Academic Pathway of Engagement Patterns and Performance Based on Learning Management System Data
This research addresses the following questions: (1) What are the typical learning pathways characterized by time engagement and social jetlag throughout a four-year undergraduate program? (2) How are students' learning pathways related to academic performance? (3) Does this relationship vary based on demographic characteristics such as gender, race, and first-generation status?
Analyzing LMS and administrative data from 9,883 students at a U.S. public university using R, we visualized the evolution of engagement patterns, applied Gaussian mixture models and k-means clustering to categorize students into distinct academic pathways, and employed a two-way fixed effects model to uncover heterogeneity across student groups. Our findings reveal that students exhibit higher engagement and less social jetlag during their first two years, indicating more consistent and regular learning behaviors. In contrast, during the final two years, students display lower engagement levels and increased social jetlag, suggesting more irregular learning patterns. Furthermore, we observed that first-generation and underrepresented racial minority students maintained higher engagement levels yet achieved lower academic performance compared to their counterparts throughout their undergraduate studies. This research contributes to a deeper understanding of students' longitudinal engagement patterns and underscores the significance of considering student agency and demographic factors when analyzing academic pathways.