Researcher: Costa Muthai, University of Venda
Supervisor: Dr Martins Aramsowna, University of Venda
Internet and Web technologies of today not only enable students to interact more freely with educational resources, friends, and teachers, but they also produce enormous amounts of application data that can be assessed to reveal study and learning habits. The Kalboard 360 Learning Management System (LMS) data was used in this research study to analyze student trajectory data from a blended learning course and create a probabilistic (Bayesian) model that predicted academic success. Statistical inferences were made to classify students and highlight characteristics from the data that corresponded to failure based on the influence of their demographic, academic, and behavioral characteristics.
