For this month’s AI in FE community meetup, we held an AI Ideas Exchange. Community members were invited to propose topics for discussion before splitting into small groups to talk through the most popular suggestions. At the end of the session, we reconvened to share what we’d learned.
A wide range of topics were suggested, including managing wearable AI devices, AI for team meetings, and how to prepare students for work in a world increasingly shaped by AI.
Four topics emerged as favourites:
- Using AI in assessment without damaging academic integrity
- The conscientious objectors to AI: How to work with students/colleagues who choose not to engage with AI on moral/ethical/environmental grounds
- AI for streamlining workflows for teachers
- AI and environmental sustainability
As this was a discussion session, there is no recording this month, but you can read below for a recap of the key points and the resources shared by the discussion groups.
Using AI in assessment without damaging academic integrity
This group’s discussion reflected a shift in perspective being felt across the sector, with a move away from focusing on AI detection and “catching learners out”, and towards assessment redesign and supporting ethical, transparent use of AI.
There was agreement that preserving academic integrity is not about preventing the use of AI altogether. Instead, the focus should be on ensuring learners can clearly demonstrate their own understanding and that any use of AI is open and transparent.
It was noted that this is not an entirely new challenge. Previous technologies such as grammar and plagiarism checkers, as well as evolving referencing practices, were highlighted as examples of how assessment practices have evolved over time. Viewed in this way, AI might be seen as part of an ongoing evolution rather than something fundamentally separate or exceptional.
The need for clear, consistent guidance from awarding bodies was also raised, particularly guidance that can be effectively cascaded through institutions to support both staff and learners. This is an area that the community has explored in previous workshops and continues to be a focus area for our work.
The conscientious objectors to AI
This group discussed how to approach working constructively with those who choose not to engage with AI on moral, ethical or environmental grounds.
Understanding the reasons behind objections to AI was seen as an essential step, considering the wide range of perspectives involved. Some members shared their success using surveys that revealed staff and student concerns, which could help build a clearer picture of where apprehensions were coming from.
Environmental concerns are one of the key issues for many and this group’s experiences link closely with the sustainability discussion group’s. Suggested responses included raising awareness of environmental impact. Techniques were shared to promote more thoughtful use of generative tools, such as refining prompts to reduce repeated requests and checking for existing resources before generating new content.
Members noted that challenges to AI use can act as a starting point for meaningful dialogue and should be welcomed rather than avoided. The importance of AI literacy was emphasised, particularly as people may not always recognise how widely AI is already embedded in everyday tools, or may be responding specifically to generative AI rather than AI more broadly.
As with the assessment discussion group, concerns around academic integrity were also identified as a driver for objection. Tools such as the AI assessment scale were discussed as a way to address these concerns without defaulting to blanket bans.
There was consensus that learners should not be forced to use AI, and that maintaining choice is important. Similarly, while staff may choose not to use AI themselves, there is a duty to ensure learners have the opportunity to develop an understanding of AI as it is an increasingly important employability skill.
Truly ethical AI use in education was framed as emerging through critical engagement and informed choice, with the broader point made that opting out of direct AI use should not mean opting out of shaping how AI is discussed and applied in education.
AI for streamlining workflows for teachers
This discussion examined how AI can be used to support teaching workflows, with a particular focus on when AI genuinely saves time and when it does not. Members noted that AI can sometimes increase workload when outputs require repeated redrafting due to inconsistent quality.
A range of tools and examples of practice were shared. TeacherMatic was discussed, with a range of uses mentioned from marking and feedback workload, to streamlining the creation of lesson plans, advanced feedback, and schemes of work.
Chalkie AI was highlighted as an emerging tool that some members found particularly effective for lesson and resource creation, while NotebookLM was noted for creating revision and study support materials. There was also interest in exploring creative uses of familiar tools, such as using Canva Sheets to generate certificates from a data set.
Members noted that the effectiveness of AI tools varies significantly depending on the task. One participant shared a useful comparison article: ChatGPT vs Claude vs Gemini: What’s the best AI tool?
The discussion also explored the potential of custom AI agents, and the potential value of developing shared, cross‑college agents for workflow support alongside more nuanced agents for individual staff. One member suggested that upskilling staff to create and use custom agents can be a more sustainable approach than relying on additional paid tools.
The discussion also highlighted ongoing challenges, including concerns around regulation, consistency, accessibility, and ethics. The pace of change was noted as a further challenge, alongside the risk of staff feeling left behind as AI tools continue to evolve.
AI and environmental sustainability
This group focused on environmental sustainability and the tension between climate commitments and the growing adoption of AI technology. Members noted that this can feel like a conflict, with the need to encourage sustainable practices while also adopting AI technologies that are energy‑intensive. As the objections group had also expressed, its being felt that learners in particular are increasingly questioning AI use based on sustainability concerns.
The group felt that clearer and more transparent messaging around AI sustainability could help address these concerns. This includes explaining how institution’s chosen AI tools work, what their environmental impact is, and how this aligns with wider sustainability policies. Offering alternatives, such as non‑generative tools, and explaining why AI is being used in specific contexts could help build trust here.
Sharing information about more energy‑efficient AI models was also suggested and links to LLM comparison tools were shared. It was acknowledged though that data isn’t always available for tools and it can be challenging to determine the environmental impact.
Some felt that considering the energy use of AI relative to other digital technologies was a helpful step in putting the issue into perspective. This could widen the conversation too, encouraging more sustainable choices across digital technologies regardless of whether they use AI.
A range of resources were shared to support the sustainability discussion:
- Link to sustainable prompting tool: Ecosia – AI Chat
- Energy LLMs table: AI Energy Score Leaderboard – a Hugging Face Space by AIEnergyScore
- Alternative to an AI/Google search engines Startpage – Private Search Engine. No Tracking. No Search History.
Next month
A huge thank you to everyone who joined us and contributed to our first AI ideas exchange.
Next month, we are back to our usual presentation and discussion format and will be joined by Clark Mitton from Bradford College. Clark will be sharing a practical look at how freely available AI tools can be used to build bespoke, standalone learning activities from scratch. Honest about the limitations as much as the wins, the session is suitable for those curious about what AI-assisted building actually looks like in practice.
As always, sessions are open to Jisc FE member institutions. Join our AI in FE Jiscmail list to receive invites.
If you would like to present a future AI in FE community session, please get in touch via ai@jisc.ac.uk
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