Counting clicks is not enough: validating a theorized model of engagement in learning analytics

Ed Fincham, Srećko Joksimović, Alexander Whitelock-Wainwright, Jan Paul Van Staalduinen, Vitomir Kovanović, Dragan Gašević

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    14 Citations (Scopus)

    Abstract

    Student engagement is often considered an overarching construct in educational research and practice. Though frequently employed in the learning analytics literature, engagement has been subjected to a variety of interpretations and there is little consensus regarding the very definition of the construct. This raises grave concerns with regards to construct validity: namely, do these varied metrics measure the same thing? To address such concerns, this paper proposes, quantifies, and validates a model of engagement which is both grounded in the theoretical literature and described by common metrics drawn from the field of learning analytics. To identify a latent variable structure in our data we used exploratory factor analysis and validated the derived model on a separate sub-sample of our data using confirmatory factor analysis. To analyze the associations between our latent variables and student outcomes, a structural equation model was fitted, and the validity of this model across different course settings was assessed using MIMIC modeling. Across different domains, the broad consistency of our model with the theoretical literature suggest a mechanism that may be used to inform both interventions and course design.

    Original languageEnglish
    Title of host publicationProceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19)
    Subtitle of host publicationLearning Analytics to Promote Inclusion and Success
    EditorsChristopher Brooks, Rebecca Ferguson, Ulrich Hoppe
    Place of PublicationNew York NY USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages501-510
    Number of pages10
    ISBN (Electronic)9781450362566
    DOIs
    Publication statusPublished - 2019
    EventInternational Learning Analytics & Knowledge Conference 2019 - Arizona State University, Tempe, United States of America
    Duration: 4 Mar 20198 Mar 2019
    Conference number: 9th
    https://lak19.solaresearch.org/

    Publication series

    NameACM International Conference Proceeding Series

    Conference

    ConferenceInternational Learning Analytics & Knowledge Conference 2019
    Abbreviated titleLAK 2019
    Country/TerritoryUnited States of America
    CityTempe
    Period4/03/198/03/19
    Internet address

    Keywords

    • Engagement
    • Factor analysis
    • Measurement invariance
    • MOOCs
    • Structural equation modeling

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