Title:
Predictive model selection for completion rate in massive open online courses
Authors:
Annamaria De Santis, University of Modena and Reggio Emilia
Katia Sannicandro, University of Modena and Reggio Emilia
Claudia Bellini, University of Modena and Reggio Emilia
Tommaso Minerva, University of Modena and Reggio Emilia
Published:
Journal of e-Learning and Knowledge Society, volume 15, issue 3 (2019)
doi: https://doi.org/10.20368/1971-8829/1135034
From the abstract:
"In this paper we introduce an approach for selecting a linear model to estimate, in a predictive way, the completion rate of massive open online courses (MOOCs). Data are derived from LMS analytics and nominal surveys.
The sample comprises 723 observations (users) carried out in seven courses on EduOpen, the Italian MOOCs platform. We used 24 independent variables (predictors), categorised into four groups (User Profiles, User Engagement, User Behaviour, Course Profile). As response variables we examined both the course completion status and the completion rate of the learning activities."