A learning web platform based on a fuzzy linguistic recommender system to help students to learn recommendation techniques

Abstract

The rapid advances in Web technologies are promoting the development of new pedagogic models based on virtual teaching. To achieve this personalized services are necessary to provide the users with relevant information, according to their preferences and needs. Recommender systems can be used in an academic environment to improve and assist users in their teaching-learning processes. In this paper we propose a fuzzy linguistic recommender system to facilitate learners the access to e-learning resources interesting for them. By suggesting didactic resources according to the learner’s specific needs, a relevanceguided learning is encouraged, influencing directly the teaching-learning process.We propose the combination of the relevance degree of a resource for a user with its quality in order to generate more profitable and accurate recommendations. In addition to that, we present a computersupported learning system to teach students the principles and concepts of recommender systems.