The Impact of Self-Regulated Learning Behaviors on Cognitive Load and Academic Performance in Online Learning Environments

Abstract

The purpose of this study is to investigate the impact of college students' self-regulation abilities on cognitive load and learning proficiency within online learning environments. A sample of 160 undergraduate students was selected for this research, with their self-regulatory capacities in online learning being surveyed and analyzed descriptively and for correlation. The analysis revealed significant differences between self-regulatory abilities and learning outcomes. Furthermore, a descriptive analysis of the rating data was conducted, dividing the participants into high self-regulatory and low self-regulatory groups. Subsequent to this, two-factor variance analysis and simple effects tests were employed to further examine the data. The results indicated that factors affecting cognitive load and academic performance did not significantly differ. However, a significant interaction was observed between self-regulatory abilities and learning proficiency from the perspective of two-factor variance analysis. Simple effects tests further disclosed that under conditions of low learning proficiency, the cognitive load for the high self-regulatory group was greater than that for the low self-regulatory group; conversely, with higher learning proficiency, the cognitive load for the high self-regulatory group was lower. According to cognitive load theory, these findings suggest that learners who appropriately utilize their self-regulatory abilities can effectively alleviate cognitive load, thereby enhancing academic performance.