The strength of current debates about the use of artificial intelligence (AI) in education can make it feel as though we must choose a side. Is it exciting, or alarming? Should the sector embrace AI, or resist it?
Whatever position individuals may land on, the most useful approach we can take as educators is to make sure we remain curious.
That is the idea behind Curious Questions, a series of three conversations produced by the Centre for Digital Information Literacy in Schools and hosted by Benjamin Riley, founder of Cognitive Resonance.
Across the series, teachers, researchers, and education thinkers with different perspectives examine the implications of AI on information, learning and teaching. The conversations are not debates where the panellists have opposing views; nor are they designed to produce a consensus. Rather, they are conversations in which the guests test various assumptions, question each other, and in some cases, actually change their minds.
Across all three episodes the same idea keeps surfacing: AI is not simply introducing new tools. It is making us look again at some of the most fundamental questions in education.
1. What shapes what we believe?
The first episode explores misinformation, cognition and our changing information environment. Generative AI can already produce convincing text, images, audio and video at scale; and increasingly, it is becoming a way of accessing information itself. Instead of searching through sources, we can now ask a chatbot a question and receive a fluent, confident answer.
This makes familiar critical questions even more important: Where did this information come from? What is the evidence? Can it be corroborated?
But the conversation goes further. What people believe is not only shaped by their ability to evaluate evidence, but also by identity, emotion, belonging, repetition and what others around them appear to believe. Navigating misinformation therefore requires us to understand something about information systems and something about ourselves.
2. What do we value about learning together?
The second conversation examines one of AI’s most attractive promises: personalised learning. The benefits of an AI tutor are that it can adapt explanations, vary its pace, and individualise feedback according to each pupil’s needs. On the surface, this is difficult to argue with. But what exactly is being personalised? Is it the content? The level of challenge? The pupil’s interests? Their misconceptions? Or what they need to learn next?
And more importantly, by adopting this type of technology, what might be lost? After all, a classroom is much more than just a means of housing 30 individual tutoring relationships. Pupils’ learning is significantly enhanced by listening to each other, hearing their classmates’ questions, watching their teacher model an idea, and struggling collectively with something difficult.
The nuances between subjects and phases also mean the added value of personalisation is likely to vary. What helps a pupil practise mathematics is very different from what supports interpretation of historical evidence, discussion of a novel or participation in music. The important question is not simply whether AI can personalise learning, but whether it supports the kind of learning we value, without eroding the shared, social experiences that matter so much.
3. What could technology help teachers notice?
The final discussion turns from pupil-facing tools to a frequently neglected question: could AI be used to help teachers understand more about their own practice?
Teaching demands continual explanation, questioning, monitoring, responding and adaptation. It is difficult for any teacher to remember everything that happened while they were intensely occupied with making it happen.
Emerging technologies could potentially help teachers to notice patterns that are difficult to perceive in the moment. But this immediately raises questions about context, privacy, trust, surveillance and professional autonomy. The sorts of practices that can be counted are not necessarily those that matter most; and the collection of information to support development would become unpalatable if it were used to monitor or judge.
The challenge is therefore not to ask AI to decide whether somebody is a good teacher. It is to explore whether technology could provide better evidence for teachers and mentors to interpret together, while ensuring that teachers remain agents in their own professional learning.
Three conversations, one invitation
Together, these conversations move from how AI is shaping what we believe, to how we learn, and to what teachers can notice.
There are no neat answers; but the conversations model something education will need as AI develops: the ability to welcome possibility without suspending judgement, to take risks seriously without being paralysed by fear, and to remain open to changing our minds.
AI may be changing the answers available to us. Curious Questions is an invitation to think more carefully about the questions we ask.
Listen to all three episodes of Curious Questions and join the conversation.
- Pip Sanderson is Head of the Centre for Digital Information Literacy in Schools at the National Institute of Teaching
We welcome perspectives from a diverse range of guest contributors. The opinions expressed in blogs are the views of the author(s), and should not be read as CST guidance or CST’s position.
