Linking artificial intelligence facilitated academic misconduct to existing prevention frameworks

Author:

Birks Daniel,Clare JosephORCID

Abstract

AbstractThis 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.

Publisher

Springer Science and Business Media LLC

Subject

Social Sciences (miscellaneous),Education

Reference42 articles.

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