Generative AI and Learning Analytics

Hassan Khosravi; Olga Viberg; Vitomir Kovanovic; Rebecca Ferguson

doi:10.18608/jla.2023.8333

Authors

Hassan Khosravi The University of Queensland https://orcid.org/0000-0001-8664-6117
Olga Viberg KTH Royal Institute of Technology https://orcid.org/0000-0002-8543-3774
Vitomir Kovanovic University of South Australia https://orcid.org/0000-0001-9694-6033
Rebecca Ferguson The Open University https://orcid.org/0000-0002-8566-8231

DOI:

https://doi.org/10.18608/jla.2023.8333

Keywords:

generative AI, GenAI, learning analytics, research, practice, editorial

Abstract

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.

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Generative AI and Learning Analytics

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