Predicting First-Year Dropout Risk from LMS Activity Logs

Andrea Villanueva

Abstract

Using anonymized learning-management-system logs from 2,300 first-year students, we compare gradient boosting and logistic regression for early dropout prediction by week 5 of the semester, with attention to fairness across campuses.