THE EFFECT OF SUBJECT FIELD AND GENDER OF PRESERVICE TEACHERS ON THEIR PREFERRED SELFREGULATED LEARNING STRATEGIES
Emine Cabı
Başkent University, Faculty of Education
Department of Computer Education and Instructional Technologies, Ankara / Turkey
[email protected]
Assist. Prof. Dr. Yasemin Gülbahar
Başkent University, Faculty of Education
Department of Computer Education and Instructional Technologies, Ankara / Turkey
[email protected]
ABSTRACT
In teaching-learning processes, students’ willingness to learn is as important as the stages of instruction like planning, presenting and
organization. The need for providing and organizing content for learners’ to learn wherever and whenever they want resulted in the emergence
of the concept of “self-regulated” learning. Individuals use self-regulation strategies for gaining experience throughout their life and according
to life-long learning approach they will continue to use it in the future also. On the other hand, since people have individual differences, the
self-regulation strategies they use will also show diversity. Since different self-regulation strategies are preferred by individuals, the purpose of
this study is to investigate this diversity according to subject fields and gender. For this reason, 203 pre-service teachers who are following the
graduate program “Secondary Education Subject Teaching” under the institute of Educational Sciences in a private university in Turkey,
formed the participants of this study. The participants were administered “Motivated Strategies for Learning Questionnaire”, which is translated
into Turkish by Büyüköztürk et. al. (2004), in order to find out the self-regulation strategies they used. The findings of this study revealed that
there is a significant difference between external goal orientation and gender, effort management and subject field, and critical thinking skills
and gender. Based on the findings, suggestions for future research were also provided.
Keywords: Self-regulated Learning, Learning Strategies, Motivation Strategies
INTRODUCTION
Social cognitive models of self-regulated learning are
strictly distinguished from cognitive models (Bandura,
1986; Pintrich, 2000; Schunk, 2001; Zimmerman, 2001).
While cognitive models do not focus on social or
environmental factors, social cognitive models investigate
the relationships between self-regulated learning
strategies, beliefs and feelings, and social and physical
environment (Whipp & Chiarelli, 2004).
Regardless of the success of teaching-learning processes’
design and presentation, learning is directly related with
students’ skills and attitudes toward instruction. During
teaching-learning processes, students’ motivation and the
need for learning are the important components which
support learning. The need for arranging and providing
learning activities whenever students require, lead the
emergence of the concept of “self-regulated learning”.
Self-Regulated Learning Cycle Phases
Schunk (2000) defines self-regulated learning as “…the
process whereby learners systematically direct their
thoughts, feelings and actions toward the attainment of their
goals”, whereas other researchers defines self-regulation as
specifying goals, developing strategies to achieve these
goals and assessing the success of these implementations
(Schunk, 2000, p. 355).
One of the leading researchers of self-regulated learning
based on social cognitive model is Zimmerman (1998).
According to Zimmerman, self-regulated learners believe
that “…academic learning is a proactive activity, requiring
self-initiated motivational and behavioral processes…”,
and by this way they “…become controllers rather than
victims of their learning experiences” (Zimmerman, 1998,
p. 1).
In general, self-regulation theories and models which
focuses on contribution to student achievement shows
diversity. For example, operant models generally focus on
behavioral dimensions of self-regulated learning, based on
the idea that behaviors influenced mostly by external stimuli.
In these models, students define their behavioral goals that
will improve their academic achievement by themselves.
The setting of these self-directed strategies encourages
students in reaching their goals (Whipp & Chiarelli, 2004).
Perceiving learning as an open-ended process, selfregulation theorists define three cyclical phases explaining
academic learning. These three phases are; forethought,
performance or volitional control, and self-reflection (See
Figure-1).
Figure 1. Academic Learning Cycle Phases (adapted from
Zimmerman 1998, p. 3)
Performance or Volitional Control
Cognitive models of self-regulated learning are influenced
by information-processing theories. Thus, metacognitive
strategies like self-monitoring, self-reflection and selfassessment are frequently used to complete academic
tasks in these cognitive models. (Whipp & Chiarelli, 2004).
Forethought
Self-Reflection
The forethought phase refers to influential processes like
feeling strong efforts to learn and to complete tasks.
313
Second phase performance or volitional control consists of
processes and efforts which affects performance. The last
phase, self-reflection covers processes like students’
reactions to learning experience which takes place after
learning occurs.
Self-judgment is a process that depends on the
comparison of current performance with previously
determined learning goals. Extend of reaching goals and
appropriateness with the objectives is some of the
features of self-judgment. These are the dimensions that
affect decision process during self-judgment (Schunk,
2000).
Cyclical processes and subprocesses of self-regulation as
stated by Zimmerman can be seen in Table-1.
Self-Reflection
Table 1. Cyclical processes and subprocesses of selfregulation (adapted from Zimmerman 1998, p. 4)
Forethought
 Goal setting
 Strategic
planning
 Self-efficacy
beliefs
 Goal orientation
 Intrinsic interest
Performance or
Volitional Control
 Attention
focusing
 Self-instruction
 Self-monitoring
According to Bandura (1986), there are two phases of
self-reflection, which is in close relationship with selfmonitoring; self-judgment and self-reaction. Self-judgment
constitutes of valuing the decisions about self-evaluation.
Self-evaluation is the comparison of herself/himself with a
standard or goal. Individuals evaluate themselves
according to four different criteria, namely mastery,
previous performance, normative and collaborative
(Zimmerman (2000) as cited in Haşlaman & Aşkar, 2007).
Self-Reflection
 Selfevaluation
 Attributions
 Selfreactions
 Adaptivity
An individuals’ reaction to herself/himself is important
while converting goals to behaviors. If individual believes
that she/he will transform the goal to behavior, in other
words giving positive reaction, he/she is more likely to
succeed (Schunk, 2000).
Self-regulation strategies, emerging from cyclical processes
of self-regulation as defined by Zimmerman and
categorization done by Schunk (2000), and Whipp and
Chiarelli (2004), can be defined as follows.
Based on the self-regulation theory, this study is
conducted to investigate if any difference occurs between
self-regulation strategies and the field of expertation of
graduate students.
Goal Setting
Goal setting facilitates students being active participants
while decision making, constructing knowledge, being
motivated and evaluating learning outcomes. There is a
strong relationship between goals, achievement, motivation
and self-regulation. Specifying goals more than the students
can achieve influence intrinsic motivation, thus affects selfregulation in a negative way (Schunk, 2000).
METHOD
This research study is mainly based on quantitative
measures and used descriptive method. This study is also
a case study since the participants are the graduate
students of one institution in one program.
Time Management
Participants
Previously defined as a predictor of academic performance
(Trueman & Harley, 1996) and a strategy that encourages
self-regulation, time management is an important concept
for self-regulation (Terry & Doolittle, 2006). From the social
cognitive view, time management influences behavioral,
environmental and personal learning strategies (Bandura,
1986). Thus, necessary principles for effective time
management should be provided students for better
performance.
The participants of this research study are the graduate
students of Secondary Science, Mathematics, Turkish and
History Education, which studies in a private university.
The data gathered from 203 students who voluntarily
wanted to participate in the study.
Instruments
In this study, “Motivated Strategies for Learning
Questionnaire (MSLQ)” was used for gathering data.
Originally developed by Pitrinch et. al. (1993), the MSLQ
is adapted into Turkish by Büyüköztürk, Akgün, Özkahveci
and Demirel (2004). The questionnaire consists of two
scales, namely Motivation Scale (MS) and Learning
Strategies Scale (LSS). In addition to descriptive and
confirmatory factor analysis for validity, the authors
performed reliability analysis. Their findings indicated that
the mean of reliability coefficient for motivation scale is
between 0.63, where the mean of reliability coefficient of
learning questionnaire scale is 0.61. Motivation scale
consisted of 6 factors, namely intrinsic goal orientation,
extrinsic goal orientation, task value, self-efficacy for
learning and performance, control belief about learning,
and test anxiety. Learning Strategies Scale consists of 9
factors that are rehearsal, elaboration, organization,
critical thinking, metacognition, managing time and study
environment, effort management, peer learning, and helpseeking.
Help Seeking
Help seeking is a method for encouraging the learners to
recognize the social environment. Self-regulated learners
seek for help from instructors and colleagues when they
face with a difficult task or need support (Schunk, 2000).
Help seeking in self-regulated learning is important to
provide feedback in teaching-learning processes (Schunk,
2000; Terry & Doolittle, 2006).
Self-Observation
While making decisions about behaviors, individuals take
into consideration both individual observations and
standards. For this reason, self-monitoring before selfdecision is a different dimension of self-regulation
strategies. Observation process and self-monitoring is
similar concepts (Schunk, 2000). Furthermore, selfmonitoring “…provides a basis of awareness and control of
cognition and learning” (Mullen, 2007, p. 406).
Data Analysis
As descriptive analysis, frequency analysis and
independent samples t-test was used to analyze the
gathered data by the use of SPSS program. The
significance level was taken as 0,05 through the analysis.
Self-Judgment
314
Factor
6
Factor
7
Factor
8
Factor
9
RESULTS
The distribution of subscales of motivation strategies of
students according to their subject fields, where “Verbal”
stands for qualitative departments (Turkish, History) and
“Numerical” (Num.) stands for quantitative departments
(Mathematics, Science), can be seen in Table 2.
Factor
1
Factor
2
Factor
3
Factor
4
Factor
5
Factor
6
Subject
Field
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.

N
X
112
91
112
91
112
91
112
91
112
91
112
91
5,32
5,29
4,29
4,20
5,33
5,16
5,35
5,47
4,93
4,89
5,00
5,00
S
df
t
1,03
,98
,99
,95
,84
,82
,98
,99
,85
,97
,89
,95
201
,18 ,85
201
,65 ,51
201
1,42 ,15
201
,84 ,40
,34 ,73
201
,05 ,95

X
S
Factor
1
Factor
2
Factor
3
Factor
4
Factor
5
Factor
6
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
123
80
123
80
123
80
123
80
123
80
123
80
5,34
5,25
4,14
4,42
5,17
5,37
5,34
5,50
4,86
4,99
4,91
5,14
1,03
,97
,99
,92
,79
,90
,97
1,00
,93
,86
,92
,89
t
Sig.
201
df
,68
,53
201
2,00
,04
201
1,61
,10
201 2,31
,02
201 1,70
,09

Faktör
Gender
N
X
S
df
t
Factor
1
Factor
2
Factor
3
Factor
4
Factor
5
Factor
6
Factor
7
Factor
8
Factor
9
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
123
80
123
80
123
80
123
80
123
80
123
80
123
80
123
80
123
80
4,99
5,07
5,12
5,21
5,22
5,52
4,95
5,32
4,99
5,07
4,78
4,95
4,21
4,45
5,02
4,79
5,00
4,78
1,26
1,26
1,21
1,11
1,05
1,16
1,06
1,11
,83
,89
,94
1,06
1,32
1,36
1,02
1,10
,88
1,02
201
,44
,65
,54
,58
201
1,88
,06
201
2,35
,01
201
,63
,52
201
1,22
,22
201
1,24
,21
201
1,49
,13
201
1,63
,10

201
Sig.

201
1,11
,26
201
0,98
,32
CONCLUSION AND DISCUSSION
201
1,80
,70
According to self-regulation theory, learning strategies and
motivation are key factors for academic achievement.
Based on this fact, this research study investigated the
relation existing between the subscales of learning
strategies and motivation. Three subscales showed
significant difference between gender or subject field.

One of them was the significant difference between
external goal orientation and gender. From the
motivational aspects, males have founded to have higher
external goal orientation than females. This finding is
parallel with other findings in the literature (Patrick, Ryan
& Pintrich, 1999; Haşlaman, 2005).
Table 4. The distribution of subscales of learning strategies
according to subject fields
Factor
,14
( X =5,32) than females ( X =4,95).
The distribution of subscales of learning strategies of
students according to their subject fields can be seen in
Table 4.
Factor
1
Factor
2
Factor
3
Factor
4
Factor
5
201 1,46
According to Table 5, there is a significant difference
between factor 4 (critical thinking) and gender (t(faktör
4)=2,35; p<0.05]. Males has higher critical thinking skills
orientation skills ( X =4,42) than females ( X =4,14).
Subject
Field
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.
,84
Table 5. The distribution of subscales of learning
strategies according to gender
According to Table 3, there is a significant difference
between factor 2 (extrinsic goal orientation) and gender.
(t(factor 2)=2,00; p<0.05]. Males has higher extrinsic goal

,20

Table 3. The distribution of subscales of motivation
strategies according to gender
N
201
fields having qualitative ones ( X =4,78).
The distribution of subscales of motivation strategies of
students according to gender can be seen in Table 3.
Gender
1,03
,94
1,36
1,31
1,04
1,05
,96
,92
management skills ( X =5,12) than students of graduation
According to Table 2, there is no meaningful relationship
between subscales of motivation strategies with their
subject fields of participants [p>0,05] .
Factor
4,86
4,83
4,43
4,16
4,78
5,12
4,81
5,04

Sig.
201
112
91
112
91
112
91
112
91
According to Table 4, there is a significant difference
between factor 8 (effort management) and subject field
(t(factor 8)=2,31; p<0.05]. Students of graduation fields
having quantitative departments has higher effort
Table 2. The distribution of subscales of motivation
strategies according to subject fields
Factor
Verbal
Num.
Verbal
Num.
Verbal
Num.
Verbal
Num.
N
112
91
112
91
112
91
112
91
112
91

X
S
4,91
5,16
5,13
5,19
5,36
5,31
5,11
5,07
5,00
5,05
1,33
1,15
1,19
1,15
1,13
1,07
1,13
1,05
,89
,80
df
t
The second finding was the significant difference between
effort management and subject field. From the learning
strategies point of view, the graduates of quantitative
departments have higher effort management skills than
qualitative ones. No similar or contradictory result has
been found in the literature related with this finding.
Sig.
201 1,38
,16
201
,38
,70
201
,34
,73
201
,28
,77
201
,40
,68
As a third and last finding of this study, it is found that
there is a significant difference between critical thinking
skills and gender as the learning strategies dimension.
Males are found to have more critical thinking skills than
females. There is a contradictory finding about this result
315
in literature. Both Özdemir (2005) and Pokay and
Blumenfeld (1990) has stated no significant difference
between males and females in terms of critical thinking
abilities.
Moshe Zeidner (Eds.),Handbook of self-regulation
(pp. 451–502).
Pokay, P., & Blumenfeld P.C., (1990). Predieting
achievement earlyand late in the Semester:,The
role of motivation and use of learning strategies.
Journal of Educational Psychology, 82(1), 41-50.
Based on the findings of this research study, the following
suggestions are provided for future researchers.

Activities that encourage the use of motivation and
learning strategies should be integrated into courses,
and academic achievement of students should be
investigated.

The effect of activities that enhances critical thinking of
students should be evaluated.

The effect of self-regulated learning environment on
different variables like life-long learning, reading
comprehension, and web-based instructional design
can be investigated.
Schunk, D. H. (2000). Learning theories: An educational
perspective (3rd ed.). USA: Merrill, an Imprint of
Prentice Hall.
Schunk, D. H. (2001). Social cognitive theory and Selfregulated Learning. In: B. J. Zimmerman & D. H.
Schunk (Eds.), Self-regulated learning and
academic achievement (2nd ed.) (pp. 125–151).
Mahwah, NJ: Erlbaum.
Terry, K. P. & Doolittle, P. (2006). Fostering Selfregulation in distributed learning. Retrieved October
10,
2007,
from
http://www.senecac.on.ca/quarterly/2006-vol09num01-winter/ Vol. 9 Num 1.
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