The Second Maximising AI in Learning and Education Conference – Write up by Dr David Perrin

Report by Dr David Perrin, Co-Director and Chair of Senate, IoPD

Introduction

This was our second Institute of Professional Development AI conference, this time held at the University of Chester in Warrington, building on the success of last year’s AI conference in London. It was fully sold out with delegates from business and the public sector across the UK.

Conference Key Themes

• Exploring the evolution of AI in education and its transformative role in reshaping the learning landscape

• Gaining insights into the applications of AI in learning and development across different sectors

• Evaluating future trends and predictions for how AI will influence workforce development and career readiness

• Understanding the implications of AI-driven educational tools on teaching practices and learning outcomes.

Conference Sessions:

Session 1 – Keynote Address: Is AI the Future of Learning?

Dr Alex Fenton, Associate Dean for International for the Faculty of Science, Business and Enterprise, and Associate Professor in Digital Transformation, University of Chester

· On balance delegates – through a Mentimeter poll – reported feeling broadly confident about their AI abilities, though with some gaps.

· Dr Fenton traced the origins of AI, including back to Alan Turing in the 1950s and then machine learning in the 1980s. Deep Blue beating Kasparov at chess in the 90s, was a turning point in perceptions. The more recent development of generative AI a bigger turning point still.

· A big question is about the extent to which education providers are ‘in control’ of AI and its uses, especially by students. Funding issues also, so HE and FE struggling to navigate this.

· Opportunities include marking & assessment, virtual reality situations such as interviews and simulations.

· Dr Fenton outlined some predictions about AI developments including changing job roles, plus changing learner attitudes and autonomy.

Session 2: Ethical Considerations in AI Education: Ensuring Responsible Usage

Dr Katharine Welsh, SFHEA, Associate Professor of Academic Innovation, University of Chester

· Mentimeter issues fed back by delegates – ethical context in AI: ‘confusing, scary, challenging’, privacy, ownership, ‘morally ambiguous’ aspect. Delegates felt less confident about ethical aspects than the technical uses of AI.

· Session looked at the nature of ethical challenges, including privacy, data protection, costs, EDI issues, access, etc. Sustainability and energy usage also an issue as is the potential devaluation of labour.

· Developing GenAI literacy is key, as informed by the Digital Education Council framework: https://www.digitaleducationcouncil.com/post/digital-education-council-ai-literacy-framework

· Session looked at a case study of how the Univ of Chester handles some of these issues currently where it is able to, including with staff and students. End Menti registered some improvement in understanding of challenges.

Session 3: How to Manage the Uncanny Guest: Generative AI and a Robust Ethics of Engagement

Professor David Webster, Director of Education, Quality & Enhancement, University of Liverpool

· Many consider the advent of generative AI as little short of an ethical catastrophe. Academically, the essay has been the mainstay of most HE & FE assessment, but this above all else is being challenged by AI.

· Equity an issue – AI challenging meritocracy, can AI enable students to buy their way to success more effectively? The best AI will most likely soon cost!

· Many AI tools fail to meet thresholds, ie in terms of ‘not making stuff up’. So reliability also an issue.

· A positive has been the ways it has impelled academics to develop innovative assessments, including process – based rather than largely focusing on end product. Talking to students about ‘what they are doing, how they are doing it and why’ is important.

· Core principles – transparency, accountability, equity and sustainability. Discussions around AI should be an intrinsic part of the student experience, not a ‘bolt-on’.

Questions and Answers Panel

· Lots of student fear about using AI ‘in the wrong way’. Efficiencies are developing exponentially.

· Some students have strong views about AI – many academics have now incorporated it into assessment explicitly but some students have then refused to engage with it on ethical grounds.

· Dichotomy between the needs of tech companies and education eg they are more interested in making users happy than producing something that is ‘truthful’.

Session 4: The Role of AI in Driving Content Creation and Personalised Learning

Professor Ian Turner, Professor in Learning and Teaching in Higher Education, University of Derby

· Case study of a Level 6 module for science students at Derby, with use of Copilot. Common practices were discussed with illustrations – rubrics, transcripts, subtitles and captions for videos, proof-reading.

· Also an illustration of how generative AI could create a game for students that was learning-focused. In addition, lecture summaries sent as an email.

· Another detailed case study involved the creation of an imaginary town and the people in it and how this could be used in various ways for prompting student learning, decision-making and authentic assessment.

Session 5: AI and Assessment

Dr Suvodeep Mazumdar, Senior Lecturer in Data Analytics, University of Sheffield

· Understanding of AI initially tends to come through personal use of tools like Chat GPT and Copilot. It has necessitated a re-evaluation of assessment practice.

· It is possible to identify an ‘acceptance cycle’ for AI. Confusion, followed by repudiation, shaming, acceptance and forgetting.

· Tests have now been done identifying scenarios in which generative AI outperforms the average student.

· There are different approaches and settings for how AI can be used in assessment. Students can use it, staff can use it, it can exist as an assessment tool in its own right (including where AI can detect where AI has been used in an assignment …). It can also be used in admin processes.

· Two examples were used for illustration – one for formative assessment, another for summative.

· Finally, key challenges and risks were identified for both staff and students.

Session 6: Empowering Educators to Lead AI Innovation in Assessment at the University of Chester

Professor Jackie Potter, Dean of Academic Innovation, University of Chester

· Majority of delegate audience from a HE environment, with a minority from FE and other sectors.

· Chester used as a case study for how all assessment was evaluated by staff in relation to AI and its use. A human-centred approach in which it was openly assumed that no-one was a real expert, let alone in possession of near perfect knowledge.

· This involved working groups, sharing spaces, and peer review leading to authentic and continuous assessment (not just end assessment).

· Outlined ‘The Seven Steps To Success’ for Generative AI and assessment.

Questions and Answers Panel

· Academic conduct/integrity massively impacted by AI and most institutions have explicit policies on its use, but these will need to evolve as AI itself and its use evolves.

· Can AI can especially help neurodiverse students?

· New AI LLM models are now appearing that are free and are arguably at least as good as Chat GPT, so this may impact on the previously highlighted ‘equity’ issue.

Session 7: Action Planning: Putting Theory into Practice through LEGO® SERIOUS PLAY®

Karen Cregan, Senior Lecturer in Professional Education, University of Chester, and Maud Duthie, Programme Manager, University of Chester

Questions posed to delegates …

What are the 3 most pressing issues for educational use of AI?

· Barriers, boundaries came up repeatedly. Fear also, the digital divide and sustainability. Also notion that big tech is a ‘shark’ and we are all in shark-infested waters. Privacy also raised as another issue.

How can these be overcome?

· Expect the unexpected. Collaborative approaches to problem-solving and innovation, involving bridging. Bringing together territories and perspectives.

· The AI Guide for Teachers from UNESCO was highlighted: https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research

· Challenges for business and the professional development and business link – will AI undermine human creativity and criticality?

Conference summary

There were also excellent opportunities for lively discussion and debate at the panel sessions, where delegates engaged fully with the speakers. Final conclusions from the conference were as follows:

Metaphors and object used were illustrative – vehicles and crash helmets! Lots of discussion about top-down or bottom-up but we have no choice but to engage constructively with what is there and how we can best respond, and then develop effective approaches.

Insights into assessment seemed especially important – with scaffolded, process-driven assessment needed more than a traditional reliance on end assessment that is one-dimensional.