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A Current Overview of the Use of Learning Analytics Dashboards
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA;CSS)ORCID iD: 0000-0002-3738-7945
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA;CSS)ORCID iD: 0000-0002-3297-0189
University of New Brunswick, Canada.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0001-7313-1720
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2024 (English)In: Education Sciences, E-ISSN 2227-7102, Vol. 14, no 1, article id 82Article in journal (Refereed) Published
Abstract [en]

The promise of Learning Analytics Dashboards in education is to collect, analyze, and visualize data with the ultimate ambition of improving students’ learning. Our overview of the latest systematic reviews on the topic shows a number of research trends: learning analytics research is growing rapidly; it brings to the front inequality and inclusiveness measures; it reveals an unclear path to data ownership and privacy; it provides predictions which are not clearly translated into pedagogical actions; and the possibility of self-regulated learning and game-based learning are not capitalized upon. However, as learning analytics research progresses, greater opportunities lie ahead, and a better integration between information science and learning sciences can bring added value of learning analytics dashboards in education.

Place, publisher, year, edition, pages
MDPI, 2024. Vol. 14, no 1, article id 82
Keywords [en]
learning analytics dashboards, LAD, trends
National Category
Computer Systems Learning
Research subject
Computer Science, Information and software visualization; Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-126815DOI: 10.3390/educsci14010082ISI: 001149183000001Scopus ID: 2-s2.0-85183134033OAI: oai:DiVA.org:lnu-126815DiVA, id: diva2:1828501
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, 2020-01221Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-08-22Bibliographically approved

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Masiello, ItaloMohseni, ZeynabNordmark, SusannaRundquist, Rebecka

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Masiello, ItaloMohseni, ZeynabNordmark, SusannaAugustsson, HannaRundquist, Rebecka
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Department of computer science and media technology (CM)Department of Pedagogy and Learning
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