Personalizing E-Learning 2.0 Using Recommendations

  • Martina Holenko Dlab
  • Natasa Hoic-Bozic
  • Jasminka Mezak
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 292)

Abstract

Recommender systems support users in accessing information available on the Web. This process ensures personalization since recommendations are generated according to user’s characteristics. In the educational domain, in the most cases, recommendations refer to learning materials. Besides that, there is a potential for using recommendation techniques in order to personalize other aspects of e-learning context. This paper describes a recommendation model for providing personalization of a collaborative learning process. Well-known recommendation techniques are adapted for online learning environment that consists of an LMS and different Web 2.0 tools. The recommendations are used to support students before and during e-tivities and include four different types of items: optional e-tivities, collaborators, Web 2.0 tools and advice.

Keywords

Recommender System Recommendation Techniques E-Learning Collaborative Learning TEL Web 2.0 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Martina Holenko Dlab
    • 1
  • Natasa Hoic-Bozic
    • 1
  • Jasminka Mezak
    • 2
  1. 1.Department of InformaticsUniversity of RijekaRijekaCroatia
  2. 2.Faculty of Teacher EducationUniversity of RijekaRijekaCroatia

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