Dr Alison Oldfield is a Senior Lecturer in Education and Digital Technologies, Rosey Crow is the Subject Librarian for Education, Policy Studies and Exercise and Dr Robert Sharples is a Senior Lecturer in Language and Education.
Lately, it seems nearly nigh on impossible to turn any corner in higher education and not run into some guise of AI. And from our teaching experience and conversations with students, it seems that many of them are feeling the same way. This has also been backed up by recent BILT-funded research involving a student survey and focus groups, in which students said they harbour many concerns and questions about AI – and unsurprisingly near the top of the list is how (or if) they should use it in their studies.
In the School of Education this year, we have tried to help students tackle those questions by starting a conversation with them early on. As colleagues from teaching, academic integrity and library strands of the school, we developed and ran timetabled workshops that were offered to every student early in the autumn term last year. Around 275 students took part – from first-year undergraduates to doctoral level. The workshop broadly aimed to develop students’ understanding and critical examination of AI technologies within their studies.
Importantly, while the session included guidance related to academic integrity and use of AI in assessment, it didn’t stop there. We also broadly examined what AI is, discussed the necessity of criticality for AI, and asked student to reflect on how potential use of AI fit with their own personal aspirations and study goals – all vital parts of supporting students to make informed decisions about if or how to engage with AI in their studies.
We also did not focus on functionality – that is, how to use AI well or ‘effectively.’ Rather, we discussed more broadly how it might support some aspects of study life and also where it could bypass learning objectives or get in the way of learning. One of the activities in particular looked at scenarios of AI use in different university settings, showing some uses that clearly contravene UoB guidance and others that are more ambiguous in relation to rules but have impacts on broader learning outcomes. Such ‘grey areas’ generated substantial debate and demonstrated the ambiguity and uncertainty involved.
At the end of the session, students told us they had learned a range of things, including ‘how to use AI appropriately,’ ‘the use of AI is quite ambiguous,’ ‘important to consider whether the use of AI enhances learning outcomes or not,’ ‘creating your own piece is more important than making a perfect copy generated by AI’ and ‘to doubt’!
Though specific expectations and uses of AI may differ across disciplines, schools and faculties, we are sharing below the outline of the workshop in case it’s helpful for other schools or faculties aiming to support students in similar ways. Some of the activities were developed in our research earlier this year – related links to the activity guides and information are below:
Workshop plan (90 minutes):
- Introduction to the workshop aims and content, including Mentimeter questions asking students how they use AI and what they would like to get out of the workshop
- Brief introduction to AI (challenges of defining AI; that it has different purposes and tools (including and beyond genAI); broadly how it works)
- University policy and guidance around AI, including categories of use and questions of academic integrity
- Activity: Scenarios of appropriate AI use at university
- Activity: Critically examining AI outputs – the CRAAP framework
- Reflection and questions
While the sessions with students opened the conversation about the complexities of learning with AI, it certainly isn’t the only one we need to have. We aim to hold ongoing discussions in each unit in the school and also intend to host another all-student workshop on other identified areas of staff and student concern and scepticism, including equitable access and use of AI, copyright, privacy, environmental (water, energy, minerals) requirements, and bias. As we further develop this in the School of Education, we certainly welcome conversations with colleagues who are also interested and participating in similar work across the university!
Image attribution: Deborah Lupton / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/
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