Volume 18, Issue 2 - National College Learning Center Association

Michael Frizell
TLAR Journal Editor
Bear Claw Center for Learning & Writing
Meyer Library 112
Missouri State University
901 South National Avenue
The Learning Assistance Review
Journal of the National College Learning Center Association
ISSN 1087-0059 | Volume 18 | Number 2 | Fall 2013
PAI D
About The Learning Assistance Review
The Learning Assistance Review
The Learning Assistance Review
Editor
Director, Student Learning Services
Bear CLAW (Center for Learning and Writing)
Missouri State University
Meyer Library, Room 112
901 South National Avenue
Managing Editor
Dean of Liberal Arts
Burlington County College
2
ALLISON ARMSTRONG
KIMBERLY BETHEA
ROSEANNA ALMAEE
BARBARA BEKIS
NANCY BROWN
SARA CICCIA
JUDITH SCHEIN COHEN
JASON COTTRELL
ALAN CRAIG
JULIAN M. DAVIS
ANGELA DEANGELO
ANDREW DELOHERY
NICOLE DIEDERICH
JOAN DILLON
DEBRA MCLELLAN FETNER
SHEILAGH GRILLS
SARAH HENDERSON
JAMILAH N. JONES
KATY LEE KEMP
LOREN KLEINMAN
MICHAEL KRUEGER
CHRIS LACKEY
ELENA LITVINOVA
GEORGINE LOACKER
MARCY MARINELLI
GERALDINE MARTIN
SAUNDRA MCGUIRE
CARON MELBLOM-NISHIOKA
KELLY A. NORTON
DANIEL J. PÉREZ
JENNIFER PIPPEN
WALTER POETZING
DAVID REEDY
CHRISTINE REICHERT
JOSHUA REID
LOGAN ROGERSVILLE
CAROL SEVERINO
KATHLEEN SHEPHERD
NORMAN STAHL
JAN TAYLOR
JACK TRAMMELL
JACK TRUSCHEL
BETH VANRHEENEN
DOMINIC J. VOGE
CLAIRE ELLEN WEINSTEIN
JAIMIE YOUNG
Editorial Board
LOGAN-ROGERSVILLE SCHOOLS
UNIVERSITY OF MARYLAND
DARTON COLLEGE
UNIVERSITY OF MEMPHIS
LOURDES COLLEGE, RETIRED
UNIVERSITY OF ILLINOIS AT CHICAGO
VIRGINIA COMMONWEALTH UNIVERSITY
GEORGIA PERIMETER COLLEGE
UNIVERSITY OF THE INCARNATE WORD
UNIVERSITY OF TOLEDO
QUINNIPIAC UNIVERSITY
THE UNIVERSITY OF FINDLAY
BLOOMSBURG UNIVERSITY, RETIRED
COLLEGE OF CHARLESTON
BRANDON UNIVERSITY
MESA COMMUNITY COLLEGE
NORTHWEST STATE COMMUNITY COLLEGE
UNIVERSITY OF NORTH TEXAS HEALTH SCIENCE
BERKELEY COLLEGE
MISSOURI STATE UNIVERSITY
ILLINOIS STATE UNIVERSITY
BLOOMSBURG UNIVERSITY
ALVERNO COLLEGE
UNIVERSITY OF MARYLAND
WEST CHESTER UNIVERSITY
LOUISIANA STATE UNIVERSITY
CAL STATE UNIVERSITY DOMINGUEZ HILLS
HIGH POINT UNIVERSITY
UT-BROWNSVILLE AND TX SOUTHMOST COLLEGE
NORTH CENTRAL COLLEGE
OHIO DOMINICAN UNIVERSITY
COLUMBUS STATE COMMUNITY COLLEGE
UNIVERSITY OF TOLEDO HSC
ILLINOIS STATE UNIVERSITY
OZARKS TECHNICAL COMMUNITY COLLEGE
UNIVERSITY OF IOWA
MONROE COUNTY COMMUNITY COLLEGE
NORTHERN ILLINOIS UNIVERSITY
MARYVILLE COLLEGE
R-MC
EAST STROUDSBURG UNIVERSITY
ROCHESTER COLLEGE
UC BERKELEY
UNIVERSITY OF TEXAS AT AUSTIN
OZARKS TECHNICAL COMMUNITY COLLEGE
Contents
Letter from the Editor
5
Georg Simmel’s Spatial Sociology and Tutoring Centers as Cultural Spaces
Topic Management in Tutoring Conversation
H
Tutor Use by Student-Athletes: An Exploratory Analysis
and Study Session Design
Math Beliefs: Theory-Framed and Data-Driven Student Success
Second-Year
Membership Application
4
Letter from the Editor
a
her
6
TLAR
Georg Simmel’s Spatial Sociology and
Tutoring Centers as Cultural Spaces
University of Cinncinati
Abstract
the generation of culture
For more information contact:
-
8
The Challenge of Student Culture
a
10
Georg Simmel’s Sociology of Space
Philosophy of Money
within
12
qualitatively
here
there,
today
me
tomorrow.
you,
Applications of Simmel’s Sociology as it Relates to Tutoring Centers
own
professor’s
14
Conclusion
References
Journal of Developmental Education, 33(3),
Journal of College Student Psychotherapy,
18(3),
Noise from the writing center.
Journal of Classical
Sociology, 10(1),
Business
Communication Quarterly, 62(2),
Journal of Higher Education, 82(1),
Research in Higher Education, 41(6),
The Writing Center Director’s Resource Book
Fragments of modernity: Theories of modernity in the work of Simmel,
Kracauer, and Benjamin.
Theory, Culture & Society, 11(1),
The center will hold: Critical perspectives on writing center scholarship
New Directions For Higher Education, (109),
16
Research
in Higher Education, 36(5),
Theory, Culture & Society, 8(3),
Peabody Journal of Education (0161956X), 80(4),
Theory in Action, 4(2),
Academy of Educational Leadership Journal, 15(2),
Community
College Review, 39(2),
Journal of Higher Education, 74(3),
Journal of
Basic Writing (CUNY), 28(2),
Simmel on culture
Theory of Culture & Society, 24(7),
The Writing Center Director’s Resource Book
New Directions for Higher Education, (109),
Topic Management in
Tutoring Conversations
Abstract
For more information contact:
|
18
ö
Applying Conversation Analysis to
the Study of Tutoring Conversations
Learning and Metacognitive Strategies
Analysis of Topic Management in the Tutoring Conversation
20
Figure 1. Outline of Topics Discussed in Toni and Amy’s Tutoring Conversation.
Greetings
A.
Discomfort with being recorded
II.
Philosophy paper
A.
Books on reserve in library
B.
Developing a thesis
C.
Review of two books
1.
Course objectives
a.
Procrastination
b.
How to avoid procrastination
(i)
Tutor will send student reminder text
(ii)
Immediate plan for finishing paper
(iii)
Resident Assistant will review paper
(iv)
Plan for next paper
(v)
Tutor will send student reminder text
(vi)
Spring Break dates
2.
Not having books delayed start of paper
a.
Buying books online
(i)
Tutor’s experience with buying books online
III.
Speech class
A.
Recitation of speech
B.
Speech test – review of exam questions
1.
Unprepared – student had not reviewed
IV.
Brother’s court date
A.
Brother’s jobs to pay off court fees
B.
Other family members who had been in jail
V.
Note taking style
VI.
Assessment of study session
VII.
Note taking style – outlining, dating notes
A.
Notes as verification of attendance in class
B.
Color coding the highlighting of notes
VIII.
Plans for the evening
A.
Painting garbage cans for fundraiser
B.
Studying and writing paper
C.
Tutor will send student a reminder text message
IX.
Assessment of study session
X.
Good-bye sequence
I.
Example 1
15
16
17
18
19
TM:
AM:
TM:
AM:
Alright, so we’re doin’ philosophy and speech today, right?
mm-hm
Alright, so, which one do you want to start with, philosophy or
speech.
Ummm, well philosophy I have a paper due on Friday …
22
Example 2
43
44
45
AM:
TM:
AM:
Yeah, people desire freedom but limit themselves.
ok. So:o what’s the book about.
.hh the second book is abou:t (.) how:
Example 3
85
86
87
AM:
TM:
AM:
… And they made it mental.
Allright so how did the two books (.) like (.) connect.
They- (.) that’s a good question. Um they connect (.)
wants
Shading into Subtopics: Asking Questions
Example 4
164
165
166
167
168
169
170
171
172
173
AM:
TM:
((clears
AM:
TM:
sure
heh. An’ I haven’t- I haven’t started it, I don’t even have an
introduction or anything. I have a thesis and that’s it.
Ok, so (.) for this- oh excuse me ((cough)) mm-mm
throat)) ok, so (.) for this paper obviously the
procrastination thing wa:s kind of a big thing,
[right?
[mmmmmm-hmmmmm
Ok. So what are you gonna do for the next paper to make
that (.) you get it in time and that you (.) can get it done.
AM:
Ahh. For the next paper I am going to make sure number
one …
24
Example 5
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
TM:
AM:
-
-
TM:
AM:
TM:
AM:
TM:
AM:
TM:
AM:
TM:
AM:
::
TM:
AM:
TM:
AM:
-
Example 6
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
TM:
AM:
TM:
AM:
TM:
AM:
TM:
AM:
TM:
AM:
TM:
((laughs)) Ahem. Okay. “Which of the following is not one of
the five canons of rhetoric. A delivery. B (.) body language. C
(.) style. D (.) memory. E (.) arrangement.”
(2.0)
And what's the question again?
“Which of the following is not one of the five canons of
rhetoric?”
Wha’ does rhetoric mean?
Rhetoric
Wha’s rhetoric
(2.0)
Um: (3.0) mm: how do you define rhetoric? How- How would you
define rhetoric?
>I don't know what it is=that's why I’m asking you<
heh (.) hhh okay, we may have to go on Google because I can't
come up with a (.) definition off the top of my head. heh
Go to the next question
Okay. (1.0) Pt.
26
Example 7
655
656
657
658
659
660
661
AM:
TM:
AM:
TM:
(3.0) ((sounds of pages turning))
What page are you on?
I was flippin around
Oh, okay.
(5.0)
OK ((coughs, clears throat))
(5.0)
Example 8
662
663
664
665
666-697
698
699
700
701
702
TM:
So what else has been going on.
AM:
Um (2.0) my brother (.) um, I told you how he had a court date
TM:
mmhm
AM:
an his court date was yesterday. …
(omitted lines)
AM:
in California so I don't mind saying it!
TM:
AM:
TM:
All right (.) s:o:
stuff (.) right?
Closing the Study Session
Example 9
708
709
710
711
712
713
714-720
721
TM:
AM:
AM:
OK.
°So°
(1.0)
This study session actually went pretty well.
(1.0)
TM:
(lines omitted)
TM:
OK. So how do you take notes then.
28
Example 10
762
763
764
TM:
AM:
TM:
Okay (1.0) Awesome.
-
Example 11
TM:
775
776
777
778
779
780
781
782
783
784
AM:
TM:
AM:
TM:
AM:
TM:
AM:
785
786
TM:
AM:
alright I'm going to text you later tell you it’ll be like “did
you do your paper- did you start your paper yet?”
[( )
[And I'm going to take a picture of the scree:n
Yes:!
Like “yes I'm doing that right now!”
Goo:d! Alright. Well (.) pt you gotta (.) get going
Ye:ah
All
Ye:s it was a really good study session even though it was
recorded.
((laughs)) And I will see- see you on Friday.
Yes (.) Friday at five.
Discussion and Conclusion
30
Future Directions
References
The Modern Language Journal, 91
Discourse Processes
27
Theory into Practice Volume 41
Annual
Review of Psychology 49
Conversational
Organization and its Development
ö
Scandinavian Journal of
Educational Research 53
Doing conversation analysis 2nd edition
The Learning Assistance Review. 15
Strategic Reading: Guiding Students to Lifelong
Literacy
32
Book Review:
Handbook for Training
Handbook for Training Peer Tutors and
Mentors
The Learning Assistance Review
34
Tutor Use by Student-Athletes:
An Exploratory Analysis
Ball State University
Abstract
For more information contact:
|
36
Method
Setting
high
research activity
38
Gender
Race
Academic Level
Sport =
Semester =
Course =
Visits
GPA Accum
GPA Semester
Grade =
Major =
40
Results
n
n
n
n
n=
n
n
Table 1
Student-Athlete Tutoring Characteristics by Gender and Race
Male
Female
Caucasian
African
American
Hispanic
Other
Unknown
SEMESTER
Fall
Spring
COURSE TYPE
353
338
350
255
455
315
198
220
22
19
13
17
15
22
Math
English
Science
Social Science
Business
120
63
89
282
70
86
34
189
203
39
119
42
202
265
62
68
40
53
186
36
9
6
11
9
5
4
3
5
14
2
6
6
7
11
4
Arts
Study Skills
45
22
32
22
50
30
24
11
1
0
1
1
1
2
VISITS (MEAN)
GPA (MEAN)
Cumulative
3.74
4.28
4.03
3.99
3.58
3.67
4
2.64
3.07
2.97
2.56
2.92
3.1
3.02
Semester
Course
MAJOR
Undecided
2.52
3.10
3.01
3.25
2.90
3.26
2.45
2.92
2.87
3.2
2.93
3.53
2.83
3.76
62
17
44
28
1
1
5
CAST
173
187
212
113
12
17
6
CAP
COB
CCIM
CFA
CSH
2
130
93
1
174
0
54
54
3
203
1
109
67
4
243
0
50
73
0
115
0
18
4
0
6
0
2
2
0
6
1
5
5
0
7
TC
11
65
58
8
0
2
8
45
691
22
605
32
770
31
418
0
41
0
30
4
37
General Studies
TOTAL
n
n
M
M
M
n
n
Table 2
Student-Athlete Tutoring Characteristics by Academic Level
Freshman
Sophomore
Junior
Senior
367
145
181
272
104
116
51
60
Math
English
Science
83
66
86
76
24
103
36
3
66
11
4
23
Social Science
Business
Arts
221
16
28
161
44
32
60
34
12
43
15
5
SEMESTER
Fall
Spring
COURSE TYPE
Study Skills
12
13
9
10
3.94
3.90
4.25
4.14
2.84
2.80
3.21
2.86
2.72
3.09
2.85
2.75
3.07
2.74
2.67
3.52
MAJOR
Undecided
CAST
CAP
COB
CCIM
CFA
CSH
TC
General Studies
64
150
0
85
26
3
148
36
0
7
142
0
59
64
0
147
21
13
0
49
0
27
45
0
57
11
31
8
19
2
13
12
1
25
8
23
TOTAL
512
453
220
111
VISITS (MEAN)
GPA (MEAN)
Cumulative
Semester
Course
42
n
women other
Table 3
Student-Athlete Tutoring Characteristics by Sport
SEMESTER
Fall
Spring
COURSE TYPE
Math
English
Science
Social Science
Business
Arts
Study Skills
VISITS (MEAN)
GPA (MEAN)
Cumulative
Football
Men's
Basketball
Baseball
Women's
Basketball
Men
Other
Women
Other
182
198
35
53
57
40
31
30
79
47
319
225
61
40
39
166
39
23
12
3.83
19
6
10
34
7
7
5
3.60
17
7
9
48
10
4
2
3.05
7
5
8
30
6
2
3
3.87
23
10
31
34
14
11
3
4.13
79
29
181
173
33
30
19
4.33
2.57
2.53
2.82
2.81
2.79
3.10
Semester
Course
MAJOR
Undecided
CAST
CAP
COB
CCIM
CFA
2.43
2.96
2.42
3.50
2.68
2.90
2.67
3.16
2.76
3.43
3.05
3.26
40
68
0
63
77
0
1
40
0
7
7
0
6
20
0
32
7
1
5
23
0
0
13
0
15
45
2
28
2
0
12
164
0
54
41
3
CSH
TC
General Studies
TOTAL
102
9
21
380
15
0
18
88
27
0
4
97
11
5
4
61
30
2
2
126
192
60
18
544
t
p
M
M
SD
SD
F
p
F
p
F
p
p
p
M
SD
M
SD
-.05
-.12**
-.06*
-.09**
.02
.10**
.20**
-.07*
-.11**
GPA Accum.
GPA
Semester
Visits
Grade
Major
Race
Academic
Level
Gender
Sport
*p < .05. **p < .01.
.03
Course
Semester
-.04
-.02
.11**
-.03
.04
.19**
-.11**
-.04
-.05
-
Course
.38**
.36**
-.03
-.09**
-.03
.23**
-.07*
.88**
-
GPA
Accum.
Pearson Correlations for Student-Athlete tutoring Variables
Table 4
.37**
.34**
-.05
-.12**
-.04
.25**
-.08**
-
GPA
Semester
.06*
.07*
.02
-.01
.04
-.04
-
Visits
.06*
.04
.02
.01
.01
-
Grade
.05
.10**
.19**
-.04
-
Major
<.01
-.04
-.14**
-
Academic
Level
.12**
.03
-
Race
.84**
-
Gender
44
Discussion
46
48
Conclusion
References
Research methods and design
in sport management.
Review of Higher Education, 27
Journal of College Reading and Learning, 40
Athletic Management, 14
Cognitive Science, 32
Society, 37
Interaction in
cooperative groups: The theoretical anatomy of group learning
Journal of Intercollegiate Sport, 3
Academic Progress Rate. Journal of Issues in Intercollegiate Athletics, 5
Journal of Student Retention.
Coach and Athletic Director, 96
Journal of College
Student Retention, 8
50
College Student Journal, 2
Leaving college
College Student Journal, 45
Athletics Coach, 66
The Relationship between
Learning Style and Study Session
University of North Texas, Denton, Texas
Abstract
L
For more information contact:
|
52
Review of the Literature
54
Theoretical Frame
Methodology
Data Collection
56
Data Analysis
Results
58
Discussion
60
Emergent Themes
62
Conclusion
Future Research
References
Research for Educational Reform, 9
Learning styles: Implications for improving
educational practices
Research design: Qualitative, quantitative, and mixed methods
approaches.
CAS professional standards for higher education
Journal of College Student
Development, 46
New Directions for Teaching and Learning, 106
New
Directions for Teaching and Learning, 106
Academy of
Management Learning & Education, 4
The modern American college: Responding
to the new realities of diverse students and a changing society
64
Experiential learning: Experience as the source of learning and development.
The Kolb Learning Style Inventory-version 3.1: LSI workbook
Journal of Developmental Education, 31
Research for
Educational Reform, 9
New Directions for Teaching and Learning, 106
Qualitative research in practice: Examples for discussion and analysis
Journal of Developmental Education, 26
How college affects students: A third decade of
research
Qualitative evaluation and research methods
Learning Theories: An educational perspective
Engineering
Education, 77
New Directions for Teaching and Learning, 106
Supplemental instruction supervisor
manual
Educational
Psychology, 28
66
Math Beliefs:
Theory-Framed and Data-Driven
Student Success
Missouri State University
Winthrop University
Abstract
I
For more information contact:
68
Learning Assistance Setting
Student perceives self as vulnerable to academic failure in
a specific course.
Student believes the consequences of academic failure to
be serious.
Student expects academic proactivity and learning
assistance to be effective in preventing failure.
Student anticipates few impediments to enacting
proactivity and seeking learning assistance.
Student is confident in own ability to perform academic
proactivity and gain learning assistance.
Health Setting
Patient perceives self as vulnerable to a specific
negative health outcome.
Patient believes the consequences of the
specific negative health outcome to be serious.
Patient expects health-promoting behaviors to
be effective in preventing the negative health
outcome.
Patient anticipates few impediments to enacting
health-promoting behaviors.
Patient is confident in own ability to perform
health-promoting behaviors.
Susceptibility
Severity
Benefit
Barriers
Efficacy
HBM Factor
Table 1. HBM Factors Mapped Onto Traditional Health Setting and New Academic Setting
70
Methods
SD
Results
72
M
p
X
p
X
p
Table 2. Descriptive Statistics, F Statistics, and Significant Beta Weights for Predictor Variables
Fail Group
Mean (SD)
n = 129
Pass
Group
Mean (SD)
Univariate F
Univariate p
Standardized
Discriminant
Function
Coefficients
n = 222
SATM
464.4 (65.2)
520.9 (70.2)
55.871
< .001
.876
Benefit
3.95 (.56)
4.05 (.50)
2.86
.09
.348
Susceptibility
2.42 (.76)
2.02 (.69)
25.18
.01
-.326
Math Anxiety
3.32 (1.10)
2.90 (1.09)
12.12
.001
-
Barrier
2.31 (.55)
2.16 (.52)
6.56
.01
-
Severity
4.10 (.86)
4.12 (.74)
.571
.45
-
Efficacy
3.81 (.52)
3.84 (.51)
.22
.64
-
Discussion
74
Reacting
References
Psychology & Health 15
Center for Studies in Higher Education
Journal of
Instructional Psychology 36
The Learning Assistance Review
12
Interdisciplinary Perspectives on Hope
Health Marketing Quarterly 26
Journal of College Student
Retention: Research, Theory & Practice 13
Journal of Applied
Social Psychology, 27
Educational
Researcher 38
New Directions for Higher Education, 99
International Quarterly of Community Health Education 15
76
Journal of
Counseling Psychology 21
Social Psychological Foundations of Health and
Illness
Journal of American
College Health, 60
Annals of Behavioral Medicine: A Publication of the Society of
Behavioral Medicine 35
MathAMATYC Educator 3
JGE: The Journal of General Education
54
Economics of
Education Review 29
Health Education Quarterly 15
Journal Of American College Health, 59
American Enterprise Institute for Public Policy Research
Liberal Education 96
Archives of Pediatric and Adolescent
Medicine 152
International Journal of Sexual Health,24
Innovations in Education and Teaching International 38
78
APPENDIX
Items on Each Subscale of the Math Belief Scale
Perceived Susceptibility to Failure
Perceived Severity of Failure
(2) I am certain that I will pass my current math class.*
(7) Math is tough enough that I think I might not pass
my current math class.
(12) I am worried about how well I will be able to
perform in my current math class.
(17) Succeeding in my current math class is not a sure
thing with me.
(3) The thought of failing my current math class scares
me.
(8) Failing my current math class would cause me big
problems.
(13) I would be embarrassed to fail my current math
class.
(18) Failing my math class this semester would not be a
big problem for me, since I could retake the course
later.*
(23) My family would be particularly upset if I get a low
grade in my current math class.
(27) I really need to learn math, because I need to use it
in the future.
Perceived Benefits of Action
Perceived Barriers to Action
(4) You either know math or you don’t; studying every
night doesn’t make much of a difference.*
(9) Going to a professor’s office greatly increases the
chances of passing a tough course.
(14) Doing math homework every night will improve
performance in my current math class.
(19) Attending group review sessions really helps with
test performance.
(24) Some people don’t think so, but I truly believe that
completing all homework assignments on time is a key
to success.
(25) Attending math class is not necessary if you
understand the material.*
(29) Proper study techniques can make a huge difference
in a math class.
(5) Math instructors speak a different language, and
there is no point in trying to ask for help.
(10) Doing math problems every night takes too much
time.
(15) No matter what they do, some people will just not
do well in math.
(20) I feel perfectly comfortable asking for help in
math.*
(28) I have other classes that are much more important
to me than passing my current math class.
(32) Success in math class is almost completely a matter
of natural ability.
Perceived Self-Efficacy
Math Anxiety
(6) I am the sort of person who can make a commitment
to study and then follow through.
(11) I know how to approach professors for help.
(16) I am organized enough to keep track of all of the
assignments, review sessions, and special resources
associated with my current math class.
(21) I might not get every answer, but I can complete
every math assignment on time.
(26) I know how to use campus resources effectively to
help me learn math.
(30) Whenever I perform poorly on a math test, it is
because of something I’ve done or not done in
preparation.
* Reverse-Coded Items
(1) Math is one of my favorite subjects.*
(22) Math makes me feel uneasy.
(31) Math makes me feel confused.
to the Second Year
University of Maine
Abstract
For more information contact:
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80
82
Method
Sample
Analyses
Table 1
Hours of Tutoring Received by Tutor Program Participants
Tutee group
Fall tutoring only
n
246
M
9.77
SD
5.21
range
.50–22.00
65
24.35
8.53
7.75–42.75
Spring tutoring only
103
11.51
5.52
.50–21.50
All tutees
414
12.49
7.85
.50–42.75
Both fall and spring tutoring
Results
M
SD =
Table 2
Represented Majors Among Tutor Program Participants
Major
Foundations
Nursing
Explorations – Undeclared
Biology
Business Administration
Animal and Veterinary Sciences
Civil Engineering
Biochemistry
Mechanical Engineering Technology
Mechanical Engineering
Psychology
Athletic Training
Zoology
Construction Management Technology
Food Science & Human Nutrition
Marine Science
Number
of Tutees
136
50
40
15
13
12
10
10
9
9
9
8
8
7
7
7
Total
FTFT
Students
209
95
190
76
47
26
54
18
28
66
61
20
23
27
18
21
Note. Only majors represented by more than 5 students are listed.
% Tutored
within Major
65.1%
52.6%
21.1%
19.7%
27.7%
46.2%
18.5%
55.6%
32.1%
13.6%
14.8%
40.0%
34.8%
25.9%
38.9%
33.3%
% of Present
Sample
(n = 414)
32.9%
12.1%
9.7%
3.6%
3.1%
2.9%
2.4%
2.4%
2.2%
2.2%
2.2%
1.9%
1.9%
1.7%
1.7%
1.7%
84
M
M
SD =
SD
d
b
p<
Table 3
Regressing Term GPA on Admissions-profile Rating and Tutoring in the Fall (Measured by Either Tutor
Program Participation or Hours of Tutoring Received)
Dependent variable
b
Fall GPA
(n = 1,510)
SE
p
Spring GPA
(n = 1,316)
b
SE
p
Tutor Program participationa
Admissions-profile rating
Tutor Program participation
Intercept
.046
.171
1.153
.003
.056
.091
.002
< .001
.049
.162
1.058
.003
.062
.094
< .001
.009
.049
.019
1.047
.003
.005
.091
< .001
.001
Hours of tutoring receivedb
Admissions-profile rating
Hours of tutoring received
Intercept
.047
.022
1.123
.003
.005
.088
< .001
< .001
Note. There were 311 tutees and 1,199 non-tutees in the analysis of fall GPA; in the analysis of
spring GPA, 224 and 1,092, respectively.
aTutor Program participation is a dichotomous variable, where 1 = tutees and 0 = non-tutees.
The unstandardized regression coefficient, b, associated with this variable is equivalent to the
mean difference between tutees and non-tutees in term GPA, adjusted for any difference on the
admissions-profile rating. For fall GPA, adjusted R2 = .16, F(2, 1507) = 146.70, p < .001; for
spring GPA, adjusted R2 = .20, F(2, 1313) = 160.44, p < .001. bHours of tutoring received is a
continuous variable capturing all fall activity, with zero assigned to non-tutees. For fall GPA,
adjusted R2 = .17, F(2, 1507) = 154.81, p < .001; for spring GPA, adjusted R2 = .20, F(2, 1313) =
163.78, p < .001
86
Adjusted term GPA
b
Table 4
Means and Standard Deviations for Tutor Program Participation and Term GPA
Group
n
Admissionsprofile rating
M
SD
M
SD
Adjusted
term GPA
M Difference
2.55
2.64
.78
.96
2.76
2.59
.17**
2.50
2.66
.84
.92
2.77
2.61
. 16*
Term GPA
Fall
Tutees
Non-Tutees
311 26.57
1,199 32.26
7.98
8.12
Spring
Tutees
Non-Tutees
224 26.20
1,092 32.72
8.19
8.10
Note. GPA statistics are based on students who received tutoring in the fall and who have valid
values for both the admissions-profile rating and fall GPA. Spring GPA statistics are based on
students who received tutoring only in the fall (in order to test for carryover effects of tutoring)
and who have valid values for both the admissions-profile rating and spring GPA. Adjusted
GPA is the regression-adjusted mean GPA based on the coefficients reported in Table 3 (Tutor
Program participation), with the difference between the adjusted means equaling the
corresponding regression coefficient in Table 3 (.17 and .16, respectively).
*p < .009. **p < .001.
of
b
p
b
p
88
Tutoring Effect on Retention
Table 5
Regressing Retention on Admissions-profile Rating and Tutoring (n = 1,613)
b
SE
p
odds ratio
< .001
< .001
1.08
1.83
Tutor Program participationa
Admissions-profile rating
Tutor Program participation
Intercept
.073
.606
-.983
.008
.155
.254
Hours of tutoring receivedb
Admissions-profile rating
.071
.008
< .001
1.07
Hours of tutoring received
.051
.012
< .001
1.05
Intercept
-.926
.246
Note. All tutees (including spring-only) were included in this analyses. There
were 414 tutees 1,199 non-tutees in the analysis of fall GPA and, respectively,
224 and 1,092 in the analysis of spring GPA.
aTutor Program participation is a dichotomous variable, where 1 = tutees and
2
88.57, p .001. bHours
0 = non-tutees. R2 = .08 (Nagelkerke), Model
of tutoring received is a continuous variable capturing fall activity, with 0
assigned to non-tutees. R2 = .09 (Nagelkerke), Model
2
94.53, p .001.
b
p
ĝ
ĝ
e gˆ (1 e gˆ )
b
p
90
Discussion
no
92
because of
how
tutoring
References
The Chronicle of Higher Education
Mentoring and Tutoring 15
Journal of College Reading and Learning 40
The Learning Assistance Review 7
The relationship between SAT scores
and retention to the second year: 2007 SAT Validity Sample.
Improving Student Learning Skills
Predicting retention and degree
progress
Journal of Student Affairs Research and Practice
46
The Learning
Assistance Review 15
Journal of College Reading
and Learning 41
American Journal of Pharmaceutical Education 70
Journal of
Developmental and Remedial Education 8
Providing Effective Tutorial Services
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