The Impact of Student Psychological Factors on Self-Regulation in Learning in Primary Schools

Ratnawati Susanto, Evi Syafrida Nasution, Henny Sanulita, Jitu Halomoan Lumbantoruan

Abstract


Regulation in effective learning can achieve knowledge and understanding of the material. However, in reality in the field, student self-regulation is still low. This is urgent to research because there are differences in theory, expectations, and reality in the field, so the research aims to analyze the influence of psychological factors on elementary school students' regulatory learning. The psychological factors studied are self-efficacy, orientation, and beliefs about intelligence. Quantitative research methods. The subjects were elementary school students with a sample of 639. The data collection technique used an instrument with the Beliefs of Intelligence Scale. Analysis techniques using Statistics version 25.0 with the Pearson correlation r test and Stepwise Multiple Regression analysis were used to analyze the research data. The results and findings show that the Regression Model of intrinsic goal orientation, self-efficacy, and entity trust contributes 31.3% in the good category. Change variance in self-regulated learning. The influence of intrinsic goal orientation is the highest, followed by self-efficacy and entity trust. This self-psychology model contributes to elementary school students' self-regulation learning. In conclusion, self-psychological factors must be considered to produce students who are more independent in independent learning. This research means that schools can shape student psychology independently.

Keywords


Confidence; Efficacy; Learning; Orientation

Full Text:

PDF

References


Akbar, A., & Picard, M. (2020). Academic integrity in the Muslim world: a conceptual map of challenges of culture. International Journal for Educational Integrity, 16(1), 1–20. https://doi.org/10.1007/s40979-020-00060-8

Alshurideh, M. T., Al Kurdi, B., Bettayeb, H., & Turki Alshurideh, M. (2020). The effectiveness of Mobile Learning in UAE Universities: A systematic review of Motivation, Self-efficacy, Usability and Usefulness. Article in International Journal of Control and Automation, 13(2), 1558–1579. https://www.researchgate.net/publication/344878508

Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies in higher education: Fostering digital literacy for sustainable lifelong learning. Education and Information Technologies, 25(4), 2393–2414. https://doi.org/10.1007/s10639-020-10201-8

Ateş, H. (2020). Merging Theory of Planned Behavior and Value Identity Personal norm model to explain pro-environmental behaviors. Sustainable Production and Consumption, 24(1), 169–180. https://doi.org/10.1016/j.spc.2020.07.006

Bakar, A. Y. A., & Mahmud, M. I. (2020). The profiling of aspiration and interest towards STEM and TVET careers among Malaysian school students. Journal for the Education of Gifted Young Scientists, 8(1), 489–500. https://doi.org/10.17478/jegys.669034

Ballesteros, M. Á., Sánchez, J. S., Ratkovich, N., Cruz, J. C., & Reyes, L. H. (2021). Modernizing the chemical engineering curriculum via a student-centered framework that promotes technical, professional, and technology expertise skills: The case of unit operations. Education for Chemical Engineers, 35(December), 8–21. https://doi.org/10.1016/j.ece.2020.12.004

Bates, T. C., Enkhbat, T., Gray, E., Lee, J., & Zakharin, M. (2023). How to get things done: Tight linkage of conscientiousness with twelve mechanisms of Goal Setting Theory. Personality and Individual Differences, 214(March), 112331.12. https://doi.org/10.1016/j.paid.2023.112331

Buenconsejo, J. U., & Alfonso D. Datu, J. (2020). Growth and fixed mindsets about talent matter for career development self-efficacy in selected Filipino adolescents. Children and Youth Services Review, 118(July), 105470.1-6. https://doi.org/10.1016/j.childyouth.2020.105470

Burbules, N. C., Fan, G., & Repp, P. (2020). Five trends of education and technology in a sustainable future. Geography and Sustainability, 1(2), 93–97. https://doi.org/10.1016/j.geosus.2020.05.001

Burić, I., & Kim, L. E. (2020). Teacher self-efficacy, instructional quality, and student motivational beliefs: An analysis using multilevel structural equation modeling. Learning and Instruction, 66, 1-51. https://doi.org/10.1016/j.learninstruc.2019.101302

Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1(July), 100002.1-20. https://doi.org/10.1016/j.caeai.2020.100002

Chiu, T. K. F. (2021). Digital support for student engagement in blended learning based on self-determination theory. Computers in Human Behavior, 124(March), 106909.1-10. https://doi.org/10.1016/j.chb.2021.106909

Corte, A. P. D., Souza, D. V., Rex, F. E., Sanquetta, C. R., Mohan, M., Silva, C. A., Zambrano, A. M. A., Prata, G., Alves de Almeida, D. R., Trautenmüller, J. W., Klauberg, C., de Moraes, A., Sanquetta, M. N., Wilkinson, B., & Broadbent, E. N. (2020). Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes. Computers and Electronics in Agriculture, 179(2), 1–17. https://doi.org/10.1016/j.compag.2020.105815

De Backer, L., Van Keer, H., De Smedt, F., Merchie, E., & Valcke, M. (2022). Identifying regulation profiles during computer-supported collaborative learning and examining their relation with students’ performance, motivation, and self-efficacy for learning. Computers and Education, 179, 1–14. https://doi.org/10.1016/j.compedu.2021.104421

De Martino, M., Gushchina, Y. S., Boyko, Z. V., Magnanini, A., Sandor, I., Guerrero Perez, B. A., & Isidori, E. (2020). Self-Organisation in Lifelong Learning: Theory, Practice and Implementation Experience Involving Social Networks and a Remote Format. RUDN Journal of Psychology and Pedagogics, 17(3), 373–389. https://doi.org/10.22363/2313-1683-2020-17-3-373-389

dos Santos, R. S. (2020). Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data. International Journal of Applied Earth Observation and Geoinformation, 88(October 2018), 102066.1-10. https://doi.org/10.1016/j.jag.2020.102066

Duque, E., Gairal, R., Molina, S., & Roca, E. (2020). How the Psychology of Education Contributes to Research With a Social Impact on the Education of Students With Special Needs: The Case of Successful Educational Actions. Frontiers in Psychology, 11(March), 1-16. https://doi.org/10.3389/fpsyg.2020.00439

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., Raman, R., Rana, N. P., Sharma, S. K., & Upadhyay, N. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 1-40. https://doi.org/10.1016/j.ijinfomgt.2020.102211

Fraser, K., Tseng, T. L. B., & Deng, X. (2018). The ongoing education of engineering practitioners: how do they perceive the usefulness of academic research? European Journal of Engineering Education, 43(6), 860–878. https://doi.org/10.1080/03043797.2018.1450847

Freedberg, D. E., Conigliaro, J., Wang, T. C., Tracey, K. J., Callahan, M. V., Abrams, J. A., Sobieszczyk, M. E., Markowitz, D. D., Gupta, A., O’Donnell, M. R., Li, J., Tuveson, D. A., Jin, Z., Turner, W. C., & Landry, D. W. (2020). Famotidine Use Is Associated With Improved Clinical Outcomes in Hospitalized COVID-19 Patients: A Propensity Score Matched Retrospective Cohort Study. Gastroenterology, 159(3), 1129-1131.e3. https://doi.org/10.1053/j.gastro.2020.05.053

Hertel, S., Reschke, K., & Karlen, Y. (2024a). Are profiles of self-regulated learning and intelligence mindsets related to students’ self-regulated learning and achievement? Learning and Instruction, 90(December 2023), .1-19. https://doi.org/10.1016/j.learninstruc.2023.101850

Hertel, S., Reschke, K., & Karlen, Y. (2024b). Are profiles of self-regulated learning and intelligence mindsets related to students’ self-regulated learning and achievement? Learning and Instruction, 90(December 2023), 101850.1-19. https://doi.org/10.1016/j.learninstruc.2023.101850

Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1(2), 1–5. https://doi.org/10.1016/j.caeai.2020.100001

Iivari, N., Sharma, S., & Ventä-Olkkonen, L. (2020). Digital transformation of everyday life – How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? International Journal of Information Management, 55(June), 102183.1-6. https://doi.org/10.1016/j.ijinfomgt.2020.102183

Ilishkina, D. I., de Bruin, A., Podolskiy, A. I., Volk, M. I., & van Merriënboer, J. J. G. (2022). Understanding self-regulated learning through the lens of motivation: Motivational regulation strategies vary with students’ motives. International Journal of Educational Research, 113(February), 1–14. https://doi.org/10.1016/j.ijer.2022.101956

Jeno, L. M., Dettweiler, U., & Grytnes, J. A. (2020). The effects of a goal-framing and need-supportive app on undergraduates’ intentions, effort, and achievement in mobile science learning. Computers and Education, 159(January), 104022.1-14. https://doi.org/10.1016/j.compedu.2020.104022

Katawazai, R. (2021). Implementing outcome-based education and student-centered learning in Afghan public universities: the current practices and challenges. Heliyon, 7(5), e07076.1-16. https://doi.org/10.1016/j.heliyon.2021.e07076

Kim, M. H., & Beier, M. E. (2020). The college-to-career transition in STEM: An eleven-year longitudinal study of perceived and objective vocational interest fit. Journal of Vocational Behavior, 123(November), 1-48. https://doi.org/10.1016/j.jvb.2020.103506

Krupiy, T. (Tanya). (2020). A vulnerability analysis: Theorising the impact of artificial intelligence decision-making processes on individuals, society and human diversity from a social justice perspective. Computer Law and Security Review, 38(2), 105429.1-25. https://doi.org/10.1016/j.clsr.2020.105429

Kryshko, O., Fleischer, J., Grunschel, C., & Leutner, D. (2022). Self-efficacy for motivational regulation and satisfaction with academic studies in STEM undergraduates: The mediating role of study motivation. Learning and Individual Differences, 93(November 2021), 102096.1-12. https://doi.org/10.1016/j.lindif.2021.102096

Li, J., King, R. B., Wang, Y., Leung, S. O., & Wang, C. (2023). Students’ and schools’ expectancy-value beliefs are associated with reading achievement: A cross-cultural study. Learning and Individual Differences, 106(August), 102344.1-11. https://doi.org/10.1016/j.lindif.2023.102344

Martínez-López, Z., Nouws, S., Villar, E., Mayo, M. E., & Tinajero, C. (2023). Perceived social support and self-regulated learning: A systematic review and meta-analysis. International Journal of Educational Research Open, 5(March), 1-12. https://doi.org/10.1016/j.ijedro.2023.100291

Miao, J., & Ma, L. (2023). Teacher Autonomy Support Influence on Online Learning Engagement: The Mediating Roles of Self-Efficacy and Self-Regulated Learning. SAGE Open, 13(4), 1–13. https://doi.org/10.1177/21582440231217737

Murshidi, G. Al, Daoud, S., Derei, R. Al, Alhamidi, H., Jabir, W., & Sayed, N. (2023). Parental involvement in English as foreign language learners’ education: Challenges and solutions in a post-pandemic era. International Journal of Educational Research Open, 5(June), 100297.1-7. https://doi.org/10.1016/j.ijedro.2023.100297

Omari, O., Moubtassime, M., & Ridouani, D. (2020). Factors affecting students’ self-efficacy beliefs in moroccan higher education. Journal of Language and Education, 6(3), 108–124. https://doi.org/10.17323/jle.2020.9911

P, C. W. T. M. R. C., Path, F. R. C., Pock, L., & Ho, F. R. C. P. A. (2020). Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19 . The COVID-19 resource centre is hosted on Elsevier Connect , the company ’ s public news and information. Nutrition, 79(January), 1–4.

Rodríguez, S., González-Suárez, R., Vieites, T., Piñeiro, I., & Díaz-Freire, F. M. (2022). Self-Regulation and Students Well-Being: A Systematic Review 2010–2020. Sustainability (Switzerland), 14(4), 1-22. https://doi.org/10.3390/su14042346

Salikhova, N. R., Lynch, M. F., & Salikhova, A. B. (2020). Psychological aspects of digital learning: A self-determination theory perspective. Contemporary Educational Technology, 12(2), 1–13. https://doi.org/10.30935/cedtech/8584

Savkov, A., Suray, I., Kotliar, L., Polishchuk, L., Bushman, I., & Vasiuk, N. (2020). Stem education as the latest philosophy of lifelong learning to develop key competencies of a civil servant. International Journal of Management, 11(2), 163–169. https://doi.org/10.34218/IJM.11.2.2020.017

Scherer, R., & Campos, D. G. (2022). Measuring those who have their minds set: An item-level meta-analysis of the implicit theories of intelligence scale in education. Educational Research Review, 37(August), 100479.1-20. https://doi.org/10.1016/j.edurev.2022.100479

Schunk, D. H., & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. Advances in Motivation Science, 8(December), 153–179. https://doi.org/10.1016/bs.adms.2020.10.001

Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2020). Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation. Computers in Human Behavior, 107, 105512.1-16. https://doi.org/10.1016/j.chb.2018.05.004

Shafiee, S., Lied, L. M., Burud, I., Dieseth, J. A., Alsheikh, M., & Lillemo, M. (2021). Sequential forward selection and support vector regression in comparison to LASSO regression for spring wheat yield prediction based on UAV imagery. Computers and Electronics in Agriculture, 183(1432), 106036.1-9. https://doi.org/10.1016/j.compag.2021.106036

Shang, C., Moss, A. C., & Chen, A. (2023). The expectancy-value theory: A meta-analysis of its application in physical education. Journal of Sport and Health Science, 12(1), 52–64. https://doi.org/10.1016/j.jshs.2022.01.003

Shi, J., van der Maas, M., Yu, L., Jiang, Q., Agasee, S., & Turner, N. E. (2022). Current prevention strategies and future directions for problem Internet use. Current Opinion in Behavioral Sciences, 48(November 2022), 1–11. https://doi.org/10.1016/j.cobeha.2022.101231

Smit, K., de Brabander, C. J., Boekaerts, M., & Martens, R. L. (2017). The self-regulation of motivation: Motivational strategies as mediator between motivational beliefs and engagement for learning. International Journal of Educational Research, 82(2), 124–134. https://doi.org/10.1016/j.ijer.2017.01.006

Thiermann, U. B., & Sheate, W. R. (2020). Motivating individuals for social transition: The 2-pathway model and experiential strategies for pro-environmental behaviour. Ecological Economics, 174(March), 106668.1-12. https://doi.org/10.1016/j.ecolecon.2020.106668

Tuominen, H., Niemivirta, M., Lonka, K., & Salmela-Aro, K. (2020). Motivation across a transition: Changes in achievement goal orientations and academic well-being from elementary to secondary school. Learning and Individual Differences, 79(August 2019), 101854.1-15. https://doi.org/10.1016/j.lindif.2020.101854

Tusianah, R., Sutarsyah, C., Sukirlan, M., Ridwan, R., Nurmalisa, Y., Isnainy, U. C. A. S., Maydiantoro, A., Zainaro, M. A., & Kesuma, T. A. R. P. (2021). An integrative review of self-efficacy: What factors enhance and impair it? WSEAS Transactions on Business and Economics, 18(2), 1057–1072. https://doi.org/10.37394/23207.2021.18.100

Van den Beemt, A., MacLeod, M., Van der Veen, J., Van de Ven, A., van Baalen, S., Klaassen, R., & Boon, M. (2020). Interdisciplinary engineering education: A review of vision, teaching, and support. Journal of Engineering Education, 109(3), 508–555. https://doi.org/10.1002/jee.20347

van Lent, M., & Souverijn, M. (2020). Goal setting and raising the bar: A field experiment. Journal of Behavioral and Experimental Economics, 87(December 2019), 101570.1-16. https://doi.org/10.1016/j.socec.2020.101570

Vosniadou, S., Lawson, M. J., Wyra, M., Van Deur, P., Jeffries, D., & I Gusti Ngurah, D. (2020). Pre-service teachers’ beliefs about learning and teaching and about the self-regulation of learning: A conceptual change perspective. International Journal of Educational Research, 99(October 2019), 1-17. https://doi.org/10.1016/j.ijer.2019.101495

Wahono, B., Lin, P. L., & Chang, C. Y. (2020). Evidence of STEM enactment effectiveness in Asian student learning outcomes. International Journal of STEM Education, 7(1), 1–18. https://doi.org/10.1186/s40594-020-00236-1

Wilkins, L., Dunn, A., Zoob Carter, B. N., & Boardley, I. D. (2022). Exploring the relationship between mindset and psychological factors linked to doping. Performance Enhancement and Health, 10(4), 100238.1-9. https://doi.org/10.1016/j.peh.2022.100238

Woods, P. J., & Copur-Gencturk, Y. (2024). Examining the role of student-centered versus teacher-centered pedagogical approaches to self-directed learning through teaching. Teaching and Teacher Education, 138(March 2023), 104415.1-16. https://doi.org/10.1016/j.tate.2023.104415

Xia, Q., Chiu, T. K. F., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers and Education, 189(2), 1–41. https://doi.org/10.1016/j.compedu.2022.104582

Xu, Z., Zhao, Y., Liew, J., Zhou, X., & Kogut, A. (2023). Synthesizing research evidence on self-regulated learning and academic achievement in online and blended learning environments: A scoping review. Educational Research Review, 39(December 2022), 100510.1-17. https://doi.org/10.1016/j.edurev.2023.100510

Yang, Q. F., Chang, S. C., Hwang, G. J., & Zou, D. (2020). Balancing cognitive complexity and gaming level: Effects of a cognitive complexity-based competition game on EFL students’ English vocabulary learning performance, anxiety and behaviors. Computers and Education, 148(January), 103808.1-21. https://doi.org/10.1016/j.compedu.2020.103808

Zheng, J., Xing, W., Zhu, G., Chen, G., Zhao, H., & Xie, C. (2020). Profiling self-regulation behaviors in STEM learning of engineering design. Computers and Education, 143(August 2019), 1-13. https://doi.org/10.1016/j.compedu.2019.103669




DOI: https://doi.org/10.53400/mimbar-sd.v11i1.68907

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2024 Mimbar Sekolah Dasar

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

View Mimbar Sekolah Dasar Stats