作者: Samuel Stallin Kapembe , José Ghislain Quenum
关键词:
摘要: In this work, we present a hybrid Recommender System (RS) for prescribing learning objects to students in Personalised Learning Environment (PLE). This RS Objects (LOs) uses explicit and implicit student profiling filter material recommendation student. Further, the profile consists of preferences, student's confidence level required topics as well courses she enrolled in. Finally, factor object ratings enhance recommendations.