Framework for a Competency-Driven, Multi-viewpoint, and Evolving Learner Model

  • Lucie Moulet
  • Olga Marino
  • Richard Hotte
  • Jean-Marc Labat
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5091)

Abstract

Considering learning as a dynamic, evolving, social, and lifelong process which occurs in a wide variety of contexts, we aim to improve online learning by offering learning adaptation possibilities, lifelong learning follow-up, learning evolution follow-up, openness to the learner’s contexts (personal, professional, and academic), and openness to actors involved in the learning process. To achieve this goal, we propose the development of a meta-model for learner models based on competencies, integrating learner production and personal and professional information, IPP, evolving in time and taking into account different viewpoints. This meta-model may be used for creating different kind of learner models which serve different purposes: adaptation of learning to the learner’s cognitive state, learning evaluation, self-reflection, team work... From these kinds of models, models representing individuals will be instantiated.

Keywords

Online learning learner model personalization competency 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Lucie Moulet
    • 1
    • 2
  • Olga Marino
    • 1
  • Richard Hotte
    • 1
  • Jean-Marc Labat
    • 3
  1. 1.LICEF Research CenterTélé-université / Université du Québec À MontréalMontréalCanada
  2. 2.CRIP5Université Paris Descartes – Paris 5Paris Cedex 06France
  3. 3.LIP6Université Pierre et Marie Curie – Paris 6ParisFrance

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