Contract Cheating: A Summative Look Back and a Path Forward

Eaton, Sarah Elaine; Stoesz, Brenda M.; Seeland, Josh; Curtis, Guy J.; Clare, Joseph; Rundle, Kiata

doi:10.1007/978-3-031-12680-2_20

Cited by 6 publications

(1 citation statement)

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“…There is considerable contemporary research on non-AI-related academic integrity (e.g., see Curtis, in press 2023;Eaton 2023;Eaton et al 2022, for a selection of edited collections on these issues). As with crime more broadly (Felson & Clarke 1998), the takeaway message from the prevention-focused academic integrity literature largely rests on rational-choice informed interpretations of behaviour (e.g., Awdry & Ives 2021;Hodgkinson et al 2016;Ogilvie & Stewart 2010) and the importance of removing the opportunity to commit specific types of academic misconduct (e.g.…”

Section: Preventing Ai-facilitated Academic Misconductmentioning

confidence: 99%

Linking artificial intelligence facilitated academic misconduct to existing prevention frameworks

Birks,

Clare

2023

Int J Educ Integr

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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.

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