COLLABORATIVE FILTERING RECOMMENDATION SYSTEM: A FRAMEWORK IN MASSIVE OPEN ONLINE COURSES
作者： Jane Sinclair , Daniel F. O. Onah
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摘要: Massive open online courses (MOOCs) are growing relatively rapidly in the education environment. There is a need for MOOCs to move away from its one-size-fit-all mode. This framework will introduce an algorithm based recommendation system, which use collaborative filtering method (CFM). Collaborative (CFM) process of evaluating several items through rating choices participants. Recommendation system widely becoming popular study activities; we want investigate support learning and encouragement more effective participation. research be reviewing existing literature on recommender systems learners’ experiences. Our proposed course components rating. The idea was learners rate they have studied platform between scales 1 – 5. After rating, then extract values into comma separated (CSV) file implement using Python programming with similar patterns. aim recommend different users text editor mode programming. act upon patterns learners, so as enhance their experience enthusiasm.
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