• DocumentCode
    2915914
  • Title

    An Architecture for Adaptive Collaboration Support Guided by Learning Design

  • Author

    Bayon, A. ; Santos, O.C. ; Couchet, J. ; Boticario, J.G.

  • Author_Institution
    Artificial Intell. Dept., UNED, Madrid, Spain
  • fYear
    2009
  • fDate
    4-6 Nov. 2009
  • Firstpage
    323
  • Lastpage
    328
  • Abstract
    A CSCL environment provides support to manage collaborative tasks. However, these systems do not usually provide the personalization features required to adapt the learning experience to the student needs, a drawback that can affect the collaboration objective and ultimately a successful learning. To alleviate this disadvantage we propose an architecture that provides adaptive collaboration support for a CSCL environment framed in an open and standards-based LMS. Our proposal combines adaptation rules defined in IMS Learning Design specification and dynamic support through recommendations via an accessible and adaptive guidance system. The implementation offers CSCL courses following a methodology called Collaborative Logical Framework. This system has been tested on a real world scenario at the Madrid Science Week 2009.
  • Keywords
    computer aided instruction; groupware; recommender systems; CSCL environment; IMS learning design specification; adaptive collaboration support; collaborative logical framework; computer supported collaborative learning; recommendation system; Adaptive control; Adaptive systems; Artificial intelligence; Buildings; Collaborative work; International collaboration; Learning; Least squares approximation; Power system management; Proposals; Adaptive collaboration; CSCL; Collaborative Logical Framework; IMS-LD; Recommender System; Tracking and Auditing; User Model; dotLRN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems, 2009. INCOS '09. International Conference on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-5165-4
  • Electronic_ISBN
    978-0-7695-3858-7
  • Type

    conf

  • DOI
    10.1109/INCOS.2009.51
  • Filename
    5369352