A survival model for course-course interactions in a Massive Open Online Course platform

PLoS One. 2021 Jan 22;16(1):e0245718. doi: 10.1371/journal.pone.0245718. eCollection 2021.

Abstract

Massive Open Online Course (MOOC) platforms incorporate large course catalogs from which individual students may register multiple courses. We performed a network-based analysis of student achievement, considering how course-course interactions may positively or negatively affect student success. Our data set included 378,000 users and 1,000,000 unique registration events in France Université Numérique (FUN), a national MOOC platform. We adapt reliability theory to model certificate completion rates with a Weibull survival function, following the intuition that students "survive" in a course for a certain time before stochastically dropping out. Course-course interactions are found to be well described by a single parameter for user engagement that can be estimated from a user's registration profile. User engagement, in turn, correlates with certificate rates in all courses regardless of specific content. The reliability approach is shown to capture several certificate rate patterns that are overlooked by conventional regression models. User engagement emerges as a natural metric for tracking student progress across demographics and over time.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Success*
  • Adolescent
  • Adult
  • Education, Distance*
  • Female
  • France
  • Humans
  • Male
  • Models, Theoretical*
  • Students*

Grants and funding

This work was supported by the Bettencourt Schueller Foundation through a CRI Research Fellowship to EHW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.