INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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Is There a Relationship between Motivational Beliefs and Cognitive
Strategy Use and Self-Regulation?
*Nurfarah Saiful Azam1, Mohamed Hafizuddin Mohamed Jamrus2, Nadiah Zubbir3, Noor Aizah Abas4
Noor Hanim Rahmat5
1,2,3,4,5 Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam, Malaysia
*Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000222
Received: 07 October 2025; Accepted: 14 October 2025; Published: 08 November 2025
ABSTRACT
Understanding how learners' beliefs influence their use of cognitive strategies and self-regulation is an important
issue in educational psychology, as motivational beliefs, cognitive strategy use, and self-control are
interconnected. And there is a cyclical relationship between these three components. Motivational beliefs drive
the use of cognitive strategies, which in turn enhance self-control. This cycle leads to better academic outcomes
and the development of lifelong learning skills. The researchers were motivated to carry out this study because
investigating this allows them to understand how these factors impact students' learning outcomes and can
provide instructors with insights into more effective teaching strategies. The objective of this study is to explore
the motivational factors that influence learning among undergraduate students. A quantitative approach was
employed for this study. A 5-point Likert-scale survey, based on Pintrich & De Groot (1990), was used to
measure the relevant variables. The survey consists of three sections: Section A includes demographic questions,
Section B contains 22 items on motivational beliefs, and Section C comprises 22 items on self-regulated learning
strategies.The survey was completed by a purposive sample of 282 undergraduate students from the largest
public university in Malaysia. The findings of this study is that students generally have moderate to high
confidence in their abilities, strong motivation to learn, and moderate levels of test anxiety suggesting that
motivation plays a vital role in students' learning experiences and performances. Next, students actively use
cognitive strategies to process information and apply self-regulation techniques, although some areas need
improvement. Lastly, there is a moderately positive correlation between motivational beliefs and self-regulated
strategies, suggesting that students who are more motivated tend to use more cognitive strategies and self-
regulation techniques which has significant implications for teaching and learning by focusing on fostering both
motivation and self-regulation. There is the need to enhance student motivation through goal-setting exercises,
positive feedback, and relevant teaching materials. Developing self-regulated learning skills by integrating
metacognitive training to help students monitor their progress, adjust their study strategies, and become more
independent learners are also encouraged. Future researchers could investigate whether early interventions aimed
at improving student motivation lead to long-term academic success.
Keywords: Motivation, Motivational Beliefs, Cognitive Strategy, Self-Regulation, Language Learning.
INTRODUCTION
Background of Study
Motivation is one of the most important key elements in making sure learning can be achieved. This paper will
elaborate on motivational beliefs which are the core factors in how students choose and approach learning.
Strong self-efficacy will help students in increasing their beliefs for success which will lead them to persevere
in challenging tasks and use deeper learning strategies. When students are engaged in high task value, they will
learn more from the content. The type of goal orientation they adopt also influences their learning behaviours—
mastery-oriented learners seek to deeply understand concepts and use advanced cognitive strategies, while
performance-oriented learners may focus on surface-level memorisation just to achieve high grades.
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These motivational beliefs shape the cognitive strategies students choose to process and retain information. Some
rely on rehearsal strategies, which involve simple repetition for memorisation, while others use elaboration
strategies, connecting new knowledge with prior learning to enhance understanding. More advanced learners
engage in organisational strategies, structuring information meaningfully, which aids recall and problem-
solving. The choice of these cognitive strategies depends on motivation—students with strong intrinsic
motivation tend to use deeper strategies, while those with low motivation often rely on surface learning
techniques.
As students apply these cognitive strategies, they develop self-regulation skills, which allow them to manage
their learning effectively. Self-regulated learners engage in a forethought phase, where they plan, set goals, and
assess their motivation. During the performance phase, they apply cognitive strategies and monitor their
progress, adjusting their learning approaches when necessary. Finally, in the self-reflection phase, they evaluate
their performance and refine their learning methods for future tasks. This process ensures continuous
improvement and adaptation to learning challenges.
Overall, there is a cyclical relationship between these three components. Motivational beliefs drive the use of
cognitive strategies, which in turn enhance self-regulation. As students become more self-regulated, they build
stronger motivation, reinforcing their ability to learn effectively. This cycle leads to better academic outcomes
and the development of lifelong learning skills
Statement of Problem
Students in the current era (2025), are facing different struggles in learning. Mass information available readily
at all times may have decreased students' motivation in learning due to the availability of information anytime
and anywhere. It can be challenging to students to have pure motivational beliefs in learning due to the
environment presented to them. Therefore this study will deep dive into the modern approach in maintaining
high motivational beliefs and connect it all together with cognitive strategy use.
Despite extensive research on student learning, many learners struggle to effectively regulate their learning
processes, leading to poor academic performance and disengagement. Motivational beliefs, cognitive strategy
use, and self-regulation are critical factors that influence how students approach learning, yet their
interconnections remain underutilized in educational practice. Many students lack the motivation to engage
deeply with learning tasks, often relying on ineffective cognitive strategies such as rote memorization rather than
deeper processing techniques like elaboration and organization. Furthermore, self-regulation skills, including
goal setting, progress monitoring, and reflection, are often underdeveloped, limiting students' ability to adapt
and sustain their learning efforts.
The challenge lies in understanding how motivational beliefs shape cognitive strategy use and how both factors
contribute to the development of self-regulation. Without a clear framework that connects these elements,
educators struggle to design interventions that foster intrinsic motivation, effective learning strategies, and self-
directed learning habits. Addressing this issue is crucial for improving student outcomes and preparing learners
for lifelong learning.
Objective of the Study and Research Questions
This study is done to investigate how learners perceive their motivational beliefs and the use of self-regulated
strategies. Specifically, the study will address the following research questions:
How do learners perceive their motivational beliefs?
How do learners perceive their use of cognitive strategies?
Is there a correlation between motivational beliefs and self-regulated strategies?
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LITERATURE REVIEW
Theoretical Framework
Motivational Beliefs
Motivational strategies can assist students in initiating their schoolwork, maintaining effort despite motivational
challenges, or redirecting their focus from non-learning to learning objectives. (Smit et al., 2017). Pintrich and
De Groot (1990) has identified that there are three key motivational factors which influence classroom academic
performance; self-efficacy, intrinsic values and test anxiety. According to Pintrich and De Groot (1990), self-
efficacy involves a student being confident in their own abilities, including their perceived competence and their
confidence in performing academic tasks. Self-efficacy is the belief in one's own ability to successfully complete
a task and learners who have self-efficacy beliefs are able to comprehend the concepts taught in class and are
able to study the materials in class (Zainuddin et al., 2023). Meanwhile, intrinsic value refers to a student's
internal interest in and perceived significance of coursework, as well as their preference for challenges and goals
related to mastery (Pintrich and De Groot, 1990). Bandura and Schunk (1981) explained in their research o, that
intrinsic interest can be fostered from the satisfaction gained from achieving subgoals. Students are interested in
learning what they like, studying important subjects and learning interesting and useful information (Yew at el.,
2023). Finally, test anxiety involves feelings of worry and mental distractions during exams (Pintrich and De
Groot, 1990). Yew at el. (2023) argued that the high motivation to achieve academic excellence results in the
prominent level of test anxiety among learners. In this study, self-efficacy, intrinsic values and test anxiety is
examined to investigate how Japanese and English language perceive motivational beliefs.
Self-Regulated Strategies
Self-regulated learning is not a mental ability or an academic skill, but rather a self-guided process in which
students convert their cognitive abilities into goal-focused academic skills (Marucci, 2023). Pintrich and De
Groot (1990) discussed that there are components of self-regulated learning which are especially vital for
classroom performance; metacognitive strategies, self-regulation and cognitive strategy. Metacognitive strategy
involved planning, monitoring, and modifying students’ cognition (Pintrich and De Groot, 1990). Meanwhile,
cognitive strategy is referred to as the strategies that learners’ utilized to to learn, memorize, and comprehend
the learning material (Pintrich and De Groot, 1990; Corno & Mandinach, 1983; Zimmerman & Pons, 1986,
1988). On the other hand, self-regulation refers to students' ability to manage and control their effort on academic
tasks in the classroom (Pintrich and De Groot, 1990). Corno and Mandinach (1983) explained that the act of
directing effort to academic tasks by students is a form of cognitive engagement and if this intellectual activity
continues, students will be able to utilize the learning approaches they used in school. Yew (2023) explained
that cognitive strategy and self-regulation are highly correlated with self-regulated learning when achieving
students’ goals. Thus, through these two components, this study aimed to investigate how Japanese and English
language students perceived self-regulated learning strategies.
Past Studies
Past Studies on Motivational Beliefs
In recent studies, motivational beliefs were examined among students at tertiary level. These studies concluded
that motivational beliefs components have a positive relationship with academic performance. However, what
components are significant varies in these studies.
Gharghani et al. (2019) explored the relationship between motivational beliefs, cognitive and metacognitive
strategies, and academic achievement among students. A total of 250 medical and health students from Shiraz
University of Medical Sciences were selected using Levy and Lemeshow sampling formula. Data were collected
through the Motivated Strategies for Learning Questionnaire (MSLQ) developed by Pintrich and de Groot.
Gharghani et al. (2019) found that, among the components of motivational beliefs, self-efficacy had a significant
positive correlation with academic performance. Through multiple regression analysis, Gharghani et al. (2019)
determined that self-efficacy demonstrates a prominent positive correlation with academic performance.
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Students with stronger self-efficacy beliefs, who reinforce their confidence, are more likely to achieve better
academic outcomes.
Zainuddin et al. (2023) investigated learners' perceptions of their use of learning strategies. A total of 140
participants were given questionnaires based on the Motivated Strategies for Learning Questionnaire (MSLQ),
developed by Paul R. Pintrich and Debra J. De Groot. The data were analyzed by calculating the mean scores
for self-efficacy, intrinsic value, test anxiety, cognitive strategy, and self-regulation. Zainuddin et al. (2023)
discovered that intrinsic value had the highest mean, indicating that students feel positive about their academic
progress and what they expect to achieve. Zainuddin et al. (2023) also reported being good at understanding and
applying the information they learn, relating it to their existing knowledge. However, self-efficacy had the lowest
mean, as students generally did not compare themselves with their peers and did not believe they knew as much
about the subject.
Yew et al. (2023) examined how learners' motivational beliefs and self-regulated learning strategies impact their
learning process. This quantitative study is based on the conceptual framework of Pintrich & DeGroot (1990).
The study sample included 51 ESL undergraduates from a public university. A 5-point Likert-scale survey,
adapted from Pintrich & DeGroot (1990), was used to gather data. Yew et al. (2023) revealed that the most
significant motivational belief component was intrinsic value, with students expressing motivation to learn
because they enjoy the subject, find it important, and view it as both interesting and useful. Additionally, Yew
et al. (2023) concluded that the learning strategies of post-Covid-19 pandemic students are strongly influenced
by their motivational beliefs and self-regulated learning strategies, particularly among diploma students.
In the studies mentioned, academic performance has a positive relationship with motivational beliefs
components. Intrinsic values and self-efficacy are the most significant components in achieving an excellent
academic performance. This indicates that students who enjoyed their classes and are confident have higher
chances to perform better in class.
Past Studies on Self-Regulated Strategies
The past studies regarding self-regulated learning strategies have varied on whether these strategies have a
positive relationship with academic performance or not. Some discovered that these strategies lead more to
increasing a student's effort in getting better grades.
Smit et al. (2017) investigated how students use motivational strategies as intermediaries between their beliefs
about the value of schoolwork, their sense of competence, and their motivational engagement. The study
involved 3,602 students aged 11 to 21 from 49 pre-vocational secondary education schools, who completed
Wolters’ questionnaire on strategies in Dutch. Smit et al. (2017) revealed that self-regulated learners were able
to set goals, plan, and adjust their motivation accordingly through the use of self-regulated learning strategies.
Smit et al. (2017) also argued that using more motivational strategies could increase a student’s effort but not
their achievement. Thus, Smit et al. (2017) suggested that students need to be trained first to utilize cognitive
and meta-cognitive strategies.
In their 2019 study, Gharghani et al. examined the connection between motivational beliefs, cognitive and
metacognitive strategies, and academic success among students. Using the Levy and Lemeshow sampling
formulas, they selected 250 medical and health students from Shiraz University of Medical Sciences, who then
completed the Motivated Strategies for Learning Questionnaire (MSLQ) created by Pintrich and de Groot. The
findings revealed that only metacognitive learning strategies were significant predictors of academic
performance. Additionally, the study concluded that students who utilize a broader range of cognitive strategies
tend to achieve better academic results.
Yew et al. (2023) investigated the influence of learners' motivational beliefs and self-regulated learning strategies
on their learning processes. This quantitative study was grounded in the conceptual framework of Pintrich &
DeGroot (1990). The sample consisted of 51 ESL undergraduates from a public university, and data was
collected using a 5-point Likert-scale survey adapted from Pintrich & DeGroot (1990). The results revealed that,
in terms of self-regulated learning strategies, students primarily rely on cognitive strategies, such as memorizing
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facts for exams. Furthermore, regarding self-regulation, students put in effort to achieve good grades even if they
do not enjoy the class.
The studies mentioned above discovered that cognitive strategies are the most utilized strategies in self-regulated
learning strategies. Students tend to memorize facts for better grades. However, the studies vary when it comes
to academic performance. Gharghani et al. agreed that self-regulated learning strategies predict the academic
performances of students. However, Smit et al. (2017) and Yew et al. (2023) argued that they only improve
student’s effort but not their grades.
Conceptual Framework
Figure 1 presents the conceptual framework of the study, which explores the relationship between motivational
beliefs and the components of self-regulated learning strategies. Motivation not only helps learners sustain their
learning but also fosters independence in their pursuit of knowledge (Rahmat & Thasrabiab, 2024). Learners'
motivational beliefs can be categorized into self-efficacy, intrinsic value, and test anxiety (Pintrich & De Groot,
1990). Independent learners are able to utilise self-regulated learning strategies, including cognitive strategy use
and self-regulation (Pintrich & De Groot, 1990).
Figure 1 - Conceptual Framework of the Study -
Relationship between Motivational beliefs and Cognitive Strategy use and Self-Regulation
METHODOLOGY
This quantitative study is done to explore motivational factors for learning among undergraduates. A purposive
sample of 282 participants responded to the survey. The instrument used is a 5-point Likert-scale survey, adapted
from Pintrich & De Groot (1990) to reveal the variables presented in Table 1 below. The survey consists of 3
sections. Section A has items on demographic information. Section B has 22 items on motivational beliefs.
Section C has 22 items on self-regulated learning strategies.
Table 1 - Distribution of Items in the Survey
PART STRATEGY SCALE No Of
Items
Total
Items
TWO MOTIVATIONAL
BELIEFS
A SELF-EFFICACY 9 22 .871
B INTRINSIC VALUE 9
C TEST ANXIETY 4
MOTIVATIONAL
BELIEFS
Cogniitve Strategy Use
Self-Regulation
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THREE SELF-REGULATED
LEARNING
STRATEGIES
D COGNITIVE STRATEGY USE 13 22 .890
E SELF-REGULATION 9
TOTAL NO OF ITEMS 44 .929
Table 1 displays the reliability of the survey. The analysis reveals a Cronbach's alpha of .871 for motivational
beliefs and .890 for self-regulated learning strategies. The overall reliability for all 44 items is .929, indicating
good reliability of the instrument used. Further analysis was conducted using SPSS to present the findings that
address the research questions of this study.
FINDINGS
Findings for Demographic Profile
Table 2 - Gender of the Respondents
NO ITEM PERCENTAGE
1 Male 35%
2 Female 65%
The percentage of gender findings in Table 2 delineates that the majority of respondents were female, accounting
for 65% of the participants, while males constituted the remaining 35%.
Table 3 - Cluster of Study
NO ITEM PERCENTAGE
1 Science & Technology 33%
2 Social Sciences 60%
3 Business 7%
The findings for the Cluster of Study in Table 3 indicates that the majority of respondents were from the Social
Sciences discipline (60%), followed by Science & Technology (33%) and Business (7%).
Table 3 - Languages Taken by Respondents
NO ITEM PERCENTAGE
1 English 26%
2 Japanese 33%
3 Both 41%
The findings from Table 3 shows the languages that respondents are learning. 41% of respondents are learning
both English and Japanese, 33% are learning Japanese, and 26% are learning English.
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Table 5 - Semester of the Respondents
NO ITEM PERCENTAGE
1 Semester 1-2 33%
2 Semester 3-4 52%
3 Semester 5 and above 15%
The findings for the semester of the respondents in Table 5 depicts that the majority were in Semester 3-4 (52%),
followed by Semester 1-2 (33%), and Semester 5 and above (15%).
Findings for Motivational Beliefs
This section presents data to answer Research Question 1: How do learners perceive their motivational beliefs?
In the context of this study, this refers to (i) self-efficacy, (ii) intrinsic value, and (iii) test anxiety.
Table 6 - Mean for (i) Self-Efficacy (9 items)
ITEM MEAN
MBSEQ1Compared with other students in this class I expect to do well. 3.4
MBSEQ2I'm certain I can understand the ideas taught in this course. 3.9
MBSEQ 3I expect to do very well in this class. 3.9
MBSEQ 4Compared with others in this class, I think I'm a good student 3.3
MBSEQ5I am sure I can do an excellent job on the problems and tasks assigned for this class. 3.7
MBSEQ61 think I will receive a good grade in this class. 3.8
MBSEQ 7My study skills are excellent compared with others in this class. 3.0
MBSEQ8Compared with other students in this class I think I know a great deal about the subject. 3.2
MBSEQ9I know that I will be able to learn the material for this class 3.9
Table 6 illustrates the mean scores for self-efficacy items, which ranged from 3.0 to 3.9. The highest mean score
(3.9) was observed for three items: certainty in understanding course ideas (MBSEQ2), expecting to do very
well (MBSEQ3), and confidence in learning course material (MBSEQ9). The lowest mean score (3.0) was
reported for study skills compared to others (MBSEQ7). Other items scored between 3.2 and 3.8, reflecting
moderate to high levels of self-efficacy among the respondents.
Table 7 - Mean for (ii) Intrinsic Value (9 items)
ITEM MEAN
MBIVQ1I prefer class work that is challenging so I can learn new things. 3.5
MBIVQ2It is important for me to learn what is being taught in this class. 4.3
MBIVQ3I like what I am learning in this class. 4.3
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MBIVQ 4I think I will be able to use what I learn in this class in other classes. 3.9
MBIVQ 5I often choose paper topics I will learn something from even if they require more work. 3.5
MBIVQ 6Even when I do poorly on a test I try to learn from my mistakes. 4.2
MBIVQ7 I think that what I am learning in this class is useful for me to know. 4.3
MBIVQ 8I think that what we are learning in this class is interesting. 4.3
MBIVQ 9Understanding this subject is important to me. 4.4
The mean scores for intrinsic value in Table 7 demonstrates that items ranged from 3.5 to 4.4. The highest mean
score (4.4) was observed for the importance of understanding the subject (MBIVQ9), followed by items
emphasizing the usefulness and interest of the content (4.3 each for MBIVQ2, MBIVQ3, MBIVQ7, and
MBIVQ8). Moderate scores (3.5) were recorded for preference for challenging work (MBIVQ1) and choosing
topics to learn from despite the effort (MBIVQ5). Overall, the data reflect strong intrinsic motivation among
respondents to learn and value the course material.
Table 8 - Mean for (iii) Test Anxiety (4 items)
ITEM MEAN
MBTAQ1I am so nervous during a test that I cannot remember facts I have learned. 3.2
MBTAQ 2I have an uneasy, upset feeling when I take a test. 3.1
MBTAQ 3I worry a great deal about tests. 3.5
MBTAQ 4When I take a test I think about how poorly I am doing. 3.3
Table 8 exhibits the mean scores for test anxiety items, which range from 3.1 to 3.5. The highest mean score
(3.5) was observed for worrying a great deal about tests (MBTAQ3), followed by thinking about poor
performance during a test (MBTAQ4) at 3.3. The lowest scores were recorded for nervousness affecting memory
(MBTAQ1) at 3.2 and having an uneasy feeling during tests (MBTAQ2) at 3.1. These results suggest moderate
levels of test anxiety among the respondents.
Findings for Cognitive Strategy Use
This section presents data to answer Research Question 2: How do learners perceive their cognitive strategy use?
In the context of this study, this refers to (i) cognitive strategy use and (ii) self-regulation.
Table 9 - Mean for (i) Cognitive Strategy Use (13 items)
ITEM MEAN
SRLSCSUQ1When I study for a test, I try to put together the information from class and from the
book.
4.1
SRLSCSUQ 2When I do homework, I try to remember what the teacher said in class so I can
answer the questions correctly.
4.2
SRLSCSUQ 3It is hard for me to decide what the main ideas are in what I read. 3.2
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SRLSCSUQ 4When I study, I put important ideas into my own words. 3.9
SRLSCSUQ 5I always try to understand what the teacher is saying even if it doesn't make sense. 3.9
SRLSCSUQ 6When I study for a test, I try to remember as many facts as I can. 4.2
SRLSCSUQ 7When studying, I copy my notes over to help me remember material. 3.9
SRLSCSUQ 8When I study for a test, I practice saying the important facts over and over to myself. 4
SRLSCSUQ 9I use what I have learned from old homework assignments and the textbook to do
new assignments.
4
SRLSCSUQ 10When I am studying a topic, I try to make everything fit together. 3.9
SRLSCSUQ 11When I read material for this class, I say the words over and over to myself to help
me remember.
3.9
SRLSCSUQ 12I outline the chapters in my book to help me study. 3.7
SRLSCSUQ 13When reading I try to connect the things, I am reading about with what I already
know.
4
The mean scores in Table 9 highlights that cognitive strategy use items ranged from 3.2 to 4.2. The highest mean
scores (4.2) were recorded for recalling teacher instructions during homework (SRLSCSUQ2) and memorizing
facts for tests (SRLSCSUQ6). Scores of 4.0 were observed for practicing important facts (SRLSCSUQ8), using
prior knowledge for new assignments (SRLSCSUQ9), and connecting new information to prior knowledge
(SRLSCSUQ13). The lowest score (3.2) was recorded for difficulty identifying main ideas in readings
(SRLSCSUQ3). Overall, the findings reflect strong utilization of cognitive strategies for learning among the
respondents.
Table 10 - Mean for (ii) Self-Regulation (9 items)
ITEM MEAN
SRLSSRQ1I ask myself questions to make sure I know the material I have been studying. 3.8
SRLSSRQ 2When work is hard I either give up or study only the easy parts. 3.1
SRLSSRQ 3I work on practice exercises and answer end of chapter questions even when I don't
have to.
3.4
SRLSSRQ 4Even when study materials are dull and uninteresting, I keep working until I finish. 3.6
SRLSSRQ 5Before I begin studying, I think about the things I will need to do to learn. 3.8
SRLSSRQ 6I often find that I have been reading for class but don't know what it is all about. 3.2
I find SRLSSRQ 7that when the teacher is talking, I think of other things and don't really listen
to what is being said.
2.9
SRLSSRQ 8When I'm reading, I stop once in a while and go over what I have read. 3.7
SRLSSRQ 91 work hard to get a good grade even when I don't like a class. 4
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The mean scores for self-regulation items, as denoted in Table 10, ranged from 2.9 to 4.0. The highest mean
score (4.0) was observed for working hard to achieve good grades even in disliked classes (SRLSSRQ9). Scores
of 3.8 were recorded for planning study strategies (SRLSSRQ5) and self-questioning during study (SRLSSRQ1).
The lowest score (2.9) was reported for lack of focus during the teacher's explanations (SRLSSRQ7). Overall,
the findings suggest varying levels of self-regulation among respondents, with strengths in goal-driven effort
and strategic preparation.
Findings for Relationship between motivational beliefs and self-regulated strategies
This section presents data to answer Research Question 4: Is there a relationship between motivational beliefs
and self-regulated strategies? To determine if there is a significant association between the mean scores of
motivational beliefs and self-regulated strategies, the data were analyzed using SPSS for correlations. The results
are presented separately in Tables 11 and 12 below.
Table 11 - Correlation between Motivational Beliefs and Cognitive Strategy Use
Table 11 manifests that there is an association between motivational beliefs and cognitive strategy. Correlation
analysis shows a highly significant association between motivational beliefs and cognitive strategy (r = .698**,
p = .000). According to Jackson (2015), the coefficient is significant at the .05 level, and the positive correlation
is measured on a scale from 0.1 to 1.0. A weak positive correlation is in the range of 0.1 to 0.3, a moderate
positive correlation ranges from 0.3 to 0.5, and a strong positive correlation is from 0.5 to 1.0. This indicates a
strong positive relationship between motivational beliefs and cognitive strategy.
Table 12 - Correlation between Motivational Beliefs and Self- Regulation
Table 12 reveals an association between motivational beliefs and self-regulation. Correlation analysis indicates
a highly significant association between motivational beliefs and self-regulation (r = .562**, p = .000).
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According to Jackson (2015), the coefficient is significant at the .05 level, and positive correlation is measured
on a scale from 0.1 to 1.0. A weak positive correlation ranges from 0.1 to 0.3, a moderate positive correlation
ranges from 0.3 to 0.5, and a strong positive correlation ranges from 0.5 to 1.0. This suggests a strong positive
relationship between motivational beliefs and self-regulation.
CONCLUSION
Summary of Findings and Discussions
5.1.2 RQ 1 (How do learners perceive their motivational beliefs?)
This study examines how learners perceive their motivational beliefs, focusing on self-efficacy, intrinsic value,
and test anxiety. The results show that students generally have moderate to high confidence in their abilities,
strong motivation to learn, and moderate levels of test anxiety. These findings suggest that motivation plays a
key role in students’ learning experiences and performance. For self-efficacy, students felt confident in their
ability to understand course material and perform well. They believed they could learn the subject, but some
lacked confidence when comparing themselves to their peers, especially in study skills. This aligns with
Bandura’s (1997) theory, which suggests that students with higher self-confidence tend to put in more effort and
persist in learning. Similarly, Pintrich and De Groot (1990) found that self-efficacy helps students stay motivated
and use effective learning strategies. In terms of intrinsic value, students showed strong motivation to learn.
They found the subject interesting, useful, and important. Even when they faced difficulties, they were willing
to learn from mistakes. These findings align with Eccles and Wigfield’s (2002) theory, which suggests that
students are more engaged when they see value in what they are learning. Research by Deci and Ryan (2000)
also shows that students with high motivation tend to work harder and perform better. For test anxiety, students
reported moderate levels of worry about exams. Many felt nervous or feared performing poorly, but this anxiety
did not reach extreme levels. Research by Zeidner (1998) suggests that test anxiety can interfere with
concentration and lower performance. While the students in this study did experience some anxiety, proper
support and test-taking strategies could help them manage it better.
RQ 2 (How do learners perceive their use of cognitive strategies?)
The findings indicate that students actively use cognitive strategies to process information and apply self-
regulation techniques, although some areas need improvement. For cognitive strategy use, students frequently
combine information from different sources, recall teacher instructions, and use memorisation techniques to
enhance learning. They also apply prior knowledge to new assignments and organise information in meaningful
ways. However, some students struggle with identifying main ideas in reading materials, which may affect their
comprehension. These results align with Weinstein and Mayer’s (1986) model of cognitive strategies, which
emphasizes the importance of organizing and elaborating on information for better learning outcomes. Similarly,
Pintrich and De Groot (1990) found that students who actively engage in cognitive strategies tend to perform
better academically. Regarding self-regulation, students show strong motivation to complete tasks and achieve
good grades, even in subjects they dislike. They also use planning strategies, such as thinking ahead about study
requirements and asking themselves questions to check understanding. However, some students struggle with
staying focused during lessons and occasionally find themselves reading without understanding the material.
This supports Zimmerman’s (2001) theory of self-regulated learning, which suggests that students who set goals,
monitor their progress, and adjust their strategies are more successful. Additionally, research by Schunk and
Ertmer (2000) highlights that students with strong self-regulation skills are better at managing challenges and
persisting through difficult tasks. Highest cognitive strategy similar to what is suggested by Smit et al. (2017)
also recommended that students should first be trained in using cognitive strategy as using more motivational
strategies may boost a student's effort, it does not necessarily lead to improved achievement.
RQ 3 (Is there a correlation between motivational beliefs and self-regulated strategies?)
The findings indicate a moderately positive correlation between motivational beliefs and self-regulated
strategies, suggesting that students who are more motivated tend to use more cognitive strategies and self-
regulation techniques. The analysis in Table 11 shows a moderately significant correlation (r = .698, p = .000)
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
Page 2752 www.rsisinternational.org
between motivational beliefs and cognitive strategy use. This means that students who believe in their abilities
and value their learning tend to use strategies like organizing information, summarising, and recalling prior
knowledge to enhance understanding. This aligns with Pintrich and De Groot’s (1990) study, which found that
students with strong motivational beliefs engage more in deep learning strategies and perform better
academically. Similarly, Table 12 reveals a moderately significant correlation (r = .562, p = .000) between
motivational beliefs and self-regulation. This suggests that motivated students are more likely to plan their
studies, monitor their progress, and persist through challenges. Zimmerman (2002) emphasised that self-
regulated learners set goals, use strategies to stay on track, and reflect on their performance, all of which
contribute to academic success. Furthermore, Schunk and Ertmer (2000) highlighted that motivation plays a
crucial role in self-regulation, as students who see value in learning are more likely to sustain effort and adopt
effective learning habits.
Pedagogical Implications and Suggestions for Future Research
The findings of this study suggest a moderate correlation between motivational beliefs and self-regulated
learning strategies, which has significant implications for teaching and learning. Educators should focus on
fostering both motivation and self-regulation to enhance student learning outcomes. One key implication is the
need to enhance student motivation through goal-setting exercises, positive feedback, and making learning
materials more relevant. When students see the value in their education and believe in their ability to succeed,
they are more likely to engage in deep learning strategies.
Developing self-regulated learning skills is equally important. Teachers can integrate metacognitive training to
help students monitor their progress, adjust their study strategies, and become more independent learners.
Encouraging students to use learning journals or reflection logs can be an effective way to track their
development. Additionally, assessments should not only focus on correct answers but also reward the use of
effective learning strategies. Schools can also introduce digital tools such as self-paced learning apps, gamified
platforms, and AI-driven personalised feedback systems to support self-regulated learning. Online discussion
forums and collaborative learning environments can further enhance motivation and cognitive engagement.
Despite the strong correlation found in this study, several areas remain unexplored, offering opportunities for
future research. Future researchers could investigate whether early interventions aimed at improving student
motivation lead to long-term academic success. Additionally, studying the influence of cultural, socio-economic,
and institutional factors on the relationship between motivation and self-regulation could provide insights into
how these strategies vary across different learning contexts.
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