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Generative AI in the Australian Education System: An Open Data Set of Stakeholder Recommendations and Emerging Analysis from a Public Inquiry

Authors :
Simon Knight
Camille Dickson-Deane
Keith Heggart
Kirsty Kitto
Dilek Cetindamar Kozanoglu
Damian Maher
Bhuva Narayan
Forooq Zarrabi
Source :
Australasian Journal of Educational Technology. 2023 39(5):101-124.
Publication Year :
2023

Abstract

The launch of new tools in late 2022 heralded significant growth in attention to the impacts of generative AI (GenAI) in education. Claims of the potential impact on education are contested, but there are clear risks of inappropriate use particularly where GenAI aligns poorly with learning aims. In response, in mid-2023, the Australian Federal Government held an inquiry, calling for public submissions. This inquiry offers a lens onto the policy framing of GenAI in education and provides the object of investigation for this paper. We use the inquiry submissions, extracting structured claims from each. This extraction is provided as an open data set for further research, while this paper focuses on our analysis of the policy recommendations made.

Details

Language :
English
ISSN :
1449-3098 and 1449-5554
Volume :
39
Issue :
5
Database :
ERIC
Journal :
Australasian Journal of Educational Technology
Publication Type :
Academic Journal
Accession number :
EJ1412896
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.14742/ajet.8922