Effects of the Self-Regulated Learning and Motivation on Learning Achievements of the Programming Courses
DOI:
https://doi.org/10.58459/icce.2024.4973Abstract
This study investigated the impact of self-regulated learning (SRL) motivation and strategies on academic performance in a programming course using learning analytics techniques. Data were collected from 250 students, including their coding behaviors, SRL motivations, and strategies. K-means clustering was applied to categorize students into two distinct groups based on SRLmotivation, SRLstrategy, code_copy, code_execution, code_speed, code_paste, and code_length, with the silhouette coefficient confirming the optimal number of clusters. Subsequent analysis revealed significant differences in the academic performance of the two clusters. Structural Equation Modeling (SEM) was employed to examine the mediating role of SRL motivation between SRL strategies and academic performance. The model demonstrated a good fit (AGFI = 0.927, CFI = 0.964, RMSEA = 0.067), confirming the reliability of the proposed relationships. Bootstrap tests further validated the mediating effect of SRL motivation. Our findings indicate that SRL strategies positively influence academic performance both directly and through SRL motivation, establishing a partial mediation effect. This research contributes to the understanding of SRL in online learning environments, highlighting the importance of motivation and strategic learning behaviors for enhancing student outcomes. The implications for designing effective educational interventions and fostering self-regulated learning practices are discussed.