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

High dropout rates pose a problem for the improvement of massive open online courses (MOOCs). Previous research has suggested that student demographic information, past performance, and participation behaviors can predict dropout. 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. Our results showed that the median retention time for online learners was 241 days. The Cox proportional hazard model results indicated that student past performance and participation behaviors were significant predictors of dropout. However, certain persistent participation behaviors (i.e. 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.