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Hybrid Recommender Strategy in Learning: An Experimental Investigation

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Author(s): Filipe Montez Coelho Madeira | Salvador Abreu | Rui Filipe Cerqueira Quaresma

Journal: Social Technologies
ISSN 2029-7564

Volume: 3;
Issue: 1;
Start page: 7;
Date: 2013;
Original page

Keywords: recommender strategy | personalized recommender systems | collaborative filtering | collaborative formal learning | sequencing | learner profile | technology enhanced learning

ABSTRACT
Purpose—finding ways of improving learning in a formal higher education context.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.Findings—the experiment shows that our recommendation techniques are able to reflect the learners’ interests.Research limitations/implications—it’s necessary to demonstrate the contributions of these kinds of solutions to the learners’ success.Practical implications—theoretical and practical framework for future research in the field was developed.Originality/Value—the main contributions are the extended Learning ManagementSystem and the hybrid Recommender System, which implements a new proposal to evaluate learners’ similarities.Research type: research paper.
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