• DocumentCode
    3294025
  • Title

    Content personalization in e learning environment

  • Author

    Benhamdi, S. ; Seridi, Hamid

  • Author_Institution
    Dept. of Comput. Sci., 8th May 1945 Univ., Guelma, Algeria
  • fYear
    2011
  • fDate
    4-6 Aug. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    For facilitating the use of e learning environments by teachers, we have proposed an approach that aid them to propose documents for learners taking in account their preferences and abilities, so allowing the personalization of these environments. This approach combines a pedagogical scenario design approach, using one of most used modelling languages IMS Learning Design (IMSLD), and taxonomy based one which is boosted-CSHTRL (Boosted Cold Start Hybrid Taxonomy Recommender for e Learning), developed to generate recommendation to learners, taking into consideration their preferences and abilities in order to motivate them, and consequently, improve efficiency and increase veracity of learner in the learning situation.
  • Keywords
    computer aided instruction; recommender systems; simulation languages; IMS learning design; IMSLD modelling language; boosted cold start hybrid taxonomy recommender; content personalization; e-learning environment; pedagogical scenario design approach; Educational institutions; Electronic learning; Graphical user interfaces; Measurement; Recommender systems; Taxonomy; Content personalization; IMSLD; recommender system; taxonomy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology Based Higher Education and Training (ITHET), 2011 International Conference on
  • Conference_Location
    Kusadasi, Izmir
  • Print_ISBN
    978-1-4577-1673-7
  • Type

    conf

  • DOI
    10.1109/ITHET.2011.6018692
  • Filename
    6018692