Article: Adaptive learning in the educational e-LORS system: an approach based on preference categories Journal: International Journal of Learning Technology (IJLT) 2011 Vol.6 No.4 pp.341 - 361 Abstract: In the field of electronic education, the recommendation of contents with higher levels of relevance may potentially attract the students' attention. In this context, this work considers students' learning styles, delineated with structured questionnaires, as a means of selecting the best content as for the learning-teaching process. The goal is to present a complete systematisation the e-LORS system, which is able to recommend electronic educational content based on the relationship between detected learning styles and stored learning objects. Our contributions include the e-LORS system its multiple-criteria architecture and study case, the methodology based on the Felder-Silverman learning style model and on the IEEE learning object metadata (LOM), and the reporting of experiments conducted in an actual educational context. Inderscience Publishers - linking academia, business and industry through research

Title: Adaptive learning in the educational e-LORS system: an approach based on preference categories

Authors: Luciana A.M. Zaina; Jose F. Rodrigues Jr.; Maria Angélica C. De Andrade Cardieri; Graça Bressan

Addresses: Universidade Federal de São Carlos Campus Sorocaba, Rod. João Leme dos Santos, Km 110 – SP-264, Sorocaba – SP – CEP 18052-780, Brazil. ' Universidade de São Paulo, Inst. de Ciências Mat. e de Computação, Av. Trabalhador São-Carlense, 400 – Centro São Carlos – SP – CEP 13560-970, Brazil. ' Faculdade de Engenharia de Sorocaba, Rodovia Senador José Ermírio de Moraes, 1425, Sorocaba – SP – CEP 18087-125, Brazil. ' Departamento de Eng. da Comp. e Sistemas Digitais – Escola Politécnica, Universidade de São Paulo, Av. Prof. Luciano Gualberto, Travessa 3, n.158, Sala C1-46, São Paulo – SP – CEP 05508-900, Brazil

Abstract: In the field of electronic education, the recommendation of contents with higher levels of relevance may potentially attract the students' attention. In this context, this work considers students' learning styles, delineated with structured questionnaires, as a means of selecting the best content as for the learning-teaching process. The goal is to present a complete systematisation the e-LORS system, which is able to recommend electronic educational content based on the relationship between detected learning styles and stored learning objects. Our contributions include the e-LORS system its multiple-criteria architecture and study case, the methodology based on the Felder-Silverman learning style model and on the IEEE learning object metadata (LOM), and the reporting of experiments conducted in an actual educational context.

Keywords: adaptive learning; educational systems; preference categories; recommender systems; learning objects; LOM standard; learning object metadata; learning profiles; learning models; Felder-Silverman learning styles; e-learning; electronic learning; online learning; content recommendation; sudent learning styles.

DOI: 10.1504/IJLT.2011.044628

International Journal of Learning Technology, 2011 Vol.6 No.4, pp.341 - 361

Published online: 20 Oct 2014 *

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Title: Adaptive learning in the educational e-LORS system: an approach based on preference categories

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