Generative AI in the Australian education system: An open data set of stakeholder recommendations and emerging analysis from a public inquiry

Simon Knight, Camille Dickson -Deane,Keith Heggart,Kirsty Kitto, Dilek Cetindamar Kozanoglu, Damian Maher,Bhuva Narayan, Forooq Zarrabi

AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY(2023)

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摘要
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.
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policy analysis,content analysis,edtech,participatory,AI ethics
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