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A survival model for course-course interactions in a Massive Open Online Course platform
Edwin H Wintermute1, Matthieu Cisel2, Ariel B Lindner1
1Université de Paris, INSERM U1284, Center for Research and Interdisciplinarity (CRI), Paris, France.
Plos One
|January 22, 2021
Summary
Student engagement on Massive Open Online Course (MOOC) platforms influences certificate completion. Analyzing course interactions reveals user engagement as a key metric for tracking student success across diverse demographics and over time.
Area of Science:
- Educational Technology
- Network Analysis
- Reliability Theory
Background:
- Massive Open Online Course (MOOC) platforms host extensive course catalogs, leading to complex student registration patterns.
- Understanding how course-course interactions impact student achievement is crucial for improving online learning outcomes.
Purpose of the Study:
- To analyze student achievement in MOOCs using a network-based approach.
- To investigate the influence of course-course interactions on certificate completion rates.
- To introduce a reliability theory-based model for analyzing student success.
Main Methods:
- Network-based analysis of 378,000 users and 1,000,000 registrations on the France Université Numérique (FUN) MOOC platform.
- Adaptation of reliability theory using a Weibull survival function to model certificate completion.
- Estimation of a user engagement parameter from registration profiles to describe course-course interactions.
Main Results:
- Course-course interactions can be effectively modeled by a single user engagement parameter.
- User engagement strongly correlates with certificate completion rates across all courses, irrespective of content.
- The reliability approach identifies patterns in certificate rates missed by traditional regression models.
Conclusions:
- User engagement is a significant predictor of student success in MOOCs.
- The proposed reliability model offers a more nuanced understanding of student progression and dropout.
- User engagement serves as a valuable metric for monitoring student progress longitudinally and across different user groups.
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