Early Detection of Learner Profiles in the Context of Online Education: A Machine Learning Approach.

This study aims to identify university student profiles based on their learning/motivational strategies and experiences with online instruction. An unsupervised learning algorithm was able to identify four profiles with significant differences in specific individual and environmental variables. Additionally, artificial neural network models were robust identifying the student group at risk.