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    Black box metadata creation: The academic problem

    Maycock, Keith and Keating, John (2014) Black box metadata creation: The academic problem. International Journal of Emerging Technologies in Learning (iJET), 9 (5). pp. 60-63. ISSN 1863-0383

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    Adaptive learning systems attempt to adapt learning content to suit the needs of the learners using the system. Most adaptive techniques, however, are constrained by the pedagogical preference of the author of the system and are always constrained to the system they were developed for and the domain content. Understanding the environmental constructs of a learning environment is critical to be able to consider adapting content to individual learners. A sample personal profile is described that can be used to automatically generate instructional content to suit the pedagogical preference and cognitive ability of a learner in real time, in an online learning environment. This paper introduces a Content Analyser (CA) that is used to automatically generate metadata to encapsulate cognitive resources within instructional content. The analyser is designed to bridge the perceived gap found within instructional repositories between inconsistent metadata created for instructional content and multiple metadata standards being used. All instructional content that is analysed is repackaged as Sharable Content Object Reference Model (SCORM) conforming content.

    Item Type: Article
    Keywords: Content Adaptation; SCORM; E-Learning;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 12350
    Identification Number:
    Depositing User: Dr. John Keating
    Date Deposited: 04 Feb 2020 15:09
    Journal or Publication Title: International Journal of Emerging Technologies in Learning (iJET)
    Publisher: International Association of Online Engineering (IAOE)
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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