In April 2026, the Society for Experimental Biology hosted Practical and Inclusive Approaches to using Gen-AI in Higher Education at Nottingham Trent University. The two-day symposium brought together students, educators, and researchers to explore how generative AI is reshaping teaching, learning, assessment, and skills development in higher education.

This post brings together reflections from NTU colleagues and students who attended or contributed to the symposium. Rather than offering a single view of GenAI, the contributions capture a range of perspectives: using GenAI to support interactive learning, redesigning assessment, developing student AI literacy, maintaining critical judgement, and keeping the human element central as these tools become more embedded in higher education.

Anastasios Stavrou:

At the symposium, I talked about how I have been using GenAI to help provide an interactive and playful environment for students learning about biochemical topics. Students often find some aspects of molecular biochemistry difficult, and interactive activities can help them explore these topics in a more engaging way. I have found that more students attend my sessions when I use interactive quizzes.

The challenge is that creating quizzes for each session, and adapting them on the fly to allow for greater exploration of student interest, takes time. Students really value these activities, so I started using GenAI to create draft quiz questions. This allowed me to generate a large bank of possible questions, choose the ones most relevant to the session, and then check their accuracy before using them.

While students were working in a workshop, I was able to talk to them and identify which topics were more challenging. I could then create or select additional practice questions using Microsoft Copilot or Vevox AI, and incorporate those questions into the quiz. This helped students identify where they still had gaps in understanding, and where their understanding was strongest. Students really enjoyed that.

I got a lot out of the symposium, including 10 pages of notes. I thought the roundtable discussion about people’s experiences with GenAI, and the skills required when using AI, particularly critical thinking skills, was really important. I think the greatest challenge and opportunity going forward is how to use GenAI inclusively and proportionately, while keeping the human factor in.

Claire Hawkes:

I presented a short abstract talk at the SEB Symposium to share an effective change I had made to one of my undergraduate module assessments this academic year. I decided to embrace GenAI this year rather than try to outrun or avoid it. I adapted the written assessment to incorporate an activity which required students to use Microsoft Copilot. I provided a brief set of patient clinical details and asked students to use this as a prompt for Copilot to generate a mock diagnostic histopathology report. Students were then asked to critically evaluate the GenAI output, comparing it to an anonymised real-life histopathology report from a patient with the same clinical picture. This gave students experience in using GenAI, while also introducing them to hallucinations inherent to GenAI outputs.

I wanted to share this approach with others in the hope that it might inspire them to try something similar in the current AI climate, or at least to show that embracing the use of GenAI can be a positive way of adapting written assessments.

I learned a lot from the symposium. Of particular interest was an approach shared about using GenAI to generate mock vivas. This aligned well with my module, as the students’ second assessment is a viva. They often feel very nervous about this, yet are reluctant to practise in front of others in our workshop. Using GenAI to ask questions, and to adapt further questions based on initial responses just as academics would do in a real viva, is an incredibly supportive approach which I believe will work well in the coming year.

Michael Loughlin:

I presented examples of where the use or evaluation of AI has been used in assessments in biosciences from a range of colleagues. My purpose was to show how assignments could be adapted to educate students about this new technology, without having to start from scratch or compromise the other expected outcomes for students. Examples ranged from correcting factual scientific mistakes made by Microsoft Copilot when explaining a topic students had experience of, and encouraging students to seek better sources, to the industry-wide practice of using AI to winnow out CV applications, and how students can shape their submissions to avoid this.

This was coupled with the use of a published framework which, while not perfect, at least supports staff in thinking about how to integrate AI into their learning activities. It also allows an external measure through which employers can better understand the skills our graduates leave us with in this fast-moving area of technology.

I will be trying out the idea of a flawed essay, generated by AI, as part of an examination paper, where the task is to correct and improve rather than create from scratch. I can see this as being less intimidating for students, but also a more authentic assessment within the examination hall.

Faiza Ahmad:

Being invited to contribute a student perspective at the SEB GenAI Symposium was a really valuable experience, especially as someone studying in a field already being reshaped by AI tools. One of the most interesting aspects of the day was seeing the level of thought and care being put into redesigning modules and assessments as GenAI becomes increasingly embedded within education and research.

Rather than focusing purely on restricting AI use, many of the discussions explored how assessments could evolve to encourage more critical and reflective engagement with these tools. It was encouraging to see conversations centred around helping students understand how to work alongside GenAI responsibly, rather than simply avoiding it altogether.

I found it especially valuable to reflect on how GenAI has lowered the barrier to entry for coding through what is often referred to as vibe coding, where users can generate functional scripts and workflows through prompting alone. In areas such as bioinformatics and data analysis, this raises important questions about how these subjects should be taught going forward. Alongside technical skills, there may need to be greater emphasis on understanding prompts, interpreting outputs, and recognising unreliable results.

I also appreciated that the symposium made space for discussions around the ethical implications of GenAI, such as those surrounding AI-generated illustrations, as well as the long-term sustainability of learning and skill development. The symposium highlighted how important it will be to balance the opportunities GenAI provides with maintaining the critical thinking, creativity, and scientific understanding that underpin research and higher education.

Rozhin Gharooni Khoshkehbar:

Participating in the SEB GenAI Symposium was a really interesting experience, and I was happy to contribute from a student perspective. It was valuable to see how much thought is going into the way AI can be used in education, not just for students learning complex topics, but also for lecturers designing teaching and assessments.

I especially found it interesting to hear the discussions around using AI responsibly and ethically, as AI will likely become an important part of education in the future. Overall, participating in this symposium and hearing lecturers’ experiences with using AI gave me a broader perspective on the opportunities AI offers, while also showing how important it is to keep critical thinking and human judgement central.

Mohamad Jomaa:

I was pleased to be invited to the SEB Symposium by the event organisers to share a student perspective. As I started my undergraduate degree in 2022, my cohort witnessed the evolution of AI into education, often while lacking clear guidance. My initial approach involved a strict avoidance policy until I gradually started assessing its use and reliability through tailored prompts and by challenging outputs, backed up by my background reading. The symposium allowed me to share my experience and reflect with lecturers who have taught me before, as well as national and international lecturers, and students from younger cohorts.

It was also particularly interesting to explore how AI is being integrated into modules I have taken previously, and to reflect on how I would have perceived similar approaches at the time. This also made me think about what limitations from previous assessment layouts these approaches are overcoming, which generated meaningful discussion with my past lecturers.

I shared my views in the roundtable discussion on how biased prompting can influence AI’s response, especially in molecular biology, where AI can invent signalling pathways to support the user’s approach and knowledge. Overall, it was a great experience to understand how our positionality, in terms of career stage, and intersectionality based on our discipline, can influence how we approach AI and its use in our area of work. It was also very helpful to consider the perspective of an assessor, their concerns about students’ use of AI, and how to maintain a balance where AI remains a supporting tool rather than the leading force in generated work.

Laurel Chaproniere:

For me, one of the most valuable aspects of the symposium was the opportunity to hear staff and student perspectives alongside one another. The discussions reinforced that GenAI is not only an academic integrity issue, but part of a wider conversation about assessment design, digital literacy, inclusion, and the skills students will need beyond university. I was particularly struck by the way several examples positioned GenAI as something students could critique, test, and use transparently, rather than something hidden or prohibited.

This feels especially important in biosciences, where students need to engage with uncertainty, evidence quality, and the limits of any tool that produces a confident answer. What still feels missing is a shared language for what good GenAI use looks like across modules and levels. Students need consistency, but staff also need space to adapt guidance to different disciplines and assessments.

Going forward, I would like us to keep building opportunities for students to practise using GenAI critically, ethically, and reflectively, while also protecting the development of their own scientific reasoning, writing, and voice.

Sarah Rayment:

For me, the symposium was an opportunity to build confidence in using GenAI and hear practical examples of how academics apply it in their contexts. As someone who has only just metaphorically dipped their toe into incorporating GenAI into assessment tasks this academic year, it was reassuring to hear that others have similarly applied it as a tool to develop students’ critical evaluation skills.

As a scholar who specialises in skills development, this, together with discussions of how frameworks focus on competency levels in the use of GenAI, allowed me to reframe a challenging topic into something that feels much more familiar, and that I am confident with. As I reflect on the symposium, one of the things that comes to mind are the words of Oana Birceanu and Christine Bell from Western University, Canada: that it is the human in the loop that drives the process.