The impact of AI was the standout theme for Day 1 of the Advance HE T&L conference. Sarah Jones (Pro-VC Education at Solent University) gave an outstanding keynote address, putting AI in the bigger context of challenges in the sector. Jones stressed the importance of not just getting students using AI, but building AI literacy skills into the curriculum. That’s something we need to think about in the history department, where we pride ourselves on encouraging students to ask rigorous and critical questions of all sources. AI literacy is just one part of the ‘Skills 4.0’ challenge which explores the sheer diversity of transferrable skills that students can and should be developing for the future. The ‘Skills 4.0’ framework, first developed in and for Scotland, is worth a look here: https://www.skillsdevelopmentscotland.co.uk/what-we-do/skills-planning/skills40.  

Jones finished her session by challenging us to think about three possible future structures for the university in the face of financial challenges: 1) the ‘super-university’ bringing together clusters of institutions in shared governance (perhaps UoM might be something of a model for this!); 2) a re-separation of research and vocational institutions; 3) smaller ‘co-operative’ universities building in student power and institutionalising the student voice.  

Continuing the theme, I next attended Danai Christopoulou and Etieno Enang’s session on academics’ own attitudes to AI. Christopoulou and Enang presented their preliminary findings on a research project among academics at the University of Liverpool. I was struck by the positive views of their informants towards AI irrespective of age, though as they admitted, this may be conditioned by a sample drawn only from the Business School.  

The two researchers then threw open the debate to those in the room, where views were much more varied, from those at the cutting edge of AI in assessment, to those much more sceptical about AI use for academics. The only agreement in the room was the importance of individual academics and programmes retaining control and autonomy over the nature of AI adoption. The big idea I came away with was the possibility of using AI to answer straightforward student questions on large modules: When’s the deadline? What’s the word count? How’s it graded? How many sources do I need to read? But you’d have to very carefully set it up to check it was delivering the right answers. The idea that made me shudder was using AI to help write student references, although I suppose most of us already use our own templates, so perhaps my horror is misplaced!  

AI for assessment is at the forefront of everyone’s minds, so I also attended a session on making ‘AI-resilient’ assessments. Lorraine Smith from the University of Sussex led us through an example from biochemistry, where students had to work together to pose a diagnostic challenge to another group. We got to have a go at the task in small groups, and it was good to see how the task of setting a challenge for another team got us thinking creatively. I don’t think I could adapt that for my own assessment, but I like the idea of posing questions between groups on an informal basis in the classroom (in our three-hour L3 seminars with plenty of time for group work).  

Richard Remedios ran a workshop asking the big question: ‘Did my intervention work?’ – in other words, when we make a change in our teaching, how can we be confident that it made a difference? The workshop offered solutions for this at various levels, from the teacher simply wanting to run their module better, to someone looking to publish their pedagogical research. The key takeaway was the importance of having a baseline starting point before the module: either a student survey or clear data from previous years. The advantages of start-of-term and mid-term student surveys shone through Remedios’ own case study from psychology. It is well worth a look at how he can prove that his intervention can reduce anxiety (under ‘Test Anxiety Group’ on this page: https://www.ntu.ac.uk/research/groups-and-centres/groups/education,-motivation-and-learning-research-group).  

The final panel of the day was an interesting grab-bag of problems that we face:  

1) What is the point of extenuating circumstances and extensions, and do they do what they’re supposed to be doing? – a presentation that raised more questions than answers!  

2) How can we better help students bridge the gap from FE to HE institutions, and what is the place of foundation years in institutions?  

3) How can we encourage students to live with uncertainty in the classroom? – to realise that they might sometimes have to hold together multiple answers. The warning here was that pushing uncertainty can lead to lower teaching evaluations in L1 modules, but we are promised rewards by the end of students’ programmes, and students are better prepared for the complexities of the workplace. 

It was a real pleasure to attend the Advance HE conference and get a sense of the cutting-edge questions people are asking. There was a great combination of research-driven papers (most of which are not yet published) and practitioner-focused workshops. I came away full of ideas for things to work on in my own individual and team teaching.  

Mark Baker
Lecturer in East Asian History
Department of History
University of Manchester

https://research.manchester.ac.uk/en/persons/mark-baker-2

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