Transforming assessment in higher education in the era of generative AI
From knowledge control to critical thinking development
DOI:
https://doi.org/10.32674/n7pdhe28Keywords:
assessment, academic integrity, critical thinking, generative AI, higher educationAbstract
The wider use of generative AI has raised concerns about how student learning is assessed in higher education. Tasks once considered reliable no longer guarantee independent work, so assessment is shifting in focus. While final written outputs still matter, greater emphasis is now placed on how students engage with material, construct arguments, verify information, and demonstrate reasoning. Attention is also given to how digital tools are used, especially when they replace rather than support thinking. This article examines changes in assessment practices in response to generative AI, identifies vulnerable formats, and highlights those that better reflect genuine learning, based on research, policy, and university practice.
References
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(1), 10. https://doi.org/10.1186/s41239-024-00444-7 DOI: https://doi.org/10.1186/s41239-024-00444-7
Ahangama, N. (2026). Designing assessments in the generative AI era: a tailored assessment framework for ICT tertiary education. International Journal of Educational Technology in Higher Education, 23(1), 9. https://doi.org/10.1186/s41239-026-00582-0 DOI: https://doi.org/10.1186/s41239-026-00582-0
Ardito, C.G. (2025). Generative AI detection in higher education assessments. New Directions for Teaching and Learning, 2025(182), 11–28. https://doi.org/10.1002/tl.20624 DOI: https://doi.org/10.1002/tl.20624
Ba, S., Zhan, Y., Huang, L., & Lu, G. (2025). Investigating the impact of ChatGPT-assisted feedback on the dynamics and outcomes of online inquiry-based discussion. British Journal of Educational Technology, 56(5), 1710–1734. https://doi.org/10.1111/bjet.13605 DOI: https://doi.org/10.1111/bjet.13605
Chan, C.K.Y., & Tsi, L.H.Y. (2024). Will generative AI replace teachers in higher education? A study of teacher and student perceptions. Studies in Educational Evaluation, 83(1), 101395. https://doi.org/10.1016/j.stueduc.2024.101395 DOI: https://doi.org/10.1016/j.stueduc.2024.101395
Corbin, T., Bearman, M., Boud, D., & Dawson, P. (2025). The wicked problem of AI and assessment. Assessment & Evaluation in Higher Education, 51(4), 736-752. https://doi.org/10.1080/02602938.2025.2553340 DOI: https://doi.org/10.1080/02602938.2025.2553340
Curtis, G.J. (2025). The two-lane road to hell is paved with good intentions: Why an all-or-none approach to generative AI, integrity, and assessment is insupportable. Higher Education Research & Development, 44(8), 2151–2158. https://doi.org/10.1080/07294360.2025.2476516 DOI: https://doi.org/10.1080/07294360.2025.2476516
Dai, K., Liu, Y., & Zhang, X. (2026). Generative AI in higher education: A bibliometric review of emerging trends, power dynamics, and global research landscapes. Computers and Education: Artificial Intelligence, 10, 100544. https://doi.org/10.1016/j.caeai.2026.100544 DOI: https://doi.org/10.1016/j.caeai.2026.100544
Dei, M. О. (2025). The impact of AI on the adaptation of educational materials and teaching methods to the needs of each student. LatIA, 3, 124. https://doi.org/10.62486/latia2025124 DOI: https://doi.org/10.62486/latia2025124
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 DOI: https://doi.org/10.1007/s11023-018-9482-5
Francis, N.J., Jones, S., & Smith, D.P. (2025). Generative AI in higher education: Balancing innovation and integrity. British Journal of Biomedical Science 81, 14048. https://doi.org/10.3389/bjbs.2024.14048 DOI: https://doi.org/10.3389/bjbs.2024.14048
Henderson, M., Bearman, M., Chung, J., Fawns, T., Buckingham Shum, S., Matthews, K.E., & de Mello Heredia, J. (2025). Comparing generative AI and teacher feedback: Student perceptions of usefulness and trustworthiness. Assessment & Evaluation in Higher Education, 1-16. https://doi.org/10.1080/02602938.2025.2502582 DOI: https://doi.org/10.1080/02602938.2025.2502582
Jin, Y., Martinez-Maldonado, R., Gašević, D., & Yan, L. (2025). GLAT: The generative AI literacy assessment test. Computers and Education: Artificial Intelligence, 9, 100436. https://doi.org/10.1016/j.caeai.2025.100436 DOI: https://doi.org/10.1016/j.caeai.2025.100436
Kehler, T. P., Page, S. E., Pentland, A., Reeves, M., & Brown, J. S. (2025). Amplifying human creativity and problem solving with AI through generative collective intelligence. ArXiv. https://doi.org/10.48550/arXiv.2505.19167
Kofinas, A. K., Tsay, C. H.-H., & Pike, D. (2025). The impact of generative AI on academic integrity of authentic assessments within a higher education context. British Journal of Educational Technology, 56(6), 2522–2549. https://doi.org/10.1111/bjet.13585 DOI: https://doi.org/10.1111/bjet.13585
Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL Institute of Education Press.
Monash University. (2024). Responsible use of AI in education. Learning and Teaching (TeachHQ). https://www.monash.edu/learning-teaching/teachhq/Teaching-practices/artificial-intelligence/responsible-use
OECD. (2026). OECD digital education outlook 2026: Exploring effective uses of generative AI in education. Paris: OECD Publishing. https://doi.org/10.1787/062a7394-en DOI: https://doi.org/10.1787/062a7394-en
Qu, Y., Loo, H.E., & Wang, J. (2025). Generative artificial intelligence in higher education: Emotional tensions and ethical declaration. British Journal of Educational Technology, 1-20. https://doi.org/10.1111/bjet.70029 DOI: https://doi.org/10.1111/bjet.70029
QAA. (2023a). The rise of artificial intelligence software and potential risks for academic integrity. Retrieved from https://www.qaa.ac.uk/docs/qaa/members/the-rise-of-artificial-intelligence-software-and-potential-risks-for-academic-integrity.pdf
QAA. (2024a). Quality compass: Navigating the complexities of the artificial intelligence era in higher education. Retrieved from https://www.qaa.ac.uk/docs/qaa/news/quality-compass-navigating-the-complexities-of-the-artificial-intelligence-era-in-higher-education.pdf
QAA. (2024b). Reconsidering assessment for the ChatGPT era: Advice on developing sustainable assessment strategies. Retrieved from https://www.qaa.ac.uk/docs/qaa/members/reconsidering-assessment-for-the-chat-gpt-era.pdf?sfvrsn=38d3af81_6
Shevchenko, A., & Antoshkina, V. (2023). Modern legal education in Ukraine as the basis of professional activity: Problems and prospects. Legal Horizons, 17(2), 008–021. https://doi.org/10.54477/LH.25192353.2023.2.pp.008-021 DOI: https://doi.org/10.54477/LH.25192353.2023.2.pp.8-21
Tertiary Education Quality and Standards Agency. (2023). Assessment reform for the age of artificial intelligence. Retrieved from https://www.teqsa.gov.au/guides-resources/resources/corporate-publications/assessment-reform-age-artificial-intelligence
University of British Columbia (2025). Ai skills accelerator for it, digital and enterprise systems professionals. Retrieved from https://extendedlearning.ubc.ca/sites/default/files/2025-09/ubc-ai-skills-accelerator-student-guide.pdf
Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025). Rethinking the importance of social norms in generative AI adoption: Investigating the acceptance and use of generative AI among higher education students. International Journal of Educational Technology in Higher Education, 22(1), 38. https://doi.org/10.1186/s41239-025-00535-z DOI: https://doi.org/10.1186/s41239-025-00535-z
Usher, M. (2025). Generative AI vs. instructor vs. peer assessments: A comparison of grading and feedback in higher education. Assessment & Evaluation in Higher Education, 50(6), 912–927. https://doi.org/10.1080/02602938.2025.2487495 DOI: https://doi.org/10.1080/02602938.2025.2487495
Usher, M., & Faraon, M. (2025). Who grades best? Comparing ChatGPT, peer, and instructor evaluations across varying levels of student project quality. Assessment & Evaluation in Higher Education, 1-20. https://doi.org/10.1080/02602938.2025.2588682 DOI: https://doi.org/10.1080/02602938.2025.2588682
Walton, J., Bearman, M., Crawford, N., Tai, J. H-M., & Boud, D. (2025). How university students work on assessment tasks with generative artificial intelligence: Matters of judgement. Assessment & Evaluation in Higher Education. https://doi.org/10.1080/02602938.2025.2570328 DOI: https://doi.org/10.1080/02602938.2025.2570328
Wang, F., Li, N., Cheung, A. C. K., & Wong, G. K. W. (2025). In GenAI we trust: An investigation of university students’ reliance on and resistance to generative AI in language learning. International Journal of Educational Technology in Higher Education, 22(1), 59. https://doi.org/10.1186/s41239-025-00547-9 DOI: https://doi.org/10.1186/s41239-025-00547-9
Xia, Q., Weng, X., Ouyang, F., Lin, T.J., & Chiu, T.K.F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21(1), 40. https://doi.org/10.1186/s41239-024-00468-z DOI: https://doi.org/10.1186/s41239-024-00468-z
Yan, L., Martinez-Maldonado, R., Jin, Y., Echeverria, V., Milesi, M., Fan, J., Zhao, L., Alfredo, R., Li, X., & Gašević, D. (2025). The effects of generative AI agents and scaffolding on enhancing students’ comprehension of visual learning analytics. Computers & Education, 234, 105322. https://doi.org/10.1016/j.compedu.2025.105322 DOI: https://doi.org/10.1016/j.compedu.2025.105322
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6 DOI: https://doi.org/10.1186/s41239-024-00453-6
Zhan, Y., Boud, D., Dawson, P., & Yan, Z. (2025). Generative artificial intelligence as an enabler of student feedback engagement: A framework. Higher Education Research & Development, 44(5), 1289–1304. https://doi.org/10.1080/07294360.2025.2476513 DOI: https://doi.org/10.1080/07294360.2025.2476513
Zhan, Y., &Yan, Z. (2025). Students’ engagement with ChatGPT feedback: Implications for student feedback literacy in the context of generative artificial intelligence. Assessment & Evaluation in Higher Education, 1-14. https://doi.org/10.1080/02602938.2025.2471821 DOI: https://doi.org/10.1080/02602938.2025.2471821
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