Proposing "collaborative filtering" to foster collaboration in ScratchR community

  • Authors:
  • Georgios Fessakis;Angelique Dimitracopoulou

  • Affiliations:
  • LTEE laboratory, University of the Aegean, Rhodes, Greece;LTEE laboratory, University of the Aegean, Rhodes, Greece

  • Venue:
  • CSCL'09 Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 2
  • Year:
  • 2009

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Abstract

The present work focuses the interest of study in a naturally emerged and intense online community, this of ScratchR "programmers by choice" community, that actually practice collaborative learning in an authentic way. Our interest is not to support collaborative learning process, but to foster collaboration opportunities. We propose a personalized recommendation system based on a "collaborative filtering" technique aiming at inciting collaboration and increasing the frequency of Scratch projects remixing, in order to foster collaborative learning. In this paper the proposed collaboration fostering mechanism is outlined with the assistance of a test data set. The significance of the proposal is discussed while the future work is described.