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Learning Analytics Dashboard for Motivation and Performance

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Intelligent Tutoring Systems (ITS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12149))

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Abstract

Deploying Learning Analytics that significantly improve learning outcomes remains a challenge. Motivation has been found to be related to academic achievement and is argued to play an essential role in efficient learning. We developed a Learning Analytics dashboard and designed an intervention that relies on goal orientation and social comparison. Subjects can see a prediction of their final grade in a course as well as how they perform in comparison to classmates with similar goal grades. Those with access to the dashboard ended up more motivated than those without access, outperformed their peers as the course progressed and achieved higher final grades. Our results indicate that learner-oriented dashboards are technically feasible and may have tangible benefits for learners.

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Author information

Authors and Affiliations

  1. Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands

    Damien S. Fleur & Bert Bredeweg

  2. Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands

    Damien S. Fleur & Wouter van den Bos

  3. Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany

    Wouter van den Bos

  4. Amsterdam University of Applied Sciences, Amsterdam, The Netherlands

    Bert Bredeweg

Authors
  1. Damien S. Fleur
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  2. Wouter van den Bos
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  3. Bert Bredeweg
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Corresponding author

Correspondence to Damien S. Fleur .

Editor information

Editors and Affiliations

  1. Athabasca University, Athabasca, AB, Canada

    Vivekanandan Kumar

  2. University of West Attica, Egaleo, Greece

    Christos Troussas

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Fleur, D.S., van den Bos, W., Bredeweg, B. (2020). Learning Analytics Dashboard for Motivation and Performance. In: Kumar, V., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science(), vol 12149. Springer, Cham. https://doi.org/10.1007/978-3-030-49663-0_51

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  • DOI: https://doi.org/10.1007/978-3-030-49663-0_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49662-3

  • Online ISBN: 978-3-030-49663-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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