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Authors: Madeira, Filipe
Abreu, Salvador
Quaresma, Rui
Editors: Skaržauskienė, Aelita
Keywords: personalized recommender systems
collaborative filtering
collaborative formal learning
learner profile
technology enhanced learning
Issue Date: 2013
Publisher: Mykolas Romeris University
Abstract: Purpose – Find ways to improve 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 contents to learners. Findings – The experiment shows that our recommendation techniques are able to reflect 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 Management System and the hybrid Recommender System, which implements a new proposal to evaluate learners similarities.
Type: article
Appears in Collections:GES - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
CEFAGE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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