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Fuzzy Student Modeling for Personalization of e-Learning Courses

  • Carla Limongelli
  • Filippo Sciarrone
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8523)

Abstract

In the context of e-learning courses, personalization is a more and more studied issue, being its advantage in terms of time and motivations widely proved. Course personalization basically means to understand student’s needs: to this aim several Artificial Intelligence methodologies have been used to model students for tailoring e-learning courses and to provide didactic strategies, such as planning, case based reasoning, or fuzzy logic, just to cite some of them. Moreover, in order to disseminate personalised e-learning courses, the use of known and available Learning Management System is mandatory.

In this paper we propose a fine-grained student model, embedded into an Adaptive Educational Hypermedia, LS_Plan provided as plug-in for Moodle. In this way we satisfy the two most important requirements: a fine-grained personalization and a large diffusion. In particular, the substantial modification proposed in this contribution regards the methodology to evaluate the knowledge of the single student which currently has a low granularity level. The experiments showed that the new system has improved the evaluation mechanism by adding information that students and teachers can use to keep track of learning progress.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Carla Limongelli
    • 1
  • Filippo Sciarrone
    • 1
  1. 1.Engineering DepartmentRoma Tre UniversityRome

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