Predicting the likelihood of dropping out from MOOC-based program
This research aims to identify the likelihood of dropping out from a MOOC-based program. Program dropout happens both, within and between courses. We identify the key dropout factors and develop a machine learning model to predict future student dropout.
Results from our prediction models reveal that learners are more likely to leave a MOOC-based program after the first few courses (1-3). Grades, level of education and gender are highly correlated with learner dropout. We suggested some potential initial interventions which could be highly valuable as a starting point.
- Borrella, I., Caballero, S., Ponce, E. Taking action to reduce dropout in MOOCs: tested interventions. Computers & Education. Accepted, Dec 2021.
- Predicting the likelihood of dropping out from the SCM MicroMasters program. Master Thesis. System Design and Management Program. June 2019.
Dr. Chris Caplice
Senior Research Scientist
Dr. Eva Ponce