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Access the show notes here: ⁠https://podcast.mrbartonmaths.com/228-hod-space-ep1-praise-tick-sheets-year-7-sets-first-departmental-meeting/⁠

In this episode of the podcast, Jo Morgan and Craig Barton discuss:

1. Praise, and the problem of the "invisible pupils"
Prompted by a question from HOD Space member Megan, Jo and Craig dig into Pritesh Raichura's seating plan tick sheet — where a teacher aims for 30 to 50 individual praises a lesson — and ask whether that's realistic in a maths lesson built around long stretches of independent practice, before turning to how a head of department supports a teacher who wants to try something like this, and what it would take to roll it out across a team.

2. Setting Year 7
Jo explains why her school groups new Year 7s using SATs results rather than a baseline test, how two early end-of-unit tests are used to sense-check those groupings, and why keeping the whole business of setting deliberately low-key matters as much as getting the groups right.

3. Planning your September INSET meeting
Jo makes the case that the first department meeting of the year is the most important one you'll run all year, and talks through what goes into hers — from lesson expectations and homework routines to the admin nudges teachers need and the single department focus that will shape the year ahead.

In an unscheduled episode, Kris Boulton analyses a trainee teacher's volume-of-prisms sequence. He and Craig Barton work through key design principles — simplifying the rule, stripping out the arithmetic, starting with the general case, and building testing and expansion sequences that force genuine mathematical thinking. Access the show notes here: podcast.mrbartonmaths.com/227-breaking-down-an-example-sequence-with-kris-boulton

Returning guest Zach Groshell, author of Just Tell Them, explains how he designs Direct Instruction maths apps for Alpha School. They cover the US school system, why most education apps fail, how atomisation and mastery work on a screen, the limits of data and motivation, and why he chose a different school for his own daughter. Access the show notes here: podcast.mrbartonmaths.com/226-ai-in-education-with-zach-groshell

In this AI in Education episode, Craig Barton welcomes back Dylan Wiliam to discuss what generative and extractive AI mean for assessment, teaching and the purpose of schooling. Wiliam argues the evidence base is thin, urges caution about education's long feedback loops, and distinguishes cognitive offloading from cognitive outsourcing. Access the show notes here: podcast.mrbartonmaths.com/225-ai-in-education-with-dylan-wiliam

Kris Boulton returns for the AI in Education mini-series. He shares how Claude has become fully woven into his daily work, gives a candid first-hand account of his visit to Alpha School in New York, and digs into where AI now sits for creating high-quality maths resources — and where it still falls short. Access the show notes here: podcast.mrbartonmaths.com/224-ai-in-education-with-kris-boulton

Grainne Hallahan, formerly an English teacher, now runs the questions at Teacher Tapp — the app that surveys more than 10,000 teachers a day. She came on with five AI-related findings from the archive, on cheating, lesson planning, attendance targets, and whole-school policies, plus three favourite Teacher Tapp findings to finish. Access the show notes here: podcast.mrbartonmaths.com/223-what-do-10000-teachers-think-about-ai

In this long-awaited sequel (eight years after her last appearance), Craig welcomes back Becky Allen — education researcher, co-founder of Teacher Tap, co-author of The Teacher Gap, and now a consultant to the US-based Alpha School chain — for a deep dive into AI in education, with a particular focus on AI as a personal tutor. Becky is a self-confessed AI optimist who uses LLMs for almost everything (with a fervent endorsement of WhisperFlow voice transcription as a game-changer for giving models richer context). She walks through what she's been seeing inside Alpha School, where students do roughly two hours a day on AI-powered learning apps and spend the rest of their time on project-based learning, sports, and life skills. Her clearest examples of where AI tutoring genuinely shines are in generative prerequisite-knowledge conversations and in forcing students to engage step-by-step with worked examples — pulling them out of the passive eye-darting that kills most textbook learning. From there, Craig walks her through a battery of common sceptical pushbacks (screen time, scalability, Alpha's wealthy demographic, motivation without an audience, the Khanmigo flop, applicability to the Global South, and the future of subject-specialist teachers) and Becky pushes back on each with characteristic nuance. Her core thesis: AI won't transform mainstream schools much — they're too operationally complex to bend — but it will enable a parallel world of micro-schools, alternative provision, and remote subject specialists, particularly for the growing population of persistently absent and home-educated children. The conversation closes with reflections on whether AI will take her own job (and what to advise her children) and a prediction that the most concrete thing AI will fix in mainstream schools is marking. View the show notes here: podcast.mrbartonmaths.com/222-ai-in-education-with-becky-allen

In this episode of the Mr Barton Maths podcast, Craig sits down with Bibi Groot, behavioural scientist at Eedi, to unpack the rigorous research behind their ed-tech work. Bibi traces her journey from the UK's Behavioural Insights Team — where she applied frameworks like EAST (Easy, Attractive, Social, Timely) to public policy — to becoming Eedi's first behavioural scientist after a stint completing a PhD at UCL and having twins. The conversation builds methodically from the fundamentals of randomised control trials (and why they're so notoriously difficult to run well in schools) through the headline results of Eedi's two-year, 20-school RCT showing that students using the platform gained the equivalent of two to four extra months of progress, before diving into the much-publicised Google DeepMind collaboration. That study, run with LearnLM and a human-in-the-loop safety net, found that an AI tutor matched a human tutor on immediate question success and actually outperformed humans on short-term transfer questions — likely because the AI was relentlessly Socratic where time-pressured human tutors tended to short-circuit students' metacognition. Bibi closes by previewing Eedi's much larger four-arm follow-up trial (running until July 2026) testing whether deep student context beats strong pedagogy alone, plus exciting new pilots bringing DQR and WhatsApp-delivered AI tutoring to learners in Guyana, India, and Sub-Saharan Africa. Visit the show notes here: podcast.mrbartonmaths.com/221-building-an-ai-tutor-with-google-deepmind-with-bibi-groot-eedis-chief-impact-officer

A decade after his first appearance on the podcast, Dan Meyer returns to discuss the intersection of AI and mathematics education. Now leading AI feature development at Amplify (which acquired Desmos), Dan brings a uniquely balanced perspective—simultaneously a critic of AI's most maximalist claims and an active builder of AI tools for the classroom. Craig and Dan dig into three core areas: AI as a personal tutor, AI for teacher professional development, and AI for assessment. Along the way, they explore why AI tutors keep falling short of their hype, what Amplify's "discussion moments" feature reveals about thoughtful AI integration, the realities of the Alpha School model, and the social dimensions of learning that no chatbot can replicate. Dan argues that genuine educational improvement may depend less on technology and more on political solutions like teacher pay, class sizes, and addressing inequality—a sobering counterpoint to the dominant AI-as-saviour narrative. the show notes here: podcast.mrbartonmaths.com/220-ai-in-education-with-dan-meyer/

In this episode, I welcome my friend and Eedi co-founder, Dr Simon Woodhead. We dive into the evolution of educational technology, data collection, and AI's role in personalised learning. Join us as we reflect on past innovations, current challenges, and future opportunities in edtech, data science, and AI integrations in education. View the show notes here: podcast.mrbartonmaths.com/219-ai-in-education-with-simon-woodhead-eedis-chief-data-scientist

Education expert Carl Hendrick discusses the transformative potential of AI in education, emphasising how AI can enhance learning science, curriculum design, and personalised instruction. He explores the differences this time around compared to past EdTech innovations and offers insights into practical applications and future implications. Access the shownotes here: podcast.mrbartonmaths.com/218-ai-in-education-with-carl-hendrick