Our November HE Community meetup followed a lean-coffee format, with participants voting on the topics they most wanted to explore. Four themes stood out, reflecting ongoing sector-wide questions about staff confidence, assessment design and student engagement with AI.
Supporting staff to build confidence in students’ use of AI
Staff confidence topped the vote, showing a shared concern about how ready colleagues feel to support students with AI. Participants noted that when AI is not discussed openly, many students avoid using it altogether, even when it is referenced in assignment briefs. This leads to inconsistent expectations and missed opportunities to build the skills they need.
Several factors contributed to this challenge, including variation in staff engagement, limited staff-facing guidance, and colleagues waiting for clearer institutional direction. Participants also emphasised the wide differences in student AI literacy — particularly among mature students, returners and those transitioning from FE — which further shapes the support staff feel able to provide.
In response, some institutions are developing communities of practice, informal sharing spaces and cross-department collaboration to surface pockets of good practice and help colleagues build confidence.
Rethinking assessment
Assessment design remained a prominent theme, with participants raising concerns about the continued viability of traditional written assessments. A range of approaches were shared to maintain authenticity and ensure students can demonstrate their own learning. These included:
- Process-focused assessments, such as reflective logs
- Interactive or oral components, from structured vivas to role-play assessments
- Considerations of scalability, particularly for large cohorts
- Mixed-mode approaches, including interviews designed to verify understanding of submitted work
Participants also highlighted practical tensions around redesigning assessments within validation timelines and varying institutional policies. The group discussed whether offering students a choice of assessment mode supports autonomy or instead encourages the selection of formats perceived as more vulnerable to AI misuse. Others questioned how realistic it is to avoid AI entirely as tools and devices become increasingly embedded in everyday study practices.
These discussions illustrated the active experimentation underway across institutions as colleagues explore where AI creates pressure — and where it opens opportunities — to rethink assessment design.
AI and academic writing
The use of AI in academic writing was another topic of interest, with participants asking how different institutions are approaching it and whether expectations vary across programmes. It was noted in the discussion that many courses are still working within existing assessment formats, meaning that staff often rely on direct conversations with learners to clarify what counts as acceptable use of AI in written work. This highlighted the need for clear expectations as institutions continue to refine their guidance.
Anti-AI stances among students
Finally, the discussion turned to students who actively choose not to use AI. Participants shared examples of students who choose not to use AI for reasons including copyright concerns, intellectual property or sustainability, alongside others who engage confidently with multiple tools. These differing stances raise questions about how institutions can support students fairly while acknowledging that AI is increasingly embedded in study and workplace practices.
The conversation also connected to wider issues of digital inequality. Some students have strong AI skills and access to premium tools, while others lack confidence or prefer not to engage at all. Participants noted that such variation has implications for equity, expectations and the support required to help all learners navigate AI-enabled environments.
Closing thoughts
This month’s discussion highlighted that AI in HE is perhaps as much a cultural shift as a technical one. Conversations around staff confidence, assessment, academic writing and student attitudes point to a shared need for clarity, consistency and equitable support as AI becomes embedded across the learning experience.
We look forward to continuing the conversation at our next meetup on Tuesday 16th December.
Links shared in the chat
Plato – Plato
Educational Development Unit at Imperial College London – Imperial Educational Development Unit
Jisc – Jisc – Learner resources on generative AI for Further Education
Gettysburg College – Teaching & Learning in the Age of genAI
Assessment & Evaluation in Higher Education – Talk is cheap: why structural assessment changes are needed for a time of GenAI
University of Sydney – Program level assessment design and the two-lane approach
Jisc – Assessment ideas for an AI enabled world
Imperial College London – How Imperial is dealing with the rise in students using AI
Medical Schools Council – Medical Schools to prepare students with AI and data sciences skills
Harvard Business School US Competitiveness Project – Navigating the Jagged Technological Frontier
Imperial College London – Department of Electrical and Electronic Engineering – Plagiarism
World Economic Forum – The Future of Jobs Report 2025
Digital Education Council – AI Literacy Framework
Centre for Higher Education Transformations – REF-AI project
Aston University and University of Leeds – Aston University and the University of Leeds jointly win £3.4m for artificial intelligence tools researcher development network
Find out more by visiting our Artificial Intelligence page to explore publications and resources, learn more about our communities and sign up for our AI Literacy training.
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Get in touch with the team directly at AI@jisc.ac.uk