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Generative AI and Learning Analytics
Institute for Teaching and Learning Innovation, The University of Queensland Research and Education Center for the Learning Sciences, Brisbane, QLD, 4072, Australia.
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology.ORCID iD: 0000-0002-8543-3774
UniSA Educational Futures, University of South Australia, Campus Central City West, GPO Box 2471, Adelaide, SA, 5001, Australia.
Institute of Educational Technology, The Open University, Walton Hall, Milton Keynes, MK 6AA, UK.
2023 (English)In: Journal of Learning Analytics, E-ISSN 1929-7750, Vol. 10, no 3, p. 1-6Article in journal, Editorial material (Other academic) Published
Abstract [en]

This editorial looks back at the Journal of Learning Analytics (JLA) in 2023 and forward to 2024. Considering the recent proliferation of large language models such as GPT4 and Bard, the first section of this editorial points to the need for robust Generative AI (GenAI) analytics, calling for consideration of how GenAI may impact learning analytics research and practice. The second section looks back over the past year, providing statistics on submissions and considering the cost of publication in an open-access journal.

Place, publisher, year, edition, pages
Society for Learning Analytics Research , 2023. Vol. 10, no 3, p. 1-6
Keywords [en]
GenAI, Generative AI, learning analytics, practice, research
National Category
Learning
Identifiers
URN: urn:nbn:se:kth:diva-342172DOI: 10.18608/jla.2023.8333ISI: 001133089300002Scopus ID: 2-s2.0-85180720417OAI: oai:DiVA.org:kth-342172DiVA, id: diva2:1827634
Note

QC 20240115

Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-02-29Bibliographically approved

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Viberg, Olga

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