We introduce a series of case studies derived from our BILT Associate Project: Staff Adoption of Generative in teaching. This case study is compiled by Dr Claire Hudson, but informed by an interview with a colleague in the Business School.
Teaching context
Discipline: Faculty of Arts and Social Sciences
Level: Undergraduate
Type of course: Newly developed taught unit
Format: Weekly lectures with accompanying seminars
What GenAI was used for?
The educator was planning the curriculum structure for a newly created unit. While the unit scope, description and learning outcomes had already been approved, the week-by-week content and corresponding seminar activities still needed to be developed. The educator used a GenAI chatbot as a planning aid, to structure their ideas and reduce reliance on peer-feedback.
How was GenAI used?
The educator input the unit description and learning outcomes into ChatGPT and asked it to propose a week-by-week content structure. Although the output was described as “somewhat regurgitation of the input”, it helped validate and structure the educator’s own thinking. Ongoing iterations of the plan helped hone their ideas further. The educator also used GenAI to brainstorm possible seminar activities aligned with each week’s topic. The tool was particularly helpful at:
- Generating valid learning activities.
- Considering appropriate timescales for the activities, taking into account seminar length and student attention spans.
- Serving as a “sounding board” without needing to consult colleagues.
What were the perceived benefits?
Key benefits included:
- Speed of planning phase and conceiving a valid structure.
- Reduced reliance on colleagues for initial feedback
- Confidence boost through validation of existing ideas
This educator stated that:
“I think using it as a sounding board, as a structuring tool, makes you more efficient. Otherwise, I would have been going round and round, you know, drafts and so forth and agonising over it, it’s effectively having somebody to talk it through with.”
“And it was almost validating, acting like a good assistant who would say, why don’t we try this? What do you think? And then you tweak it a bit so that it is quite a healthy activity.”
“it’s made it easier to structure and refine ideas. I don’t think we’d have had any more active learning, but it’s enabled a bit of focus; one of the struggles with active learning is putting too many things in a session.”
Challenges and limitations
- Output was only as good as the input provided.
- The AI-generated content somewhat lacked originality.
- Required human judgment to refine, adapt, and ensure relevance to students and learning outcomes.
“I don’t think it came up with any profound activity that I’ve never thought of before. It used my initial ideas but structured them.”
Outcomes and impact
- Teaching sessions were well-received, with students engaging actively and responding well to activities.
- The approach has encouraged continued use of GenAI as a planning support tool — not to replace pedagogic thinking, but to enhance and streamline it.
“I got good feedback from students. I did quick Menti polls at the end of lectures, so I was able to see not only how they were acting in class, but also gauge formally if it was working and yes, it’s been highly effective.”
Example prompts
I have derived a suggested starting prompt: You are an experienced academic in [discipline]. Given the following unit description and learning outcomes, propose a week-by-week structure for a 12-week undergraduate course. Leave week 6 and week 12 free for consolidation and assessment preparation, respectively. There should be 30 hours of structured teaching over the 10 teaching weeks, mostly in-person lectures with some flipped-classroom style asynchronous content, and at least 2 hours of interactive seminars per week. Organise the topics into a logical order, and provide details of the content and length for each teaching session. *Insert unit details here*.
Additional prompt ideas:
- “Suggest seminar activities for each week’s topics that promote critical thinking and active learning.”
- “Generate time-appropriate learning tasks for a 60-minute seminar focused on [topic].”
- “Based on this weekly structure, how can I scaffold student skills development in [insert skills] across the teaching block?”
Tips for other educators
- Use GenAI as a starting point, not a finished product — think of it as a collaborative planning partner or an assistant who generates a first draft for you.
- Don’t hesitate to ask GenAI to rework or restructure its suggestions, it’s a two-way conversation.
- Use your professional judgment to refine its outputs and check alignment with learning outcomes.
- Try using GenAI to quickly generate several versions of seminar activity ideas — pick and combine the best ones.
Final reflections
This case highlights how GenAI can play a valuable role in early-stage curriculum planning and development of in-class activities. While the output may sometimes lack originality, the tools can help educators clarify their thinking, iterate quickly, and feel supported; especially when developing new teaching. Used critically and reflexively, GenAI doesn’t replace human input, but becomes a more practical, low-stakes collaborator. Personally, I have used GenAI very successfully for generating active learning tasks for students, and was impressed by its ideas; this stance may depend on your own levels of creativity, perhaps mine are low!
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