Stay or Leave? Exploring Student Factors Associated With Dropout Patterns in Massive Open Online Courses

• In Event: Learner Engagement in Online Environments

Abstract

High dropout rates pose a problem for the improvement of massive open online courses (MOOCs). In this study, we analyzed data from 32,593 students (31.2% dropout rate) enrolled in fully online courses at an open university. Using survival analysis, we examined the effect of demographic information, past performance, and participation behaviors on student dropout patterns in the prophase, metaphase, and anaphase of online courses. The Cox proportional hazard model results indicated that past performance and participation behaviors were significant predictors of dropout. However, certain persistent participation behaviors (active days and assignment submission) tended to become less important in predicting dropout as the course progressed. Based on these findings, we provide recommendations for identifying at-risk students in a fully online environment.

Authors

• Hui Shi, Florida State University

• Yihang Zhou, Tongji University