Now showing items 1-3 of 3

  • An e-learning recommender that helps learners find the right materials. 

    Mbipom, Blessing; Massie, Stewart; Craw, Susan (Association for the Advancement of Artificial Intelligence, 2018-02-03)
    MBIPOM, B., MASSIE, S. and CRAW, S. [2018]. An e-learning recommender that helps learners find the right materials. To be presented at the 8th educational advances in artificial intelligence 2018 (EAAI-18), 3-4 February 2018, New Orleans, USA, (accepted).
    Learning materials are increasingly available on the Web making them an excellent source of information for building e-Learning recommendation systems. However, learners often have difficulty finding the right materials ...
  • Improving e-learning recommendation by using background knowledge. 

    Mbipom, Blessing; Craw, Susan; Massie, Stewart (Wiley https://doi.org/10.1111/exsy.12265, 2018-01-26)
    MBIPOM, B., CRAW, S. and MASSIE, S. 2018. Improving e-learning recommendation by using background knowledge. Expert systems [online], Early View. Available from: https://doi.org/10.1111/exsy.12265
    There is currently a large amount of e-Learning resources available to learners on the Web. However, learners often have difficulty finding and retrieving relevant materials to support their learning goals because they ...
  • Towards a fuzzy domain ontology extraction method for adaptive e-learning. 

    Lau, Raymond Y. K.; Song, Dawei; Li, Yuefeng; Cheung, Terence; Hao, Jin-Xing (IEEE http://doi.ieeecomputersociety.org/10.1109/TKDE.2008.137, 2009-06)
    LAU, R., SONG, D., LI, Y., CHEUNG, T. and HAO, J., 2009. Towards a fuzzy domain ontology extraction method for adaptive e-learning. IEEE Transactions on Knowledge and Data Engineering, 21 (6), pp. 800-813.
    With the wide spread applications of e-Learning technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. ...