Knowledge-based algorithms to optimise e-learning outcome

Zhuhan Jiang, Xiling Guo, Narendra Gangavarapu, Khaled Khan

    Research output: Chapter in Book / Conference PaperConference Paperpeer-review

    Abstract

    ![CDATA[Major providers of e-learning mostly design their products to aim at corporative organisations such as the universities. They are usually large systems with support only on very standard operations, lacking subsequently knowledge-based components to intelligently optimise the online delivery. In this work, we propose a number of concrete knowledge-based algorithms that would enable subject designers to effectively and efficiently select drill or assessment questions to target specific learning outcome, and at the same time automatically enrich the characterisation of such questions through their usage. The database structure and implementation issues are also addressed and analysed.]]
    Original languageEnglish
    Title of host publicationProceedings of the 2009 International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2009), Las Vegas, Nevada, USA, July 13-16, 2009
    PublisherCSREA Press
    Number of pages7
    ISBN (Print)160132104X
    Publication statusPublished - 2009
    EventInternational Conference on Frontiers in Education: Computer Science and Computer Engineering -
    Duration: 16 Jul 2012 → …

    Conference

    ConferenceInternational Conference on Frontiers in Education: Computer Science and Computer Engineering
    Period16/07/12 → …

    Fingerprint

    Dive into the research topics of 'Knowledge-based algorithms to optimise e-learning outcome'. Together they form a unique fingerprint.

    Cite this