Adapt Learning Path by Recommending Problems to Struggling Learners

Abstract

The objective of this work is the creation of a resource recommendation application in Python integrated into the code of the virtual edX platform, which appears as an additional tab in each course. By selecting this tab, learners will have access at any time to their recommended issues for this course, and so they can adapt their learning path. In this article, we present a recommendation algorithm that will be responsible for proposing these problems according to the scores obtained in the problems already performed by the learner. By calculating the similarity with the rest of the classmates, an estimate of the most practical problems for the learner will be made. We also present the different functions and parameters to implement it.