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

5 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
CountryUnited 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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