I Read 25 Studies on AI in Education. Here’s What Teachers Are Actually Doing.

I am going to start where no good teacher should start, with a $10 word: epistemology. It refers to a branch of philosophy that explores how we know what we know – something scholars like John Dewey argued is deeply tied to experience, not just information.

Your kid was born for this exact moment in history, with possibilities ahead of them that previous generations could only dream about.
The only question left is: will you let this failing system stifle your kid’s potential, or will you go looking for something to unleash it?

Understand how GenAI is reshaping learning and formative assessment.  Generative AI is changing how learners engage with language – and raising tough questions about assessment. If students can lean on GenAI, how do we still see what they truly know and can do? Our Assessment Evolved report explores how formative assessment can evolve in response. With the right design, GenAI doesn’t undermine learning – it can enhance reflection, strengthen feedback and deepen language use.

Language is central to learning. Across many contexts worldwide, schools and classrooms bring together learners with diverse linguistic backgrounds and identities. This diversity enriches communities but also requires careful decisions about which languages are used in education, and how. In multilingual contexts – including those shaped by colonial histories or high mobility – these decisions are often complex.

What are the burdens and benefits that GenAI technologies and the policies designed around these technologies create, and are these burdens and benefits fairly distributed among students, on the one hand, and teachers, on the other? More generally, can assessment be fair or be made to be more fair in the age of GenAI? These are the kind of questions that the Fair Educational Assessment in the Age of GenAI (FAIR-ASSESS) project at Leiden University tries to answer.

Drawing on experience across higher education in the UK and Malaysia, two academics argue that the real AI divide in universities is not about access to tools but about institutional readiness — and why it is an urgent equity issue policymakers can no longer afford to ignore.

Monty Python covered this in the 1970s. In one of Terry Gilliam's surrealist animations, a television set opens up to jab and pluck at the eyes of the hapless viewer whilst his wife crows 'Henry, turn that television, you know it's bad for your eyes.' The sketch was aimed firmly at the moral panic over…

From the Pod: 7 things parents get wrong about screens. We talk about the data showing exactly how much "dumb screen time" is already cluttering traditional classrooms, and how one-to-one AI tutors can keep kids in the zone of proximal development. Done right, screens are how we demand more from our students, accelerate their learning by multiple grade levels, and raise high-agency kids in a digital world.

I hate either/or thinking. It flattens complexity into something easier to argue with, but less true. False binaries make for lively debates, but what happens when we sit in the uncertainty, the messy middle, a little longer instead of rushing to pick a side?

There’s a reason the class clown always wins. When rules come from above and kids have no say in shaping them, rebellion becomes the only way to feel powerful. The kids who buck the rules get the laughs, the stories, the social capital. The rule-followers are seen as vanilla. So of course kids goof off and heckle. The system is handing them two options: be obedient and invisible, or disruptive and cool.