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    Inside Out: Detecting Learners' Confusion to Improve Interactive Digital Learning Environments

    255611.pdf (1.004Mb)
    Access Status
    Open access
    Authors
    Arguel, A.
    Lockyer, L.
    Lipp, Ottmar
    Lodge, J.
    Kennedy, G.
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Arguel, A. and Lockyer, L. and Lipp, O. and Lodge, J. and Kennedy, G. 2017. Inside Out: Detecting Learners' Confusion to Improve Interactive Digital Learning Environments. Journal of Educational Computing Research. 55 (4): pp. 526-551.
    Source Title
    Journal of Educational Computing Research
    DOI
    10.1177/0735633116674732
    ISSN
    0735-6331
    School
    School of Psychology and Speech Pathology
    Remarks

    Arguel, A. and Lockyer, L. and Lipp, O. and Lodge, J. and Kennedy, G., Inside Out: Detecting Learners' Confusion to Improve Interactive Digital Learning Environments, Journal of Educational Computing Research . 55 (4): pp. 526-551. Copyright © 2017 The Authors. Reprinted by permission of SAGE Publications

    URI
    http://hdl.handle.net/20.500.11937/56983
    Collection
    • Curtin Research Publications
    Abstract

    Confusion is an emotion that is likely to occur while learning complex information. This emotion can be beneficial to learners in that it can foster engagement, leading to deeper understanding. However, if learners fail to resolve confusion, its effect can be detrimental to learning. Such detrimental learning experiences are particularly concerning within digital learning environments (DLEs), where a teacher is not physically present to monitor learner engagement and adapt the learning experience accordingly. However, with better information about a learner's emotion and behavior, it is possible to improve the design of interactive DLEs (IDLEs) not only in promoting productive confusion but also in preventing overwhelming confusion. This article reviews different methodological approaches for detecting confusion, such as self-report and behavioral and physiological measures, and discusses their implications within the theoretical framework of a zone of optimal confusion. The specificities of several methodologies and their potential application in IDLEs are discussed.

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