Work in progress: A didactic strategy based on Machine Learning for adaptive learning in virtual environments

In the current post-pandemic context, learning mediated by virtual platforms has become the de facto methodology. Despite its wide use and recent developments, virtual learning still faces several challenges to reach its maximal potential. One of these challenges is related to the homogeneity of the contents presented to the students and the lack of awareness of the different learning styles. This scenario has evidenced the need to develop mechanisms that strengthen learning processes according to the particular preferences of each student. In this context, this work presents a methodology to implement a didactic strategy oriented to incorporate adaptive learning in virtual environments. The strategy is supported by a machine learning based contents recommender that is integrated with the Learning Management System to improve the student's outcomes.