What this research is about
Generative AI has become widely accessible, yet there’s a gap between how young people use these technologies and the ways in which the structure of guidance, rules and management of these tools are designed.
Young people’s digital lives move fluidly between home and school, between different apps and tools, between different expectations and rules. This research aims to capture and learn from that fluidity.
What is a sociomaterial lens?
We are starting from the point that technology use isn’t just about individuals making choices. Instead, people, policies, devices, technologies, spaces, relationships, societal norms, and other factors are all part of a wider network (or entanglement) that shape, and are shaped by, everything else in that network.
Think of it this way: when a young person uses AI to help with homework, they’re not just interacting with technology. They’re also impacting and interacting with school policies about AI use, their parents’ and teachers’ expectations, their friends’ experiences, the design and functionality of the AI tool itself, where they’re physically located, what device they have access to, and countless other factors that all influence what happens.
How we’re doing the research
This research will use a few different research methods over four school terms and the holidays in between them. These methods – detailed in the dropdowns below – will engage with a cohort of young people, their schools and families. In almost all the research activities, the young people involved will act as co-researchers – that is to say, they will be instrumental in ensuring the proposed research methods make sense, gathering data, analysing that data and coming up with recommendations. They will also be involved (should they want to be) in any dissemination of recommendations to groups outside of their school/home network, and be named co-authors on any academic or other literature that is published as a result of their hard work.
The research will work in phases, using the same research methods to explore a different theme as time progresses:
Phase 1 (summer term 2026): getting to know each other – what does AI use look like in school?
Phase 2 (summer holidays 2026): what does AI use look like outside of school?
Phase 3 (winter term 2026): what are the rules and requirements about AI use in and out of school?
Phase 4 (spring term 2027): what does AI help with and make worse (or harm)? What needs to happen in the future?
In school research
Technology Observation and Interviews
We’ll spend time in schools observing how generative AI appears (or doesn’t) in everyday classroom life. We will ask students and teachers to report back periodically on what different approaches to technology use means for their experience of learning and teaching.. We’ll also talk with people in school about their experiences and perspectives on generative AI.
Walkthroughs
Different groups (students, teachers, school staff) will guide us through the spaces in their school where generative AI (or other technologies) figure – or don’t. Different groups of participants might have very different ideas and experiences of what it is to engage with AI in schools!
Technology interviews/engagement
Young people will have the opportunity to interview those pieces of generative AI technology that they consider impactful in their lives.
How do you interview a piece of software? Adams and Thompson, two posthumanist researchers who work with digital technologies, have eight “heuristics” that you can explore with any piece of technology. We will work with the young people to apply some of these concepts to the technology of their choice. Some of the heuristics:
- What does the technology allow you to do – or not do? (What would happen, for instance, if you removed the delete key from your keyboard?)
- What does it invite you to do? (How does using a PowerPoint slide deck change to teach a lesson change the shape of information presented?)
- What do you need to know in order to use it in the way you need it to? (How effective is Excel if you don’t have a thorough grasp of how to create a formula to do the calculations you need?)
We may also be able to run some experiments to see how well generative AI does certain tasks compared to the youngp eople themselves. Can it write touching poetry? Can it do maths? Can it plan revision schedules? This can help explore the limits or practical application of generative AI use.
Outside of school research
Photovoice
Using the photovoice method as a guide, young people will document their own AI experiences and use the outputs to reflect on what the impact of AI is in their own lives, and within their community. Photovoice puts young people in the researcher role, presenting an exciting experience to help explore what it is to perform academic research (and maybe even publish and communicate the findings publicly).
The photovoice process will be outside of the school context: home or anywhere else that triggers thoughts of generative AI. The experiences can be documented through photos, voice notes, written text, drawings, screenshots, videos – any medium that captures what the young person wants to show. All the young people will then bring together what they’ve documented to discuss what they’ve learned – and, based on the photovoice goal of community action – what changes they might want to advocate for as a result.
Co-creation workshops
After the end of the four school terms, all the findings will feed into a series of co-creation workshops to create resources based on what we’ve learned. Depending on the findings, these resources will help support the community to understand, use and set boundaries or guidelines around generative AI use.
These workshops will be young person focused, with an emphasis on using the outcomes of the photovoice research. However, you can’t create resources for the community without the community – so we want all the people who have been involved in the project to take part to make something that really reflects what’s needed!
Why the research matters
Young people are at the forefront of adopting new technologies, yet they often navigate these tools with limited guidance. In fact, any guidance may often be contradictory based upon the setting they use them in.
When it comes to generative AI, seeing stories in the news around the harms – and the hypes – may serve to add more confusion, worry, or excitement. Adults may have less experience with AI – or use it in different ways.
How we can help
As part of the project, the research team are keen to help out schools and their communities in any way they can to support more thoughtful, understood and safe digital technology use. Sarah has experience in teaching students from primary school up to master’s level about using digital technologies safely, securely – and legally. Get in touch and we can discuss how we can help further.
Ethical details
This research has ethical approval from UCL’s Institute of Education’s Research Ethics Committee (REC2354), data protection number Z6364106/2026/02/73.