Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education

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.

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Publication Details

Journal
Assessment & Evaluation in Higher Education
Published
2024-10-22
DOI
https://doi.org/10.1080/02602938.2024.2415654
Citations
47
Primary Topic
Academic integrity and plagiarism
Type
article
Field-Weighted Citation Impact
24.72
Controls
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article

Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education

Chahna Gonsalves
47 citations
Assessment & Evaluation in Higher Education
Academic integrity and plagiarism
24.72
article

Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education

Chahna Gonsalves
article en
47 citations

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.

Assessment & Evaluation in Higher EducationVol. 50(4)
King's College London (GB)
Quality Education
Openalex Percentile: Top 0%
Academic integrity and plagiarism
24.72
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