Hiperion: A fuzzy approach for recommending educational activities based on the acquisition of competences

A recommender system which is able to suggest personalized activities for each student in order to reinforce their competences in a subject is developed and tested with real students, achieving successful results.

Abstract

The concept of competence is acquiring relevance as core element of educational systems and consequently importance in the job market. Therefore, teachers must prepare educational activities designed to exercise a set of competences that each student needs to obtain. These activities should be recommended to each student according to their strengths and weaknesses as they are uncovered during the academic year. In order to appropriately recommend these activities, a framework is necessary where competences are at the core of assessment. Thus, the focus of this work is a system where activities are designed in order to exercise each competence to some extent and assess them according to their degree of acquisition. From this idea it is possible to develop a recommender system which is able to suggest personalized activities for each student in order to reinforce their competences in a subject. These recommendations are computed through the characteristics of the competences from each subject and the designed activities, modeled by fuzzy linguistic labels. In order to test the effectiveness of the proposed system, a prototype has been developed and tested with real students, achieving successful results.