Adaptive learning in the educational e-LORS system: an approach based on preference categories
by Luciana A.M. Zaina; Jose F. Rodrigues Jr.; Maria Angélica C. De Andrade Cardieri; Graça Bressan
International Journal of Learning Technology (IJLT), Vol. 6, No. 4, 2011

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.

Online publication date: Mon, 20-Oct-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Learning Technology (IJLT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com