Improving the Unreliability of Competence Information: an Argumentation to Apply Information Fusion in Learning Networks

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    Abstract

    Automated competence tracking and management is crucial for an effective and efficient lifelong competence development in learning networks. In this paper, we systematically analyze the problem of unreliability of competence information in learning networks. In tracking the development of competences in learning networks, a large amount of competence information can be gathered from diverse sources and diverse types of sources. Individual information is more or less credible. This paper investigates information fusion technologies that may be applied to address the problem and that show promise as candidate solutions for achieving an improved estimate of competences by fusing information coming from multiple sources and diverse types of sources.
    Original languageEnglish
    Pages (from-to)366-380
    JournalInternational Journal of Continuing Engineering Education and Life-Long Learning
    Volume19
    Issue number4/5/6
    DOIs
    Publication statusPublished - 24 Mar 2009

    Keywords

    • competences
    • learning network
    • information fusion
    • automated competence tracking
    • lifelong competence development
    • self-directed learning
    • competence profile
    • competence proficiency level
    • evidence record
    • competence record

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