Recommendation in E-Learning Social Networks

  • Pierpaolo Di Bitonto
  • Teresa Roselli
  • Veronica Rossano
Conference paper

DOI: 10.1007/978-3-642-25813-8_36

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7048)
Cite this paper as:
Di Bitonto P., Roselli T., Rossano V. (2011) Recommendation in E-Learning Social Networks. In: Leung H., Popescu E., Cao Y., Lau R.W.H., Nejdl W. (eds) Advances in Web-Based Learning - ICWL 2011. ICWL 2011. Lecture Notes in Computer Science, vol 7048. Springer, Berlin, Heidelberg

Abstract

In the past years learning has evolved from face-to-face to computer-supported learning, and we are now entering yet a new phase. The (r)evolution that yielded the knowledge transforming the Web 1.0 into Web 2.0 is now coming to e-learning contexts. Social media are the technologies most widely used to share educational contents, to find colleagues, discussion groups, and so on. But while in the Web 1.0 the most “time-spending” activity was to find suitable learning content, in the Web 2.0 era the search process is focused on different types of resources. This paper proposes a recommendation method that, by using a clustering algorithm, is able to support users during the selection steps. The recommendation is based on the tags defined by the network learners and the items to be recommended include not only contents but also social connections that could enrich the user’s learning process.

Keywords

Social network recommendation systems clustering algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pierpaolo Di Bitonto
    • 1
  • Teresa Roselli
    • 1
  • Veronica Rossano
    • 1
  1. 1.Department of InformaticsUniversity of Bari “Aldo Moro”BariItaly

Personalised recommendations