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Exploring the vector space model for online courses

In this article, we investigate the role of recommender systems and their potential in the educational system. The key idea is to describe the information aggregation capabilities of a recommender system to find the best way tutoring. The recommender system presented in this article is based on building a vector space model for massive open online courses (MOOCs). We show that the resulting model can be used to effectively query semantically related courses as well as search for clusters and linear transitions between them.