Work

Hybrid Recommender Strategy in Learning: an Experimental Investigation

Year: 2013

Type: article

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 Management System and the hybrid Recommender System, which implements a new proposal to evaluate learners’ similarities. Research type: research paper.

Source: Social Technologies

DOI: 10.13165/st-13-3-1-01

Authors: Filipe Montez Coelho Madeira, Salvador Abreu, Rui Filipe Cerqueira Quaresma

Institutions: Mykolas Romeris University, University of Évora, Universidade Politécnica de Santarém, Centro de Estudos e Formação Avançada em Gestão e Economia

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

Funder: Fundação para a Ciência e a Tecnologia