developed. In this chapter it is stated that EDM and Learning Analytics
(LA) is not very far from each other; however, at the same time, it is emphasized that they
are different from each other. In EDM; prediction, classification, clustering, and association
methods are used for the purpose of answering questions about educational practice. On
the other hand, LA focuses on data collection, measurement, and reporting by analyzing.
This book which consists of four parts will be a valuable source of interest to researchers,
practitioners, academicians, and learners who aim to have information on the EDM field, to
learn current practices related to the EDM and to see the trends in this area.
127
BIODATA and CONTACT ADDRESSES of the AUTHOR
Aylin OZTURK is currently working as a Research Assistant in the
Department of Distance Education, Open Education Faculty at Anadolu
University, Turkey. She graduated from Primary Education Mathematics
Teaching Department and Computer Education and Instructional
Technology Department of Eskisehir Osmangazi University. OZTURK
had her master’s degree in Distance Education Department at Anadolu
University and currently she is a PhD candidate at the same university
in Department of Distance Education. Her research interests are open
and distance education, online learning, educational data mining, personal learning
environments, adaptive learning, information and communication technologies, learning
analytics, and differentiated instructional design.
Research Assistant Aylin OZTURK
Open Education Faculty,
Anadolu University, 26470 Eskisehir, TURKEY
Phone: +90 (222) 335 0580 ext:2772
E-mail: aylin_ozturk@anadolu.edu.tr
REFERENCES
Pena-Ayala, A. (Ed.) (2014). Educational Data Mining: Applications and Trends (Vol. 524).
Springer.
Baker, R. S. J. D. (2010). Data mining for education. In McGaw, B., Peterson, P., Baker, E.
(Eds.) International Encyclopedia of Education (3rd edition), 7, 112-118. Oxford, UK:
Elsevier.
128