An Ontological Model to Predict Dropout Students Using Machine Learning Techniques

E-learning systems become more popular than it has ever been. However the popularity of e-learning systems, they still suffer from some problems related to the completion rate of online courses and the learners’ failures. Nowadays, a lot of educational institutions are concentrating on how to solve those problems in order to improve the quality of learning process. This paper presents an ontological model based on machine learning techniques to predict learners coming performance using data produced by learners through their interaction with Learning Management System and Facebook groups. It also presents two different approaches to evaluate ontology model in terms of completeness and correctness.