Enter your email address
Submit
Write your message
Volume 23, Issue 143 (12-2024)
Journal of Psychological Science 2024, 23(143): 345-358 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Mahmoud Alaki M S, Hassani M. (2024). The Role of Self-Regulated Learning Strategies in Predicting Students’ Learning Attitudes and Metacognitive Skills in Biology: The Mediating Role of Motivational Beliefs. Journal of Psychological Science. 23(143), 345-358. doi:10.61186/jps.23.143.345
URL: http://psychologicalscience.ir/article-1-2720-en.html
URL: http://psychologicalscience.ir/article-1-2720-en.html
Department of Educational Sciences, Urmia University, Urmia, Iran. , basicsci38@uodiyala.edu.iq
Abstract: (74 Views)
Background: Students’ learning attitudes and metacognitive skills are considered crucial determinants of effective biology learning. While self-regulated learning strategies and motivational beliefs can play a pivotal role in reinforcing these two components, empirical evidence simultaneously examining these constructs among biology students in Baqubah, Diyala Governorate, remains scarce.
Aims: The present study aimed to examine the role of self-regulated learning strategies in predicting students’ learning attitudes and metacognitive skills in biology, with the mediating role of motivational beliefs.
Methods: This study employed a descriptive-correlational research design. The statistical population comprised all biology students in Diyala–Baqubah (N=4,500), from which a sample of 357 students was selected using cluster random sampling based on Krejcie and Morgan’s (1970) formula. Data collection was conducted using the Motivational Beliefs Questionnaire (Pintrich et al., 1991), the Self-Regulated Learning Strategies and Metacognitive Skills Questionnaire (Pintrich & De Groot, 1990), and the Learning Attitude Scale (Akpinar et al., 2009). The hypotheses were tested using Pearson correlation and structural equation modeling (SEM) via SPSS (Version 24) and AMOS (Version 23).
Results: Structural equation modeling results indicated that self-regulated learning strategies had a direct and significant effect on students’ learning attitudes and metacognitive skills in biology (p<.001). Furthermore, the direct effect of self-regulated learning strategies on motivational beliefs, as well as the direct effect of motivational beliefs on both learning attitudes and metacognitive skills, was positive and statistically significant (p<.001). Moreover, bootstrap analysis demonstrated that motivational beliefs significantly mediated the relationship between self-regulated learning strategies and learning attitudes (β=.256), as well as metacognitive skills (β=.268).
Conclusion: The findings suggest that the implementation of self-regulated learning strategies not only directly reinforces students’ learning attitudes and advances their metacognitive skills in biology, but also deepens this process through the activation and enhancement of motivational beliefs. Therefore, incorporating self-regulated learning instruction into biology curricula can provide an effective framework for fostering learners’ scientific attitudes and metacognitive capabilities.
Aims: The present study aimed to examine the role of self-regulated learning strategies in predicting students’ learning attitudes and metacognitive skills in biology, with the mediating role of motivational beliefs.
Methods: This study employed a descriptive-correlational research design. The statistical population comprised all biology students in Diyala–Baqubah (N=4,500), from which a sample of 357 students was selected using cluster random sampling based on Krejcie and Morgan’s (1970) formula. Data collection was conducted using the Motivational Beliefs Questionnaire (Pintrich et al., 1991), the Self-Regulated Learning Strategies and Metacognitive Skills Questionnaire (Pintrich & De Groot, 1990), and the Learning Attitude Scale (Akpinar et al., 2009). The hypotheses were tested using Pearson correlation and structural equation modeling (SEM) via SPSS (Version 24) and AMOS (Version 23).
Results: Structural equation modeling results indicated that self-regulated learning strategies had a direct and significant effect on students’ learning attitudes and metacognitive skills in biology (p<.001). Furthermore, the direct effect of self-regulated learning strategies on motivational beliefs, as well as the direct effect of motivational beliefs on both learning attitudes and metacognitive skills, was positive and statistically significant (p<.001). Moreover, bootstrap analysis demonstrated that motivational beliefs significantly mediated the relationship between self-regulated learning strategies and learning attitudes (β=.256), as well as metacognitive skills (β=.268).
Conclusion: The findings suggest that the implementation of self-regulated learning strategies not only directly reinforces students’ learning attitudes and advances their metacognitive skills in biology, but also deepens this process through the activation and enhancement of motivational beliefs. Therefore, incorporating self-regulated learning instruction into biology curricula can provide an effective framework for fostering learners’ scientific attitudes and metacognitive capabilities.
Keywords: Learning attitude, metacognitive skill, self-regulation learning strategy, motivational beliefs
Type of Study: Research |
Subject:
General
Received: 2024/12/7 | Accepted: 2024/12/20 | Published: 2024/12/25
Received: 2024/12/7 | Accepted: 2024/12/20 | Published: 2024/12/25
References
1. اصولی، اعظم و شریعتمدار، آسیه و کلانترهرمزی، آتوسا. (1395). بررسی رابطه باورهای فراشناخت با خودتنظیمی تحصیلی وتعارض والد نوجوان، فصلنامه فرهنگ مشاوره و روان درمانی، 7(27)، 83-104. https://doi.org/10.22054/qccpc.2016.6726.
2. Akpınar, E., Yıldız, E., Tatar, N., & Ergin, Ö. (2009). Students’ attitudes toward science and technology: An investigation of elementary students. Elementary Education Online, 8(1), 40–53. https://doi.org/10.1016/j.sbspro.2009.01.498
3. Azevedo, R. (2020). Reflections on the field of metacognition: issues, challenges, and opportunities: Reflections on the field of metacognition: issues, challenges, and opportunities. Metacognition and Learning, 15(2), 91-98. https://doi.org/10.1007/s11409-020-09231-x
4. Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual review of psychology, 53(1), 109-132. https://doi.org/10.1146/annurev.psych.53.100901.135153
5. Fleming, S. M. (2024). Metacognition and confidence: A review and synthesis. Annual Review of Psychology, 75, 241–268. https://doi.org/10.1146/annurev-psych-022423-032425
6. Fleur, D. S., Bredeweg, B., & van den Bos, W. (2021). Metacognition: ideas and insights from neuro-and educational sciences. npj Science of Learning, 6(1), 13. https://doi.org/10.1038/s41539-021-00089-5
7. Heyes, C., Bang, D., Shea, N., Frith, C. D., & Fleming, S. M. (2020). Knowing ourselves together: The cultural origins of metacognition. Trends in Cognitive Sciences, 24(5), 349–362. https://doi.org/10.1016/j.tics.2020.02.007
8. Kingir, S., Tas, Y., Gok, G., & Vural, S. S. (2013). Relationships among constructivist learning environment perceptions, motivational beliefs, self-regulation and science achievement. Research in Science & Technological Education, 31(3), 205–226. https://doi.org/10.1080/02635143.2013.825594
9. Li, J., Lin, Y., Sun, M., & Shadiev, R. (2023). Socially shared regulation of learning in game-based collaborative learning environments promotes algorithmic thinking, learning participation and positive learning attitudes. Interactive Learning Environments, 31(3), 1715–1726. https://doi.org/10.1080/10494820.2020.1857783
10. Loksa, D., Margulieux, L., Becker, B. A., Craig, M., Denny, P., Pettit, R., & Prather, J. (2022). Metacognition and self-regulation in programming education: Theories and exemplars of use. ACM Transactions on Computing Education (TOCE), 22(4), 1-31. https://doi.org/10.1145/3487050
11. Norman, E., Pfuhl, G., Sæle, R. G., Svartdal, F., Låg, T., & Dahl, T. I. (2019). Metacognition in psychology. Review of General Psychology, 23(4), 403–424. https://doi.org/10.1177/1089268019883821
12. Osakwe, I., Chen, G., Fan, Y., Rakovic, M., Singh, S., Lim, L., ... & Gašević, D. (2024). Towards prescriptive analytics of self‐regulated learning strategies: A reinforcement learning approach. British Journal of Educational Technology, 55(4), 1747-1771. https://doi.org/10.1111/bjet.13429
13. Osoli, A., Sharat Madar, A., & Kalantar, A. (2016). The relationship between metacognitive beliefs with academic self-regulation and parents-adolesent conflict. Counseling and psychotherapy culture, 7(27), 83-104.(in persian). https://doi.org/10.22054/qccpc.2016.6726
14. Pintrich, P. R., & Schragben, B. (2012). Students' motivational beliefs and their cognitive engagement in classroom academic tasks. In Student perceptions in the classroom (pp. 149-184). Routledge.
15. Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40. https://doi.org/10.1037/0022-0663.82.1.33
16. Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ) (Technical Report No. 91-B-004). National Center for Research to Improve Postsecondary Teaching and Learning (NCRIPTAL), The University of Michigan. https://files.eric.ed.gov/fulltext/ED338122.pdf
17. Prather, J., Becker, B. A., Craig, M., Denny, P., Loksa, D., & Margulieux, L. (2020, August). What do we think we think we are doing? Metacognition and self-regulation in programming. In Proceedings of the 2020 ACM conference on international computing education research (pp. 2-13). https://doi.org/10.1145/3372782.3406263
18. Rodriguez-Gomez, D., Muñoz-Moreno, J. L., & Ion, G. (2024). Empowering teachers: Self-regulated learning strategies for sustainable professional development in initial teacher education at higher education institutions. Sustainability, 16(7), 3021. https://doi.org/10.3390/su16073021
19. Rominger, C., & Schwerdtfeger, A. R. (2024). The misjudgment of interoceptive awareness: Systematic overrating of interoceptive awareness among individuals with lower interoceptive metacognitive skills. Consciousness and Cognition, 117, 103621. https://doi.org/10.1016/j.concog.2023.103621
20. Russo, T., & Benson, S. (2005). Learning with invisible others: Perceptions of online presence and their relationship to cognitive and affective learning. Journal of Educational Technology & Society, 8(1), 54-62.
21. Yassin, E. (2024). Examining the relation of open thinking, critical thinking, metacognitive skills and usage frequency of open educational resources among high school students. Thinking Skills and Creativity, 52, 101506. https://doi.org/10.1016/j.tsc.2024.101506
22. Zalbidea, J. (2024). Variability in heritage and second language writers’ linguistic complexity: Roles of proficiency and motivational beliefs. Studies in Second Language Acquisition, 46(2), 330-353. https://doi.org/10.1017/S027226312300058X
23. Zhou, S., Thompson, G., & Zhou, S. (2024). Transitioning from secondary school to an English-medium transnational university in China: A longitudinal study of student self-efficacy and motivational beliefs. International Journal of Bilingual Education and Bilingualism, 27(4), 487-500. https://doi.org/10.1080/13670050.2023.2213376
24. Zhu, Y., Zhang, J. H., Au, W., & Yates, G. (2020). University students’ online learning attitudes and continuous intention to undertake online courses: A self-regulated learning perspective. Educational technology research and development, 68(3), 1485-1519. https://doi.org/10.1007/s11423-020-09753-w
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)