Featuring contributions from:
- Mia Stevens, Undergraduate Education Officer, Bristol SU
- Toby Reynolds, Senior Placements Administrator, Engineering Faculty Office
- Esther Ng, BILT Student Fellow, BSc Biomedical Sciences
- Catriona Johnson, EAP Subject Lead, Centre for Academic Language and Development
It has been great to hear insights and reflections from different people within the UoB community in response to the scenarios which Myles, Anya and Darren experienced.
In trying to bring these thoughts together, some key themes are apparent from the collective insights of our blog contributors.
Anya and Miles – students adapting to changes in their approaches to study?
Here’s what Esther Ng reflected on the scenario:
“In my opinion, Myles’ reflection on the situation suggests a somewhat negative perception of AI-assisted learning, whereas Anya may have developed valuable skills through her study approach, such as enhanced critical thinking. Myles’ concern about becoming her “safety net” seems somewhat dismissive of her independent learning process, as it assumes that her use of AI diminishes the depth of her understanding. However, I do understand their viewpoint on fairness, particularly given the significant amount of time and effort they have invested in learning the module material. It’s important to recognise that different students have different study techniques, and efficiency doesn’t equal a lack of understanding. With the increasing demands of a third-year workload (especially in a Science degree), students often must balance multiple responsibilities, making it much more important to find tools and develop skills to help them get through this. Rather than viewing using AI as a shortcut, it should be seen as a positive thing! It’s an adaptive approach that complements traditional reading while also fostering meaningful learning as complex concepts are broken down.”
Mia Stevens share her thoughts that:
‘In a situation such as this, it is important for each student to pursue the method which empowers them to get the most out of their learning. For Myles, this looks like following a more traditional, established method – using library resources, reading over course materials, making notes. For Anya, this involves using AI to focus her understanding in a more streamlined way. The “risk” of Anya’s method is perhaps that it is a lesser-known mode of learning – we don’t know as much about AI-guided learning as we do about the processes of reading material and summarising in the form of notes. However, just because a method is lesser known it does not mean that it should be rejected as a useful mode of learning – we are an innovative university and so the possibilities that AI opens should be explored with openness and curiosity. That being said, I think that the most exciting thing about studying is the “accidental” knowledge you encounter – the ideas, concepts, examples you stumble upon when reading more broadly around your area of research. From my point of view, using AI to streamline your searches perhaps loses this sense of possibility, of expansiveness. By using AI to summarise course material, Anya runs the risk of excluding all the valuable information that Myles has access to through a more comprehensive method of reading and understanding all the course material. Whilst Anya’s study time is more time-efficient, Myles’ is richer, deeper – it offers more opportunity for intellectual curiosity. Of course, with students often needing to work extra hours of employment to support their study, it is becoming increasingly harder to manage time and workload – this is where AI can be seen as a real benefit in focussing tasks. However, when looking at this from the perspective of a rich and expansive educational experience, I think it’s important to give oneself as many opportunities to learn as possible. AI literacy is a skill which is becoming increasingly valuable to employers — and so should be explored and developed — but maintaining those important skills in creativity, critical thinking and curiosity must always be placed at the forefront of our academic experience.
Next to share her insights on this scenario is Catriona Johnson:
‘My first thought is that it would be a huge shame if Anya and Myles stopped working together on assessments, as helping each other generate ideas and understand key concepts is such a valuable part of the learning process. I’d encourage them to talk openly about their feelings regarding Gen-AI so that they can understand each other’s viewpoints more clearly, rather than letting it drive a wedge between them. Anya needs to appreciate Myles’ reluctance to embrace this technology, which could be due to ethical or sustainability concerns. In turn, Myles could have a more open mind about how Gen-AI can help time-poor students to study more efficiently and cope with external pressures. Hopefully, through conversations like this, the two friends can find a slightly new way of collaborating and possibly learn some study strategies from each other.
It would be interesting to hear more from Anya about how she uses Gen-AI to prepare for assessments, which LLMs she is using and for which purposes. How does she view its role in her learning? Does she simply see it as a more sophisticated version of Google or as a personal tutor with whom she can engage in dialogue and receive feedback from? If the latter, then it might be worth pointing out to her that her AI use is starting to substitute person-to-person interaction, which could have a negative effect on her interpersonal skills as well as her friendships.
It would also be interesting to hear how Anya is using Gen-AI to summarise information, and whether she is reading the documents first so that she’s able to evaluate the output. I can see how asking AI to create written summaries or podcasts of long articles can help students to revise the main ideas, but only if they’ve read the texts and can check the content. A group of students told me recently that they often compare summaries of the same text by different LLMs, such as ChatGPT and Deep Seek, to see which is the most accurate. They also discuss how to combine LLMs to get the best results, e.g. Claude for initial document analysis followed by ChatGPT for a summary of the structure. Therefore, perhaps in some contexts, the nature of student collaboration has shifted, so that in place of more traditional ‘bouncing ideas off each other’, students are now critically evaluating the outputs from different LLMs. These kinds of conversations could arguably help to develop their AI literacy skills which might be useful for their future careers.’
Toby Reynolds has reflected that:
‘It’s interesting that Anya feels like she doesn’t have the luxury of doing things in an ‘extra’ way (whatever that is), which is probably due to other life pressures as well as course demands. That said, the overuse / misuse of AI can lead to knowledge deficits and the danger of surface knowledge, without the backup of deeper knowledge and appreciation of the context of her course material.
With regards to Myles, there is evidence that (dependent on learning style) reading and writing notes in the traditional way can lead to greater and deeper retention of knowledge, and a greater appreciation of the course content and context. As far as being Anya’s safety net, this isn’t just one way; maybe Anya would act as his…..?
It would be an idea for Anya and Myles to come together and share their different approaches, despite the impact of AI, as there would be much to learn from each other. Both students may well have missed things, and from a social and friendship aspect, it’s very nourishing to share knowledge and revision notes.”
Darren – a lecturer feeling tension between the ‘what’ and ‘how’ of teaching
Some reflections on Darren’s experiences come from Toby Reynolds:
‘Darren’s situation is very understandable and very common. There has to be a balance struck between the ‘what’ and the ‘how’ as student learning needs both to be in place to be effective. It’s very easy to get caught up in a hamster wheel of endlessly trying out new teaching techniques, and neglecting tried and tested methods that work well. If I had to make a choice between the ‘what’ and the ‘how’, I would have to choose the ‘what’.’
Here are the reflections of Catriona Johnson:
‘I’d reassure Darren that many lecturers experience the same ongoing tension between the what and how of teaching, as choosing the most suitable approach or activity for specific subject matter is a complex process, which involves a lot of trial and error and constant reflection. A process which has been further complicated by the rise of technology and the vast number of digital tools that can be used by educators. To help Darren plan his lectures and choose the right approaches and tools for his subject, I’d recommend using the TPACK framework (see Figure 1) which explores the connections between pedagogy, content and technology, so that digital tools can be integrated effectively to support and enhance the students’ learning.
The effort he’s putting into the planning of his lectures is clearly paying off, but he needs to be mindful of burn out. To avoid ‘pouring from an empty cup’, Darren could reduce the pressure on himself by striking a healthier balance between trying out new teaching approaches / tech tools and recycling old ones, e.g., he could create a bank of templates, such as Menti polls or Padlet activities, that can be quickly adapted and easily shared with colleagues to reduce the preparation load. These simple tools can make a lecture instantly more interactive without too much work. To help strike the right balance, I often remind myself that the impact on the students should generally be greater than the preparation time: effort < effect.’
Figure 1: The technological pedagogical content knowledge framework (Mishra and Koehler, 2006)
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Once again, many thanks to our contributors for sharing their reflections on these scenarios. Please feel free to comment below if you have anything to add to these reflections based on your own experiences.
For more information about the series as a whole, you can find out more here.
If you have been inspired to contribute to the next scenarios blog, more details can be found here. Otherwise, we look forward to seeing you in the next edition of ‘Picture This’.
References:
Mishra, P. and Koehler, M.J., 2006. Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers college record, 108(6), pp.1017-1054.
