Addressing Student Non-Compliance in AI Use Declarations: Implications for Academic Integrity and Assessment in Higher Education

Autor/in	Chahna Gonsalves
Titel	Addressing Student Non-Compliance in AI Use Declarations: Implications for Academic Integrity and Assessment in Higher Education
Quelle	In: Assessment & Evaluation in Higher Education, 50 (2025) 4, S. 592-606Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Zusatzinformation	ORCID (Chahna Gonsalves)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0260-2938
DOI	10.1080/02602938.2024.2415654
Schlagwörter	Forschungsbericht; Foreign Countries; Student Behavior; Compliance (Psychology); Artificial Intelligence; Technology Uses in Education; Student Attitudes; Behavior Standards; Fear; Peer Influence; Self Disclosure (Individuals); Ethics; Integrity; College Students; Student Evaluation; School Policy; Trust (Psychology); Plagiarism; United Kingdom (London) + Suchen Sie Ihr Suchwort? Ausland; Student behaviour; Schülerverhalten; Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Furcht; Ethik; Integrität; Collegestudent; Schulnote; Studentische Bewertung; Schulpolitik; Plagiat
Abstract	This study examines the factors driving student non-compliance with AI use declarations in academic assessments at King's Business School, where 74% of students failed to declare AI usage despite declaration being a requirement of a mandatory coursework coversheet. Utilising the Theory of Planned Behaviour (TPB) as a framework, the research combines service evaluation survey data and semi-structured interviews to explore how attitudes, subjective norms, and perceived behavioural control influence compliance. Findings reveal that fear of academic repercussions, ambiguous guidelines, inconsistent enforcement, and peer influence are key barriers to AI use declaration. These factors complicate the declaration process, undermine transparency, and challenge academic integrity. The study extends the TPB model by highlighting the ethical and practical dilemmas posed by generative AI, which blur traditional norms of academic integrity. This research offers critical insights for policymakers, suggesting that clear, consistent, and trust-based policies are crucial in fostering ethical AI use. The findings underscore the importance of transparent communication and supportive institutional cultures to improve compliance. Ultimately, this study informs policy development by evaluating the effectiveness of declaration mechanisms and providing actionable recommendations to promote a culture of academic integrity in the evolving landscape of AI technologies. (As Provided).
Anmerkungen	Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2025/4/11