Using Data Acquired from Learning Management Systems to Predict Examination Results

Francis B. Lavoie, Pierre Proulx, Ryan Gosselin
2019 Proceedings of the Canadian Engineering Education Association (CEEA)  
This work presents a novel learning management system (LMS), named Catalyseur, which allows the instructors to easily visualize which lessons and exercises allowed the students to better perform at an examination. This LMS feature is based on a regression methodology calculating easy-to-analyze models and being able to fit dynamic relationships. These models are calculated automatically and only require as human input to upload the student results at an examination.
doi:10.24908/pceea.vi0.13781 fatcat:6k4iowesofeenho2jwbujqpkbu