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Cited by 110Academic integrity and plagiarismArtificial Intelligence in EducationStudent Assessment and Feedback

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Talk is cheap: why structural assessment changes are needed for a time of GenAI

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Corbin, Thomas, Dawson, Phillip, Liu, Danny·2025·Assessment & Evaluation in Higher Education
DOI 10.1080/02602938.2025.2503964
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Abstract

Generative AI (GenAI) challenges assessment validity by enabling students to complete tasks without demonstrating genuine capability. In response to this challenge, institutions have developed and implemented various approaches that aim to communicate permissible AI use to students. Familiar examples include the ‘traffic light’ approach now commonly found within institutional policy. While well-intentioned, these approaches share a common limitation: They focus primarily on communicating rules rather than redesigning assessment mechanics. To clarify why such approaches fail, and to guide more effective responses, this paper introduces a novel conceptual distinction between discursive changes to assessment (modifications relying solely on instructions students remain free to ignore) and structural changes (modifications that reshape the underlying mechanics of assessment tasks themselves). Through a critical analysis of prominent frameworks, we demonstrate that current approaches predominantly rely on discursive changes that create what we term an ‘enforcement illusion’. We find that educational frameworks frequently borrow the language of socially familiar structural systems (like vehicular traffic lights) while lacking their actual enforcement capabilities, creating an illusion of assessment security. In place of this, we argue for a shift towards structural assessment redesign that builds validity into assessment architecture rather than attempting to impose it through unen…

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Crossref · 10.1080/02602938.2025.2503964

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Research works printed but not linked: 1

  1. Perkins, M., J. Roe, B. H. Vu, D. Postma, D. Hickerson, J. McGaughran, and H. Q. Khuat. 2024b. “GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education.” arXiv Preprint arXiv:2403.19148. · arXiv

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Metadata

Authors
Corbin, T., Dawson, P., & Liu, D.
Affiliations
  • Deakin University (AU)
  • The University of Sydney (AU)
Corresponding author
Corbin, Thomas
ORCID
Venue
Assessment & Evaluation in Higher Education
Publisher
Informa UK Limited
Published
2025-05-15
Volume
50
Issue
7
Pages
1087-1097
ISSN
  • 0260-2938 (ISSN-L)
  • 1469-297X
DOI
10.1080/02602938.2025.2503964
OpenAlex
W4410403683
Cited by
107
References
14
Citations by year
2026: 89 · 2025: 18
FWCI
111.30
Type
journal article
Language
en
Open access
Licence
Locations
  • Assessment & Evaluation in Higher Education (publishedVersion, cc-by-nc-nd)
  • Figshare (submittedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Education › Academic integrity and plagiarism
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Education › Student Assessment and Feedback
Keywords
generative AI, assessment validity, discursive change, AI policy in higher education, student use of AI

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