Dr Claire Hudson continues a series of case studies derived from a BILT Associate Project: Staff Adoption of Generative AI (GenAI) in Teaching, which previously covered GenAI use for teaching activities and assessment design. The ideas presented in this blog are derived from staff interviews and anecdotal experience, and are suitable for staff with very limited GenAI experience.
The Teaching Context
Many of the conversations I had with staff about their use of GenAI in higher education touched on efficiency: reducing admin, generating materials more quickly, or streamlining assessment design. However, one of the most enjoyable uses of GenAI is its role in supporting creativity in teaching.
GenAI can act as a creative partner, helping us to generate ideas, test possibilities, and design playful teaching materials; allowing us to experiment in ways that might usually be outside our comfort zone, or we avoid due to lack of time. Think of it like GenAI lowering your barrier to experimentation.
Drawing on staff interviews and examples from practice, this blog explores how GenAI can help not only to enhance productivity, but to spark our imaginations and create engaging and playful teaching. You may be thinking: “I thought GenAI suppresses creativity”, and there are certainly arguments either way, however as one interviewee noted:
“Generative AI should extend your imagination, not replace it”
GenAI as a brainstorming partner
GenAI is a great partner for generating novel ideas, albeit in-class activities, case-studies, analogies or explanations. In this way, it supports divergent thinking, generating several different possibilities quickly – more quickly than I could! We’ve all experienced the blank-page syndrome, and GenAI can effectively overcome this.
Top tip: ask for variety. For example,
“Generate 10 different unusual or playful ways to teach [insert topic]”.
Top tip: ask for iterations. For example,
“Make this more interactive”, “make this analogy more visual”.
Staff reported that collecting multiple ideas allowed them to pick and choose their favourites, adapt them for different student audiences, or use several ideas within the same teaching session, since students often engage differently with different examples.
Lowering the barrier to playful teaching
Have you ever wanted to include role-play, debates, simulations, narratives, or scenario-based learning; but don’t usually have the time or starting point to design them? GenAI can help bridge this gap by rapidly generating characters, clinical or scientific cases, discussion prompts, or ethical dilemmas.
Storytelling approaches are particularly powerful for making content more memorable and emotionally resonant, and I’ve come across some interesting examples in the literature, for example AI-generated ‘cinematic narratives’ used in clinical case-based learning.
Example 1: Barbie and academic command verbs
One interviewee described using GenAI to support students’ understanding of academic command verbs such as describe and explain, which students often find abstract, particularly in early undergraduate study.
They asked GenAI to generate examples using the film Barbie:
- a “describe” version of the film
- an “explain” version of the film
The outputs made the distinction very clear. The “describe” response focused on observable features such as its bright colours, aesthetic style, and characters; whereas the “explain” response explored how the visual imagery and narrative communicated themes such as gender stereotypes and misogyny.
The educator noted that this was a far more memorable way to communicate the distinction than a written definition, and importantly, it translated quite an abstract assessment skill into something students could immediately recognise and use.
Top tip: create exemplars based on multiple cultural references to enhance inclusivity
“Illustrate the difference between describing and critically evaluating using a well-known film or TV show”.
Example 2: Creating analogies using GenAI
Mirroring the Barbie example, this is a very quick way of helping to explain something to students, in this example, a complex scientific process or laboratory technique.
Example prompt:
“I am teaching [level] students in [discipline].
I want to use an analogy to help students understand a complex laboratory technique.
Please generate a clear, accurate analogy for [insert technique].
Requirements:
- The analogy should map the key scientific concepts onto some familiar
- It should avoid oversimplification that leads to scientific inaccuracies
- Clearly explain the mapping between the analogy and the scientific process
- One main analogy only, not multiple options”
Analogies help students translate complex concepts into familiar contexts, making them easier to understand and importantly, remember. For staff, they provide a fun and flexible way to clarify difficult concepts and identify misconceptions, and GenAI can super-charge this process.
Example 3: A debate-based activity
Another colleague described using GenAI to quickly design a debate activity that encouraged students to evaluate competing ideas, rather than simply learn content.
In this example, the educator asked GenAI to generate a mock “trial” or debate scenario centred on a contemporary public health policy issue, but this could equally be adapted to other disciplines, for example, conflicting disease mechanisms, clinical reasoning and treatment, or contested historical events.
Students were assigned structured roles within the debate, such as:
- “defence” teams arguing one point,
- “prosecution” teams arguing the opposite
- “expert witnesses” presenting evidence from different perspectives.
The GenAI output was adapted to generate:
- structured opening statements for each position
- suggested lines of evidence and reasoning from the different perspectives
- potential counterarguments to support deeper discussion
It also helped compose the student instructions and plan the timeframe for the activity.
The educator noted that this format was effective because it moved students beyond their own opinions, but instead, required them to construct and defend arguments using evidence, while also engaging with opposing viewpoints, much like we’d hope they achieve in a written piece of academic work. Plus, framing the activity as a “trial” introduced a narrative, which made it more engaging and fun while maintaining academic rigour.
The educator reflected that GenAI was especially valuable in rapidly generating the starting arguments for the debate, significantly reducing preparation time. In fact, the idea was first conceived after using a prompt like this:
“Create a 30-minute playful classroom activity for level-6 students on [insert topic] that encourages debate and collaboration.”
Final thoughts
I’ve discussed prompts before, but will re-iterate it here: it is important to give GenAI clear context (e.g. topics, teaching environment, student level), constraints (e.g. duration, formats, mood/tone, interaction type) and pedagogic intent (if students are actively involved).
Top tip: don’t be afraid to ask for more! For example:
- “Add an element of debate to this activity”
- “Turn this into a role-play”
- “Turn this into a game”
Students always tell me that they love in-class activities, and introducing elements of playfulness or creativity is likely to make these more engaging. Used thoughtfully, GenAI may help create more space for these approaches, not by replacing educators, but by helping us explore ideas more quickly and freely and lowering the barriers to trying something new. The value of GenAI is not in a final, perfected output, but how it might encourage us to think ‘outside the box’ about teaching and learning design.
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