Institutional Governance Authenticity and Student Responses to Artificial Intelligence Assessment Guidelines in Higher Education
Year: 2026
Type: preprint
Abstract: Rapid proliferation of generative artificial intelligence (GenAI) has prompted universities worldwide to issue guidelines on student AI use in assessment. While existing research catalogues policy content and student misuse, little is known about how students perceive these guidelines and how such perceptions shape behaviour. This paper argues that current research treats guidelines as a binary intervention—present or absent—overlooking their psychological and institutional authenticity. Drawing on procedural justice and neutralisation theories, we contend that when guidelines are vague, invisible, unenforceable, and treated by academics as box-ticking exercises, they fail as integrity safeguards and may instead provide justifications for disingenuous AI use. We further argue that this pattern reflects institutional compulsions—legal, reputational, and competitive—that drive guideline issuance despite known limitations. We propose a research agenda centred on guideline authenticity and its effects on fairness perceptions, moral neutralisation, and compliance intentions, alongside perceptions of institutional motivation. A sequential mixed-methods design is outlined, drawing on UAE and UK contexts. The agenda aims to move institutional practice beyond symbolic policy-making toward genuinely embedded academic integrity cultures.
Source: Research Square
Authors: Peter Tor Atorough, Sara Hajikazemi
Institutions: De Montfort University, Queen Mary University of London
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7224767935