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Introduction

The rise of accessible large language models (LLMs) has revolutionised higher education, enabling machines to mimic human-like text generation and exceed traditional benchmarks such as the Turing Test (Suleyman, 2023). These tools act as a ‘double-edged sword’ (Terzimehić et al., 2025, p. 1), enhancing research and learning while posing risks of overreliance, inaccuracies and threats to academic integrity in traditional assessment methods (Kosmyna et al., 2025).

Academic integrity in higher education (HE) encompasses honesty, respect for intellectual property and ethical conduct (QAA, 2025). The rise of artificial intelligence (AI), however, has intensified challenges, particularly in AI-facilitated plagiarism, with instructors reporting more instances of cheating (Bittle & El-Gayar, 2025). Beyond dishonesty, overreliance on AI can cause cognitive offloading, weakening critical thinking and deep learning (Kosmyna et al., 2025). In response, some institutions have adopted restrictive measures, including outright AI bans (Moorhouse et al., 2023).

This blog post identifies that the rise of AI necessitates a redesign of HE essay-based assessments to uphold academic integrity and prepare graduates for an AI-integrated workforce. Banning AI is a reductive response; instead, educators must critically reevaluate assessment design. If AI can complete tasks effectively, the flaw lies in the assessment rather than the technology, especially given AI’s inevitability in future professional practice (Leaton Gray et al., 2025).

‘Banning AI is a reductive response; instead, educators must critically reevaluate assessment design.’

The role of traditional essays

Essay writing remains central to HE assessments, evaluating knowledge, source engagement and communication skills (QAA, 2023). However, its efficacy in meeting contemporary demands is increasingly questioned (QAA, 2023). Generative AI (GenAI) aids students in overcoming essay challenges by offering structure, vocabulary and ideas, often outperforming human efforts (Malik et al., 2023), yet it prompts concerns about learners’ authentic intellectual contributions.

Rethinking essay assessments with AI

A ‘catch and punish’ strategy proves to be ineffective owing to unreliable AI detection tools, fostering suspicion among educators (Leaton Gray et al., 2025). Instead, the ‘AI Collaboration Zone’ should be prioritised as the optimal assessment framework; a partnership wherein generative AI augments, but does not replace, students’ creative and cognitive efforts (Dorobat et al., 2024). Dorobat et al. (2024) highlight case-based projects where students integrate concepts through AI-supported research and analysis. Similarly, AI-assisted dialogues enhance reflection and creativity, positioning AI as a collaborative coauthor or feedback tool that surpasses traditional essay formats (Bouziane & Bouziane, 2024).

Conclusion

Higher education must embrace AI as a collaborative tool to redesign traditional essay assignments, transforming them into dynamic, multidimensional tasks. By centring assessments on research, reflection and application alongside GenAI, educators can foster critical thinking and essential workplace skills while addressing risks such as plagiarism and overreliance (Leaton Gray et al., 2025).

References

Bittle, K., & El-Gayar, O. (2025). Generative AI and academic integrity in higher education: A systematic review and research agenda. Information, 16(4), 296.

Bouziane, K., & Bouziane, A. (2024). AI versus human effectiveness in essay evaluation. Discover Education, 3, 201.

Dorobat, C. E., Larner, A. Sutherst, J., & Underwood, S. (2024). Generative AI and assessment design: Preliminary guidance for turning principles into practice in higher education.

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. arXiv preprint, arXiv:2506.08872. Ìý

Leaton Gray, S., Edsall, D., & Parapadakis, D. (2025). AI-based digital cheating at university, and the case for new ethical pedagogies. Journal of Academic Ethics, 23, 2069–2086.

Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki, M. (2023). Exploring artificial intelligence in academic essay: Higher education student’s perspective. International Journal of Educational Research Open, 5, 100296. .

Moorhouse, B. L., Yeo, M. A., & Wan, Y. (2023). Generative AI tools and assessment: Guidelines of the world’s top ranking universities. Computers and Education Open, 5, 100151.

Quality Assurance Agency for Higher Education [QAA]. (2023). Making learning visible in a world of invisible GenAI.

Quality Assurance Agency for Higher Education [QAA]. (2025). Generative artificial intelligence.

Saborío-Taylor, S., & Rojas-Ramírez, F. (2024). Universal design for learning and artificial intelligence in the digital era: Fostering inclusion and autonomous learning. International Journal of Professional Development, Learners and Learning, 6(2), ep2408.

Suleyman, M. (2023). The coming wave. Penguin Random House UK.

Terzimehić, N., Bühler, B., & Kasneci, E. (2025). Conversational AI as a catalyst for informal learning: An empirical large-scale study on LLM use in everyday learning. arXiv preprint, arXiv:2506.11789.