Introducting AI as part of the Learning Process

Approach 

At the start of a 3-hour class, I introduced a 30 minute activity designed to encourage students to engage critically with AI as a learning tool, while preparing them for new course content. At the start of the session, students were asked to open their preferred AI platform and, in their own words, ask about two key public health approaches that would be covered in the lecture. They were asked to make notes and discuss AI responses within small groups, comparing similarities, differences, and their confidence in the answers. Students were also asked to save their notes for later comparison, AI versus the lecture. 

A whole-class discussion followed the activity, where groups shared insights. This revealed variation in both AI outputs and students’ ability to understand the answer or have sufficient knowledge to critically interpret them. Some students demonstrated stronger questioning skills, while others expressed uncertainty about whether the AI responses were accurate or sufficiently detailed. This understanding enabled me as a teacher to have an unplanned discussion about how AI written essays often appear impressive but are superficial and don’t seem to relate to learning outcomes. Additionally, I was able to have an unplanned discussion about demonstration and application of knowledge, and critical thought. 

Students then put away their devices, and I delivered the lecture using planned teaching strategies aimed at deepening understanding and encouraging interaction. 

Outcome 

After the lecture, students reflected on how their understanding on the approaches had developed compared to their initial AI-generated responses. Many reported that: 

• The lecture provided greater clarity and depth than they had achieved from questioning AI 

• Students valued the opportunity to ask questions and engage in discussion in the lecture 

• Students said that AI responses, while useful, lacked sufficient detail and contextualisation 

When asked how they would now use AI, students reported they realised that to use AI effectively, they needed to have a good knowledge base from the outset which would help them to refine their questioning.  

Insight 

This activity created a structured and open space for students to begin to actively use AI in a controlled space. Some students said that their experience made them realise that they were focused on the answer rather than the learning. For me as an academic, I saw deeper engagement in class. The activity had also allowed a transparent and meaningful discussion about the limitations of AI. However, I also realised that by positioning AI at the start of the session, students were primed to think about the topic and develop their evaluative skills. 

My advice to any colleague wanting to try this, is to undertake some prior testing of AI responses to ensure confidence that your lecture and seminar lecture actively demonstrate added value. While I can see that for some this approach involves some risk, my experience us that it supported deeper engagement and the results gave me confidence to integrate different AI activities into weekly learning activities. 

Developing Critical Thinking and Questioning Through AI-Supported Learning 

Approach 

At the beginning of a 3-hour class on anthropogenic climate change, I designed a flipped-style activity to build on students’ prior knowledge while encouraging critical engagement with both content and AI-supported learning. 

The level 7 students worked in small groups to create a mind map of what they already knew about anthropogenic climate change, including its impact on health. They were permitted to use AI tools to support this task but were explicitly instructed to fact-check any information gathered. 

Students were asked to discuss their ideas collaboratively and be prepared to explain their understanding to me, as the lecturer. Following this, each group were encouraged to reflect on their discussion and develop a single question they wanted answered in the lecture. 

During the activity, I circulated between groups, observing discussions and supporting students in refining their thinking. I encouraged them to identify gaps in their knowledge and to prioritise what they felt was most important to learn. Students were specifically asked to formulate their final critical question independently of AI. Groups then shared their questions, which I recorded on a whiteboard. I informed the class that most of these questions would be addressed during the session, with any remaining questions carried forward to a later lecture. 

To maintain engagement, I introduced a simple bingo activity: as students recognised their question being answered during the lecture, they called it out and it was ticked off the board. 

Outcome

This approach enabled students to actively engage with the topic from the outset and to reflect on their existing knowledge. It also supported the development of critical questioning skills, as students moved from broad understanding to identifying specific gaps in their learning. The use of the bingo activity added an interactive element, helping sustain attention and encouraging students to listen actively for relevant content.  

Reflection 

This activity helped me as the teacher, to elicit prior knowledge allowing me to tailor the lecture more effectively and avoid unnecessary repetition for this student group. The activity created a structured opportunity for students to engage critically with both AI and subject content. By requiring students to fact-check AI outputs and generate their own questions reinforced the importance of evaluation and independent thinking as a skill needed when working with AI. 

Insight 

Combining AI-supported exploration with structured questioning tasks appears to strengthen critical thinking and deepen engagement. This results in a more responsive, student-centred teaching. Students appear more confident in their own knowledge. 

Using AI to Stress-Test Sustainable Service Improvement Ideas 

Approach

In a level 7 seminar, I designed an extended activity to develop students’ ability to apply service improvement principles to a real-world healthcare challenge, while integrating the pillars of sustainability and critical use of AI. 

Students were presented with an authentic scenario and instructed that as members of a GP practice service improvement team, they were tasked with addressing a real issue, that is low patient attendance for appointments linked to a national screening programme. They were also required to consider sustainability challenges within their proposed solution. 

Working in groups, students used a worksheet to guide their thinking. This scaffolded the process step-by-step, requiring them to: 

• Design an intervention 

• Apply it to the three pillars of sustainability 

• Critically evaluate their proposal against these pillars 

• Draw on relevant evidence to support their approach 

At the final stage, students were asked to stress test their proposed solutions using AI. I had co-developed the prompt with AI in advance to guide this process. The prompt instructed AI to critically challenge the student’s ideas and identify potential weaknesses. Following this, a whole-class discussion explored the activity and how effectively AI had performed in this role. 

Outcome 

Student experiences of using AI were mixed. Some reported that AI did not meaningfully challenge their ideas or add value. Others found it useful in identifying gaps and highlighting areas for further development, in some cases revealing that their proposals were less robust than initially thought. 

Through discussion, it became clear that the effectiveness of AI was closely linked to the level of detail and clarity students provided in their prompts. This led to a broader conversation about how to use AI more effectively. 

The activity also supported deeper engagement with real-world problem-solving, encouraging students to think critically about sustainability and the complexity of implementing service improvements in practice. 

Reflection and Insight 

This task highlighted the importance of prompt quality in determining the usefulness of AI as a critical tool. It also reinforced that AI can support, but not replace, rigorous thinking and evidence-based decision-making. 

Framing the activity around a real-world problem enhanced its relevance and encouraged students to engage more deeply with both the content and the process of evaluation. The AI stress test acted as a useful extension, prompting students to consider perspectives and challenges they may not have initially identified. 

Using AI to co-design a resource 

Background 

In response to student feedback, I sought to develop a structured worksheet that support differentiated learning paces and deeper engagement with complex concepts. Students had expressed a preference for guided activities that allow both rapid progression, checks their understanding of concepts and provides opportunity for a more reflective and slower pace of deep engagement. I have previously found that designing worksheets is time-intensive, often taking up to a full day due to the need for careful planning, clear instruction, and alignment with learning outcomes. I wanted the worksheets to begin with simple, low-risk questions to check understanding before progressing to more applied and critical tasks. 

The worksheets were for part of a seminar session, that follows a lecture about system complexity. I aimed to support students in understanding climate change as a complex or wicked problem, including the challenges for addressing it, and why some leverage points for change, don’t lead to the expected or intended changes. To support the design of the worksheet, I worked iteratively with AI (ChatGPT), providing detailed prompts about: 

• The content to be taught and its theoretical basis 

• The intended learning outcomes 

• The need to scaffold from knowledge-checking to application and critical thinking 

Approach 

Using ChatGPT as a collaborative tool, I co-developed a structured worksheet. This included: 

• Initial true/false questions to check understanding 

• Group discussion prompts to encourage collaborative exploration 

• Higher-level questions focused on systems thinking, paradigms, and the challenges of changing behaviours and perspectives 

This process was iterative rather than immediate, taking around 2.5-3 hours. I refined outputs by repeatedly prompting AI to adjust the balance of activities, strengthen critical thinking elements, and better align with the complexity of the topic. 

Outcome

The final worksheet produced is coherent, provides a scaffolded learning resource that supports students to progress from basic understanding to deeper critical engagement with a challenging threshold concept. I am looking forward to using it in class. 

While the process was not instantaneous, it was significantly more efficient than designing the resource independently. AI supported idea generation, structuring, and refinement, enabling a more streamlined development process. 

Insight 

I can see the value of AI in this context; it helped me to co-produce something that I would not normally have had the time to do. I can also see that it won’t be replacing my role anytime soon. The quality of the final resource remained dependent on my subject expertise, critical input, and iterative refinement.