• Login
    View Item 
    •   DORA Home
    • Faculty of Computing, Engineering and Media
    • School of Computer Science and Informatics
    • View Item
    •   DORA Home
    • Faculty of Computing, Engineering and Media
    • School of Computer Science and Informatics
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    An Adaptive Learning Ontological Framework Based on Learning Styles and Teaching Strategies

    Thumbnail
    View/Open
    shaimaa_siewe_2017_egypt.pdf (1.037Mb)
    Date
    2017-09
    Author
    Nafea, Shaimaa;
    Siewe, Francois;
    He, Ying
    Metadata
    Show attachments and full item record
    Abstract
    Ontology are increasingly being used in a variety of applications, and particularly in adaptive e-learning. They have the potential to enable developers to create adaptive course content for specified domains. E-learning applications are thus able to use technology and educational content in order to generate content that matches the student's capabilities and knowledge. This personalises learning, rather than assuming that "one-size-fits-all" and providing all learners with the same content, which is what the majority of e-learning systems do. This study introduces a new approach that takes into account the fact that each learner has an individual learning style and needs. The approach enables to adapt the course content, teaching strategy and learning objects so that they correspond to each student’s learning styles. This is achieved with the use of artificial intelligent in the form of an ontology and rule-based reasoning. The proposed system takes some of the key design aspects such as extensibility, reusability, and maintainability into consideration in order to enhance performance of adaptive course content recommendation.
    Description
    Citation : Nafea, S., Siewe, F. and He, Y. (2017) An Adaptive Learning Ontological Framework Based on Learning Styles and Teaching Strategies. Proceedings of 85th ISERD International Conference, Cairo, Egypt, 11th-12th September 2017
    URI
    http://hdl.handle.net/2086/14720
    Research Group : Software Technology Research Laboratory (STRL)
    Research Institute : Cyber Technology Institute (CTI)
    Peer Reviewed : Yes
    Collections
    • School of Computer Science and Informatics [2679]

    Submission Guide | Reporting Guide | Reporting Tool | DMU Open Access Libguide | Take Down Policy | Connect with DORA
    DMU LIbrary
     

     

    Browse

    All of DORACommunities & CollectionsAuthorsTitlesSubjects/KeywordsResearch InstituteBy Publication DateBy Submission DateThis CollectionAuthorsTitlesSubjects/KeywordsResearch InstituteBy Publication DateBy Submission Date

    My Account

    Login

    Submission Guide | Reporting Guide | Reporting Tool | DMU Open Access Libguide | Take Down Policy | Connect with DORA
    DMU LIbrary