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Abstract
The ability to properly evaluate one’s own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in enhancing mathematics learning, particularly in programming-based contexts. Focusing on two components of SRL, self-awareness and reflection, the study provides empirical evidence on the psychological effectiveness of SRL in academic outcomes through the implementation of an e-portfolio-based intervention. Using Bayesian inference, the study models individual learning processes, offering personalized insights for effective educational interventions. The analysis reveals that the use of e-portfolios significantly fosters self-awareness and enhances learning among students. Nevertheless, the study also addresses psychological challenges in programming-based mathematical education, such as complex problem-solving and abstract thinking. The findings highlight the need for interactive, technology-enhanced teaching approaches to keep university-level students engaged and motivated. Key psychological implications are discussed for relevant measures in mathematics education.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
PEDAGOGICAL RES, Volume 10, Issue 1, January 2025, Article No: em0233
https://doi.org/10.29333/pr/15682
Publication date: 01 Jan 2025
Online publication date: 04 Dec 2024
Article Views: 193
Article Downloads: 106
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