Analysis of Self-Regulated Learning Elements in Introductory Computer Programming
DOI:
https://doi.org/10.53840/myjict9-1-174Keywords:
Self-Regulated Learning, introductory computer programming, programmingAbstract
This paper presents analysis for self-regulated learning (SRL) element in the context of introductory computer programming courses. SRL is a critical skill for students to develop as it enables them to take control of their learning process and become more effective learners. The proposed elements are based on insights from educators and experts in the field. The findings of this analysis provide valuable guidance for educators looking to integrate SRL principles and elements into introductory computer programming courses. Additionally, the analysis highlights the importance of considering the diverse needs and backgrounds of students in the design of SRL interventions.
Downloads
References
Çakiroğlu, Ü., & Öztürk, M. (2017). Flipped classroom with problem based activities: Exploring self-regulated learning in a programming language course. Educational Technology and Society, 20(1), 337–349.
Castellanos, H., Restrepo-Calle, F., González, F. A., & Echeverry, J. J. R. (2017). Understanding the relationships between self-regulated learning and students source code in a computer programming course. Proceedings - Frontiers in Education Conference, FIE, 2017-Octob(April 2020), 1–9. https://doi.org/10.1109/FIE.2017.8190467
Cheng, G., Poon, L. K. M., Lau, W. W. F., & Zhou, R. C. (2019). Exploring The Relationship Between Self-Regulated Learning Strategies And Computer Programming Achievement In Higher Education. 5, 67–74. https://doi.org/10.17501/24246700.2019.5108
Cigdem, H. (2020). How Does Self-Regulation Affect Computer-Programming Achievement in a Blended Context? Contemporary Educational Technology, 6(1), 19–37. https://doi.org/10.30935/cedtech/6137
Garcia, M. B. (2021). Cooperative learning in computer programming: A quasi-experimental evaluation of Jigsaw teaching strategy with novice programmers. Education and Information Technologies, 26(4). https://doi.org/10.1007/s10639-021-10502-6
Garcia, R., Falkner, K., & Vivian, R. (2018). Systematic literature review: Self-Regulated Learning strategies using e-learning tools for Computer Science. Computers and Education, 123, 150–163. https://doi.org/10.1016/j.compedu.2018.05.006
Lishinski, A., & Yadav, A. (2021). Self-evaluation Interventions: Impact on Self-efficacy. ACM Transactions on Computing Education, 21(3).
Loksa, D., & Ko, A. J. (2016). The role of self-regulation in programming problem solving process and success. ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research. https://doi.org/10.1145/2960310.2960334
Pedrosa, D., Cravino, J., Morgado, L., Barreira, C., Nunes, R. R., Martins, P., & Paredes, H. (2016). Simprogramming: the Development of an Integrated Teaching Approach for Computer Programming in Higher Education. INTED2016 Proceedings, 1(April), 7162–7172. https://doi.org/10.21125/inted.2016.0699
Puustinen, M., & Pulkkinen, L. (2001). Models of Self-regulated Learning: A review. Scandinavian Journal of Educational Research, 45(3), 269–286. https://doi.org/10.1080/00313830120074206
Song, D., Hong, H., & Oh, E. Y. (2021). Applying computational analysis of novice learners’ computer programming patterns to reveal self-regulated learning, computational thinking, and learning performance. Computers in Human Behavior, 120, 106746.
Tsai, C. Y. (2019). Improving students’ understanding of basic programming concepts through visual programming language: The role of self-efficacy. Computers in Human Behavior, 95, 224–232. https://doi.org/10.1016/j.chb.2018.11.038
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Malaysian Journal of Information and Communication Technology (MyJICT)
This work is licensed under a Creative Commons Attribution 4.0 International License.
