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    The effect of users' tagging motivation on the enlargement of digital educational resources metadata

    Access Status
    Fulltext not available
    Authors
    Zervas, P.
    Sampson, Demetrios
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Zervas, P. and Sampson, D. 2014. The effect of users' tagging motivation on the enlargement of digital educational resources metadata. Computers in Human Behavior. 32: pp. 295-300.
    Source Title
    Computers in Human Behavior
    DOI
    10.1016/j.chb.2013.06.026
    ISSN
    0747-5632
    School
    School of Education
    URI
    http://hdl.handle.net/20.500.11937/19841
    Collection
    • Curtin Research Publications
    Abstract

    The emerging Web 2.0 applications have allowed new ways of characterizing digital educational resources, which moves from the expert-based descriptions relying on formal classification systems such as the IEEE Learning Object Metadata (LOM) to a less formal user-based tagging. This alternative way of characterizing digital educational resources is commonly referred to as social tagging, whereas the collection of tags created by the different users individually is referred to as folksonomy. As a result, a number of studies have been reported in the field of Technology-enhanced Learning (TeL) which provide evidence that social tagging has the potential to enlarge metadata descriptions, as well as the formal structured vocabularies with additional terms derived by the resulted folksonomy but more in depth studies are needed regarding this enlargement process. Thus, one issue to investigate further is the possible influence of users' tagging motivation to the resulted enlarged metadata descriptions. In this paper we aim to investigate this issue by first proposing a methodology that aims to evaluate whether users' tagging motivation can influence (a) the enlargement of educational resources possible descriptions compared to the anticipated creators' descriptions and (b) the resulted folksonomy compared with formal structured vocabularies used by the creators of the educational resources and then, apply it to an existing LOR with more than 3,000 science education resources, 434 taggers and 14,707 social tags. Our experiments provided evidence that taggers with a specific type of tagging motivation can produce tags that are significantly different from formal metadata generated by the creators of the educational resources. © 2013 Elsevier Ltd. All rights reserved.

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