Birks, D. orcid.org/0000-0003-3055-7398 and Clare, J. orcid.org/0000-0003-0444-4189 (2023) Linking artificial intelligence facilitated academic misconduct to existing prevention frameworks. International Journal for Educational Integrity, 19 (1). 20.
Abstract
This paper connects the problem of artificial intelligence (AI)-facilitated academic misconduct with crime-prevention based recommendations about the prevention of academic misconduct in more traditional forms. Given that academic misconduct is not a new phenomenon, there are lessons to learn from established information relating to misconduct perpetration and frameworks for prevention. The relevance of existing crime prevention frameworks for addressing AI-facilitated academic misconduct are discussed and the paper concludes by outlining some ideas for future research relating to preventing AI-facilitated misconduct and monitoring student attitudes and behaviours with respect to this type of behaviour.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
Keywords: | Artificial intelligence; Large language models; Academic integrity; Academic misconduct; Prevention; Detection; Opportunity reduction; Situational crime prevention |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Jan 2024 13:42 |
Last Modified: | 31 Jan 2024 13:42 |
Published Version: | http://dx.doi.org/10.1007/s40979-023-00142-3 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Identification Number: | 10.1007/s40979-023-00142-3 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:205031 |