Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

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

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read Online Read More Add to Saved list
  • Author(s): Chahna Gonsalves (ORCID Chahna Gonsalves (ORCID 0000-0002-3516-4297)
  • Language:
    English
  • Source:
    Assessment & Evaluation in Higher Education. 2025 50(4):592-606.
  • Publication Date:
    2025
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      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
    • Peer Reviewed:
      Y
    • Source:
      15
    • Intended Audience:
      Policymakers
    • Education Level:
      Higher Education
      Postsecondary Education
    • Subject Terms:
      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
    • Subject Terms:
      United Kingdom (London)
    • Accession Number:
      10.1080/02602938.2024.2415654
    • ISSN:
      0260-2938
      1469-297X
    • 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.
    • Abstract:
      As Provided
    • Publication Date:
      2025
    • Accession Number:
      EJ1484911