AI in Education #9: Five Things I Learned from Gráinne Hallahan about What 10,000 Teachers a Day Are Actually Saying about AI
This is the ninth in a series of AI in Education specials, where I speak to the world’s leading experts about how AI is changing teaching and learning.
Every other guest in this series has been a researcher, a data scientist, or someone building AI tools for education. Gráinne Hallahan is none of those things. She is a former English teacher from Essex who now runs the questions and data at Teacher Tapp – the app that asks over 10,000 teachers in England three questions a day about what is going on in their schools.
And that is exactly why I wanted her on the show. Because we can debate the promise and peril of AI in education until we are blue in the face, but at some point, we have to ask: What are teachers actually doing? What are students actually doing? And does any of this match what the researchers and the builders think is happening?
It was an absolute pleasure to have Gráinne on the podcast, and I wanted to share five takeaways from our conversation that I think every classroom teacher and school leader will find interesting.
1. 58% of secondary teachers have caught a student cheating with AI in the past month – and the real number is almost certainly higher
Teacher Tapp asked secondary teachers whether they had suspected a student of using AI in the past month, even though they had been told not to. 58% said yes.
That number is striking… but I think it is a significant underestimate.
I was in a school recently where a teacher told her students not to use AI for homework. I was chatting to some Year 10 lads, and they were quite proud of their system. They would screenshot their online homework, send it to ChatGPT, and get the answers. But they knew that if they all suddenly started getting 10 out of 10, the teacher would be suspicious. So they planned it out in advance: one would get question 3 wrong, another would get question 7 wrong. Different mistakes, different scores, no detectable pattern.
That is not an outlier. Kids are onto this. The question is what we do about it.
Of the teachers who did catch students cheating, 77% just spoke to the student, 35% asked them to redo the work, and only 13% issued a sanction. The sanction, assuming it’s sufficiently unappealing to the student, is likely to provide the most significant incentive… but perhaps not the one we hope for. It is likely to incentivise the kids to put more effort into hiding the fact that AI is doing the homework for them, just like the Year 10 lads did.
I believe there’s only one way to solve this problem, and it’s the argument I made in my Is Maths Homework Dead? piece and in my conversation with Adam Boxer. We have to stop judging students on the output they produce outside of class. Instead, set the homework, encourage them to use whatever support they want, and then test them in class on paper with no technology. Use the same questions, but ask for full working out. If they ace the test, then they learned from their homework, whether they used AI or not. If they bomb it, they did not, and can be held accountable for that. The purpose of homework has flipped from assessment to preparation for assessment, so the incentive to cheat disappears immediately.
Gráinne agreed but added that it also needs to be tied to a broader message: the reward is the work itself. She cited recent essays by university graduates who had used AI throughout their degrees and now felt they had cheated themselves out of the education they had paid for. You need the strategy and the culture shift together.
2. Four in ten teachers have never taught students about AI and do not plan to – and they might be right
27% of secondary teachers and 12% of primary teachers have taught students how to use AI tools this year. But the biggest group – four in ten – said they have never done it and do not plan to.
Is this a problem? Maybe, but maybe not.
The best AI tools are paid. The free ones are not great at things where precision matters (eg maths). I wrote about this recently: the workflows I demonstrate in my newsletters rely on Claude’s Max plan, which costs me £75 a month. When teachers try to replicate them on free ChatGPT, they get a completely different – and often terrible – output. And if that is true for teachers, it is even more true for students. Pointing a child towards a free chatbot that cannot count, hallucinates freely, and has access to all kinds of content you would not want a 12-year-old to see is not obviously the right move.
Gráinne drew a comparison I liked: we do not tell students to go home and use VR headsets because not all students have them. AI is not like that on the surface – in theory, everyone has access – but the quality spectrum is enormous, and that gap maps onto existing inequalities.
There is also the question of whether novice learners can even use AI effectively. I keep coming back to this. The only reason I can use AI productively is because I have enough subject knowledge to evaluate the output, catch the errors, and push back when it is wrong. A Year 7 student who does not know whether 4.2 × 19 is closer to 80 or 800 – to borrow Barbara Oakley’s example from earlier in this series – is in no position to catch a chatbot’s mistake.
So maybe those four in ten teachers are making a reasonable call. Their time is better spent teaching their subject than teaching a tool that changes every month, and that their students may not be able to use well anyway.
3. More teachers are using AI to plan lessons – and the ones who need it most are the ones most at risk
The proportion of teachers using AI to plan lessons has risen from 14% to 20% this year. Teachers with the least experience are the most likely to be doing it, which makes sense as they do not have a bank of lesson plans to draw on.
But Gráinne shared a story that should ring alarm bells. A teacher had been given geography on their timetable and was using AI to generate quick starter questions. A colleague walked past, looked at the board, and quietly pointed out that the answers were completely wrong. The teacher had no idea, because they did not know the subject well enough to spot the errors.
This is exactly the scenario that Adam Boxer warned about in his episode. A non-specialist or a novice who generates a worksheet on a topic they do not understand deeply is in a worse position than one who downloads a static resource from a trusted source, because at least with the static resource, someone with subject expertise created it.
Dan Meyer made a similar point in his episode: the best software engineers will be multiplied 10x by AI, and the least experienced will be multiplied by 0.9. An experienced teacher using AI to adapt a curriculum for their specific class is powerful. A novice teacher using AI because they do not know what else to do is dangerous.
Gráinne made a point here that I think deserves more attention. She talked about the relationship between a new teacher and their mentor, and asked me about my own NQT year – about Geraldine, my second in department, who watched my lessons, gave me feedback, told me when I was improving, but also taught me about staffroom culture, what to do and not do, how to survive, how to be a better person.
Gráinne’s argument: for novice teachers, that mentoring relationship is irreplaceable. AI can be a useful supplement, but it should not be the dominant resource they turn to. If we have a problem with access to mentors, we fix the mentoring problem. We do not try to solve it with AI.
4. 17% of schools have no AI policy at all – and in schools that do, teachers often do not know it exists
In secondary schools, 51% of teachers said their school has no AI policy for staff. But when Teacher Tapp asked senior leaders the same question, the vast majority said: “Of course we have an AI policy!”
The gap tells a familiar story: a policy exists somewhere in a shared drive or an email chain, but it has not been communicated, discussed, or embedded in the way that, say, Keeping Children Safe in Education gets printed out and read by every member of staff every September.
Gráinne’s point is simple: you cannot hold a teacher accountable for something you have not told them. If a parent complains that their child’s report was generated by AI, and you have no policy that says teachers should not be doing that, you have no leg to stand on.
The challenge, of course, is that any AI policy specific enough to be useful will be out of date within months. Gráinne’s suggestion is to make it principle-based rather than platform-specific: never put identifiable student information into an AI tool, here are the approved platforms, here are the dos and don’ts, and so on. And then actually give staff time to read it, ask questions, and understand it – rather than burying it in an email.
As an aside, I suspect a fair few school AI policies were themselves generated by AI. Which rather proves the point.
5. Teachers who believe they are getting better are the ones who want to come back – and no AI can replicate that
Gráinne saved her favourite Teacher Tapp finding for last… and it has nothing to do with AI.
Every year, Teacher Tapp asks teachers towards the end of the summer holidays whether they are looking forward to going back to school. Gráinne wanted to know what the enthusiastic ones had in common. She filtered by age, experience, subject, phase, whether they had children at home – nothing explained the pattern.
Then she crossed it with a different question: Compared to this time last year, do you think you are a better teacher?
There it was. Teachers who believed they had improved: 47% were looking forward to returning. Teachers who felt the same or worse: 29%.
That was the only variable that produced the pattern.
Gráinne’s point is that this is the most powerful lever we have for teacher retention – and it costs nothing. A good line manager who says to you, “I can see you are calmer in the classroom this year, your workload seems more manageable, you handled that situation better than you would have last year” – that conversation changes whether a teacher wants to come back in September.
No AI tool can do this. No policy can mandate it. It is a human relationship, built on observation and trust, delivered in a corridor or over a cup of tea. And in a series where we have spent eight episodes talking about what technology can and cannot do for education, I thought it was the perfect note to end on.
Over to you
This was a brilliant conversation, and I have only scratched the surface here. You can listen to or watch the full episode on the Mr Barton Maths Podcast. And if you are a teacher in England and you are not already on Teacher Tapp, download it from the app store. Gráinne reads every message that comes in and answers every question request personally.
This is the ninth in a series of conversations I am having with leading thinkers about AI in education. Here are the others in the series:
I would love to know: does your school have an AI policy? Do you know what it says? And do you agree with those four in ten teachers who have decided not to teach students about AI – or do you think that is a mistake?
Thanks so much for reading.
Craig
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Excellent article. Another one that should be read by EVERY teacher. I used to love TeacherTapp too - one of the things that I miss after I retired. The insight is useful to me too as a governor.