Modelling Student Learning and Forgetting for Optimally Scheduling Skill Review
Résumé
Current adaptive and personalised spacing algorithms can help improve students’ long-term memory retention for simple pieces of knowledge, such as vocabulary in a foreign language. In real-world educational settings, however, students often need to apply a set of underlying and abstract skills for a long period. At the French Laboratoire de Recherche en Informatique (LRI), we developed a new student learning and forgetting statistical model to build an adaptive and personalised skill practice scheduler for human learners.