Trace Learners Clustering to Improve Learning Object Recommendation in Online Education Platforms

E-learning platforms propose pedagogical pathways where learners are invited to mobilize their autonomy achieve the learning objectives. However, some face a set of cognitive barriers that require additional objects progress in course. A mediating recommendation system is one efficient solutions reinforce resilience online platforms, while suggesting will be interesting for them according needs. The objective this contribution design new mediator model e-learning suggest learner based on collaborative filtering. To end, proposed relies implicit behaviors estimation function as an underlying technique convert tacit traces into explicit preferences allowing compute similarity between learners.