• DocumentCode
    262448
  • Title

    Adaptivity in E-Learning Systems

  • Author

    Alshammari, Mohammad ; Anane, Rachid ; Hendley, Robert J.

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Birmingham, Birmingham, UK
  • fYear
    2014
  • fDate
    2-4 July 2014
  • Firstpage
    79
  • Lastpage
    86
  • Abstract
    Traditional e-learning systems have been, typically, designed for a generic learner, irrespective of individual knowledge, skills and learning styles. In contrast, adaptive e-learning systems can enhance learning by taking into account different learner characteristics and by personalising learning material. Although a large number of systems incorporating learning style have been deployed, there is a lack of comprehensive, comparative evaluations. This paper attempts to bridge this gap by comparing a number of adaptive e-learning systems. It considers three main perspectives: the learner model, the domain model and the adaptation model. A set of criteria is generated for each perspective, and applied to a representative sample of adaptive e-learning systems.
  • Keywords
    computer aided instruction; human factors; adaptation model; adaptive e-learning systems; domain model; learner model; learning style; Adaptation models; Adaptive systems; Data models; Electronic learning; Materials; Navigation; Standards; adaptation model; adaptive e-learning systems; domain model; learner model; learning style; learning technologies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Complex, Intelligent and Software Intensive Systems (CISIS), 2014 Eighth International Conference on
  • Conference_Location
    Birmingham
  • Print_ISBN
    978-1-4799-4326-5
  • Type

    conf

  • DOI
    10.1109/CISIS.2014.12
  • Filename
    6915500