Simon Knight, Camille Dickson-Deane, Keith Heggart, Kirsty Kitto, Dilek Çetindamar Kozanoğlu, Damian Maher, Bhuva Narayan, Forooq Zarrabi
{"title":"澳大利亚教育系统中的生成式人工智能:利益相关者建议的开放数据集和来自公共调查的新分析","authors":"Simon Knight, Camille Dickson-Deane, Keith Heggart, Kirsty Kitto, Dilek Çetindamar Kozanoğlu, Damian Maher, Bhuva Narayan, Forooq Zarrabi","doi":"10.14742/ajet.8922","DOIUrl":null,"url":null,"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.\nImplications for practice or policy\n\nFor practitioners, policymakers, and researchers. the paper provides an overview and synthesis of submission recommendations and their themes, by source type.\nFor respondents to the inquiry (sources), the paper supports reflection regarding synergies and gaps in recommendations, pointing to opportunity for collaboration and policy development.\nFor stakeholders with responsibility for aspects of policy delivery and/or those applying a critical lens to the inquiry and recommendation framing(s), the paper offers actionable insight.\n","PeriodicalId":47812,"journal":{"name":"Australasian Journal of Educational Technology","volume":"16 10","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"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 Çetindamar Kozanoğlu, Damian Maher, Bhuva Narayan, Forooq Zarrabi\",\"doi\":\"10.14742/ajet.8922\",\"DOIUrl\":null,\"url\":null,\"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.\\nImplications for practice or policy\\n\\nFor practitioners, policymakers, and researchers. the paper provides an overview and synthesis of submission recommendations and their themes, by source type.\\nFor respondents to the inquiry (sources), the paper supports reflection regarding synergies and gaps in recommendations, pointing to opportunity for collaboration and policy development.\\nFor stakeholders with responsibility for aspects of policy delivery and/or those applying a critical lens to the inquiry and recommendation framing(s), the paper offers actionable insight.\\n\",\"PeriodicalId\":47812,\"journal\":{\"name\":\"Australasian Journal of Educational Technology\",\"volume\":\"16 10\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Australasian Journal of Educational Technology\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://doi.org/10.14742/ajet.8922\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australasian Journal of Educational Technology","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.14742/ajet.8922","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Generative AI in the Australian education system: An open data set of stakeholder recommendations and emerging analysis from a public inquiry
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.
Implications for practice or policy
For practitioners, policymakers, and researchers. the paper provides an overview and synthesis of submission recommendations and their themes, by source type.
For respondents to the inquiry (sources), the paper supports reflection regarding synergies and gaps in recommendations, pointing to opportunity for collaboration and policy development.
For stakeholders with responsibility for aspects of policy delivery and/or those applying a critical lens to the inquiry and recommendation framing(s), the paper offers actionable insight.