Recommendation of learning material through studentś collaboration and user modeling in an adaptive e-learning environment

Daniel Lichtnow, Isabela Gasparini, Amel Bouzeghoub, José Palazzo M. De Oliveira, Marcelo S. Pimenta

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this chapter, we present an approach for recommendation of learning materials to students in an e-learning environment. Our aim is to increase the current system's personalization capabilities for students in different scenarios making use of recommendation techniques. The recommendation is produced considering learning materials' properties, student's profile and the context of use. In addition, the process of recommendation is improved through studentś collaboration. In the context of this work, a learning material is a link to a Web page or a paper available on the Web and previously stored in a private repository. The process of collaboration occurs during student's evaluations of the recommendations. These student́s evaluations are used by the system to produce new recommendations for other students. The main features of the recommendations aspects are described and some examples are also used to discuss and illustrate how to provide this personalization.

Original languageEnglish
Title of host publicationTechnology-Enhanced Systems and Tools for Collaborative Learning Scaffolding
EditorsThanasis Daradoumis, Thanasis Daradoumis, Angel Juna, Santi Caballe, Fatos Xhafa
Pages257-278
Number of pages22
DOIs
Publication statusPublished - 15 Apr 2011
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume350
ISSN (Print)1860-949X

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