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Cited by 5Academic integrity and plagiarismArtificial Intelligence in EducationEngineering Education and Curriculum Development

Beyond assessment security: A critical policy analysis of four alternative strategies to uphold academic integrity and adopt the GenAI transformation of teaching and learning for an accredited engineering degree

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Nikolic, Sasha, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, New South Wales, Australia, Ros, Montserrat, Al-Abdeli, Yasir M., Fairweather, Helen, School of Engineering, Edith Cowan University, Western Australia, Australia, Head of Accreditation, Engineers Australia, Brisbane, Australia·2025·STEM Education
DOI 10.3934/steme.2025027
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Abstract

Generative Artificial Intelligence (GenAI), exemplified by tools such as ChatGPT, has posed significant challenges and opportunities in the realm of academic integrity, particularly in engineering education. This commentary critically examines alternative strategies that go beyond traditional assessment security, aiming to uphold academic integrity while embracing the transformative potential of GenAI in teaching and learning. In the context of programs that rely on unit level outcomes to determine the overall student progression (not the programmatic approach to progression), this study identifies and explores four strategies that may offer potential improvements to assessment security: Ⅰ - risk‑level analysis, which aligns the mix of supervised and unsupervised assessments with their susceptibility to GenAI‑enabled misconduct; Ⅱ - adaptive grade scaling, which links marks for unsupervised work to performance in supervised tasks, thereby discouraging dishonest outsourcing; Ⅲ - gatekeeper units, which embed high‑stakes supervised checkpoints that verify the essential competencies before progression; and Ⅳ - maintaining the status quo, which exposes the limitations of solely relying on the existing security measures. The analysis highlights the potential benefits and weaknesses of each approach, supporting holistic decision-making on policies that improve the ability of students to meet the competency requirements (compared to strategy Ⅳ) while fostering a culture of honesty and ethical behavior. By providing a thorough examination of these strategies, this study contributes valuable insights for educators, policymakers, and researchers, aiming to facilitate a balanced approach that aligns with the accreditation requirements and prepares students for the ethical use of GenAI in their professional careers. This commentary broadens and stimulates discussions on academic integrity in the GenAI era, thus providing practical guidance for educators and institutions.

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Research works printed but not linked: 6

  1. Abeysekera, I., ChatGPT and academia on accounting assessments. Journal of Open Innovation: Technology, Market, and Complexity, 2024, 10(1): 100213. https://www.sciencedirect.com/science/article/pii/S2199853124000076.
  2. Neupane, A., Shahi, T., Cowling, M. and Tanna, D., Threading the GenAI needle: unpacking the ups and downs of GenAI for higher education stakeholders. Journal of Applied Learning and Teaching, 2024, 7(2): 1-9. https://doi.org/10.37074/jalt.2024.7.2 · DOI
  3. Fatahi, B., Nguyen, L.D., Khabbaz, H. and Hadgraft, R., Virtual teammates: transforming engineering learning through generative AI integration. In 35th Australasian Association of Engineering Education Conference, Christchurch, New Zealand, 2024.
  4. Belkina, M., Neal, P., Grundy, S., Hassan, G.M., Haque, R., Daniel, S., et al., Systematic literature review of GenAI integration in higher education and analysis of opportunities for engineering education. In Proceedings of the 35th Annual Conference of the Australasian Association for Engineering Education (AAEE 2024), Christchurch, New Zealand. 2024, 1-10.
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  6. University of Technology Sydney, Next steps for GenAI and assessment reform at UTS: a response to TEQSA. 2024. https://educationexpress.uts.edu.au/blog/2024/09/02/next-steps-for-genai-and-assessment-reform -uts-response-teqsa/ 52. Hurdle requirements. 2025, accessed 19/05/2025. https://www.adelaide.edu.au/learning/resources-for-educators/assessment/hurdle-requirements 53. GenAI and integrity: the arguments to reshape the thesis assessment structure. 2024, accessed 08/10/2025. https://www.aaieec.org/post/genai-and-integrity-the-arguments-to-reshape-the-thesis-assessment -structure.

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Authors
Nikolic, S., Faculty of Engineering and Information Sciences, U. O. W., Ros, M., Al-Abdeli, Y. M., Fairweather, H., School of Engineering, E. C. U., & Head of Accreditation, E. A.
Affiliations
  • University of Wollongong (AU)
  • Edith Cowan University (AU)
ORCID
Venue
STEM Education
Publisher
American Institute of Mathematical Sciences (AIMS)
Published
2025
Volume
5
Issue
4
Pages
564-586
ISSN
2767-1925 (ISSN-L)
DOI
10.3934/steme.2025027
OpenAlex
W4411049328
Cited by
5
References
49
Citations by year
2026: 5
FWCI
5.20
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
  • STEM Education (publishedVersion, cc-by-nc-sa)
  • Australasian Journal of Paramedicine (submittedVersion, cc-by)
Topics
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Engineering › Media Technology › Engineering Education and Curriculum Development
Keywords
generative AI, academic integrity, assessment security, engineering education, ChatGPT, assessment design, student progression, accreditation, academic misconduct, ethical use of AI

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