Beyond Grades: A Critical Examination of SRL and Demographics Among Engineering Students

Accurate prediction of academic performance in engineering education is crucial yet challenging. Current approaches heavily rely on cognitive factors, overlooking the potential of non-cognitive aspects. This study bridges this gap by investigating the complementary role of Self-Regulated Learning (SRL) and demographics in predicting student performance. Using established statistical methods, we analyze data from 890 engineering students from three cohorts at a Malaysian university (Spearman's rho, Chi-Square). While confirming the expected positive correlation between prior academic performance and final CGPA, our key contribution lies in demonstrating the significant impact of SRL on academic achievement. Three MSLQ scales (Time and Study Environment, Effort Regulation, and Metacognitive Self-Regulation) exhibit robust positive correlations with final CGPA, highlighting SRL as a potentially valuable predictor alongside cognitive measures. While demographic factors, such as gender, exhibit moderate associations with final grade classification, income shows no significant effect. This suggests that cognitive factors and SRL may be more prominent in predicting student success in engineering education. This study lays the groundwork for future research with broader populations to account for potential confounding variables and socio-economic contexts. By emphasizing the promising role of SRL, our findings offer valuable insights for developing more comprehensive and effective educational strategies and policies.