Hybrid Recommender Strategy in Learning: An Experimental Investigation

Abstract

Purpose—finding ways of improving learning in a formal higher education context.<br /> Design/methodology/approach—in the proposed model we will consider extending traditional content management systems, giving learners the possibility to add new materials and to rate them, and a hybrid strategy that combines technical recommendations with some profile-based filtering to offer adaptive and suitable sequencing learning content to learners.<br /> Findings—the experiment shows that our recommendation techniques are able to reflect the learners’ interests.<br /> Research limitations/implications—it’s necessary to demonstrate the contributions of these kinds of solutions to the learners’ success.<br /> Practical implications—theoretical and practical framework for future research in the field was developed.<br /> Originality/Value—the main contributions are the extended Learning Management<br /> System and the hybrid Recommender System, which implements a new proposal to evaluate learners’ similarities.<br /> Research type: research paper.