I convened a cross institutional workshop on GenAI and assessment and developed inclusive AI aware approaches that strengthen student critical thinking, transparency, and digital literacy through research informed practice.
Our challenge / opportunity
The rapid adoption of Generative AI (GenAI) tools by students created uncertainty around academic integrity, assessment design, and the future of teaching. Traditional assessments risked being gamed by AI, while educators lacked evidence‑based guidance on integrating these tools in ways that support learning rather than undermine it.
Our solution (approach)
Framing the problem:
Traditional assessments often measure static product outcomes rather than student process, analysis, and judgement. With GenAI, the ability of students to generate text and code autonomously required a shift towards assessments that foreground critical thinking, metacognition, and process evaluation.
How we responded:
- Designed and facilitated an inclusive cross‑institutional symposium to gather diverse perspectives on AI and assessment.
- Developed practitioner resources drawing from the symposium outcomes — including examples of AI‑integrated assessment tasks that emphasise reasoning, critique, and iteration.
- Shared evidence‑informed practice with faculty colleagues and contributed to wider sector discussions through academic networks.
Tools & methods:
- Workshop facilitation with breakout activities to prototype AI‑aware assessment tasks
- Case examples of AI co‑creation exercises in coding and writing
- Critical reflection tasks embedded within assessment rubrics
The impact (results)
On students:
In my modules, students have responded positively to the opportunity to engage with AI tools as learning partners rather than threats. They report increased confidence in evaluating digital outputs, improved understanding of authorship and ethics, and a clearer sense of how to navigate digital workspaces in future employment contexts.
On colleagues and practice:
I have shared my approach through informal workshops and teaching networks. While adoption is still early-stage, colleagues have expressed interest in adapting these assessment models to their own disciplines, particularly for scaffolded reflective assessment.
On scholarly engagement:
This work has led to a peer-reviewed manuscript and has supported further collaborations around AI literacy and assessment design. I am integrating these insights into future curriculum development.
Lessons learned
This initiative deepened my appreciation for assessment as a dynamic conversation rather than a static measure. Designing assessments for the age of AI is as much about what we value, critical thinking, resilience, ethical judgement, as it is about technology. Next steps include scaling AI‑aware assessment examples into the new curricula, and continuing practitioner research on assessing digital fluency.
Tips for colleagues
- AI requires a shift from product‑centric to process‑centric assessment.
- Collaborative, cross‑disciplinary dialogue accelerates innovation in educational design.
- Pedagogy should foreground learner agency, reflection, and ethical engagement with technology.
Skills and attributes
Students were able to develop the following attributes:
Education for Life Strategy
This case study reflects the following aims of the Education for Life strategy:
- Encounters with the Leading Edge: To put at the heart of our curriculum and learning experiences, encounters with our world leading research and the leading edge of industry and practice.
- Fit for the future: To ensure our students are fit for their future, our teaching is fit for the future of our offer, and our colleagues are fit for the future of HE
Further resources
Perspectives from a workshop: intelligent assessment in the age of artificial intelligence – Advances in Physiology Education
Authors
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Dr Matt Bawn Senior Lecturer, Microbial Genomics School of Natural and Environmental Sciences |