Effects of Environmental Management on Students’ Learning Strategies

Learning strategies are crucial for language acquisition, skill improvement, and overall mastery. Effective learning is highly dependent on environmental management, a strategy in which learners organize their physical and social surroundings to reduce distractions and increase learning effectiveness. Despite its importance, the specific mechanisms through which the learning environment influences a learner's choice of strategies remain under-explored. Furthermore, the application of these effective learning strategies receives insufficient attention from researchers and remains ambiguous in current literature. Hence, this study aims to examine the influence of environmental management on students' learning strategies, specifically its relationship with cognitive strategies, metacognitive self-regulation, and resource management. This study employed a quantitative survey, collecting data via a 5-point Likert scale instrument, which is divided into 3 main sections, focusing on: cognitive components, metacognitive self-regulation and resource management. The sample involved 286 respondents from University Technology MARA Selangor, comprising elementary and intermediate Japanese language students from science and technology, social sciences, and business academic backgrounds. The findings clearly show that students actively utilize cognitive, metacognitive, and resource management strategies. Statistical analyses also revealed a strong, positive, and significant relationship between environmental management and cognitive components, metacognitive self-regulation, and resource management. Ultimately, these findings offer theoretical implications by expanding existing knowledge on self-regulated learning environments. They also provide practical insights for educators and institutions to design, manage, and organize activities that promote more strategic and effective teaching and learning.

learning strategies, environment, cognitive, metacognitive, self-regulation

1. Abdelouahed, L. (2019). The use of e-learning in foreign language learning: A case study of undergraduate EFL students. International Journal of Language and Literacy Studies, 1(3), 30–42. https://doi.org/10.36892/ijlls.vli3.79 [Google Scholar] [Crossref]

2. Ahmad, N., Alias, F. A., Hamat, M., & Mohamed, S. A. (2024). Reliability analysis: Application of Cronbach’s alpha in research instruments. SIG: e-Learning @CS, 114–119. https://appspenang.uitm.edu.my/sigcs/ [Google Scholar] [Crossref]

3. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191 [Google Scholar] [Crossref]

4. Bandura, A. (1986). Social foundations of thought and theory: A social cognitive theory. Prentice-Hall. https://psycnet.apa.org/record/1985-98423-000 [Google Scholar] [Crossref]

5. Dorman, J. P. (2008). Classroom environment research: Progress and possibilities. Queensland Journal of Educational Research, 24(2), 112–140. [Google Scholar] [Crossref]

6. Finders, J., Wilson, E., & Duncan, R. (2023). Early childhood education language environments: Considerations for research and practice. Frontiers in Psychology, 14, Article 1202819. https://doi.org/10.3389/fpsyg.2023.1202819 [Google Scholar] [Crossref]

7. Fraser, B. J. (2012). Classroom learning environments: Retrospect, context and prospect. In B. J. Fraser, K. G. Tobin, & C. J. McRobbie (Eds.), Second international handbook of science education (pp. 1191–1239). Springer. [Google Scholar] [Crossref]

8. He, L. (2024). The application of SPSS correlation analysis in the study of precision teaching of English in universities. Applied Mathematics and Nonlinear Science, 9(1), 1–13. https://doi.org/10.2478/amns-2024-1371 [Google Scholar] [Crossref]

9. Moos, R. H. (1974). Family Environment Scale (FES) [Database record]. APA PsycTests. https://doi.org/10.1037/t27699-000 [Google Scholar] [Crossref]

10. Nickerson, C. (2025). Albert Bandura's social cognitive theory. Simply Psychology. https://www.simplypsychology.org/bandura-social-cognitive-theory.html [Google Scholar] [Crossref]

11. Organization for Economic Co-operation and Development (OECD). (2019). PISA 2018 results (Volume III): What school life means for students’ lives. OECD Publishing. [Google Scholar] [Crossref]

12. Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385–407. https://doi.org/10.1007/s10648-004-0006-x [Google Scholar] [Crossref]

13. Rahmat, N. H., & Thasrabiab, T. (2024). Exploring motivation and self-regulation from the social cognitive view. International Journal of Academic Research in Business & Social Science, 14(1), 3276–3290. https://doi.org/10.6007/IJARBSS/v14-i1/20476 [Google Scholar] [Crossref]

14. Ramlee, M., Seri, B., Saemah, R., Yusof, H. M., & Rahayu, A. B. (2014). Environmental factors and students’ learning approaches: A survey on Malaysian polytechnics students. Journal of Education and Learning, 8(4), 387–398. [Google Scholar] [Crossref]

15. Tabinas, A. M., Panuncio, J. A. R., & Salvo, D. M. M. T. (2023). Learning strategies, motivation, and its relationship to the online learning environment among college students. [Insert Journal Name Here], [Volume]([Issue]), [Pages]. [Insert DOI/URL] [Google Scholar] [Crossref]

16. Vetter, T. R. (2017). Descriptive statistics: Reporting the answers to the 5 basic questions of who, what, why, when, where, and a sixth, so what? Anesthesia & Analgesia, 125(5), 1797–1802. https://doi.org/10.1213/ane.0000000000002471 [Google Scholar] [Crossref]

17. Wenden, A., & Rubin, J. (1987). Learner strategies in language learning. Prentice Hall. [Google Scholar] [Crossref]

18. Wolters, C. A. (2003). Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist, 38(4), 189–205. https://doi.org/10.1207/S15326985EP3804_1 [Google Scholar] [Crossref]

19. Yang, Y., Du, J., Teo, T., Xue, S., & Lui, F. (2023). Effects of goal orientation on environment management in technology-based physics learning. Frontiers in Psychology, 13, Article 1048143. https://doi.org/10.3389/fpsyg.2022.1048143 [Google Scholar] [Crossref]

20. Ziegenfuss, J. Y., Casey, A. E., Jennifer, M. D., Meghan, M. J., Thomas, E. K., & Marna, C. (2021). Impact of demographic survey questions on response rate and measurement: A randomized experiment. Survey Practice, 14(1). https://doi.org/10.29115/SP-2021-0010 [Google Scholar] [Crossref]

21. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2 [Google Scholar] [Crossref]

• Employee Training Efficacy in Banking Sector
• Multidimensional Predictors of University Students’ Examination Performance: A Quantitative Analysis of Psychological, Environmental, And Skill-Based Factors
• Digital Learning Innovation: Evaluating the Effectiveness of MOOC and Politicbox in Enhancing Students Understanding
• An Investigation of Group Work through Mcclelland’s Theory
• The Impact of a Practical Flipped Process-Genre Writing Model on Moroccan EFL High School Students’ Writing Performance