Paper Info
Title
A Survival Model For Course-Course Interactions In A Massive Open Online Course Platform
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 Universite Nume rique (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.
Year
DOI
Venue
2019
10.1371/journal.pone.0245718
PLOS ONE
DocType
Volume
Issue
Journal
16
1
ISSN
Citations 
PageRank 
1932-6203
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Edwin H. Wintermute150.70
Matthieu Cisel200.34
Ariel B Lindner372.27