Foundational Impact

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Oct 2026

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Welcome to Foundational Impact, a podcast series that focuses on education and artificial intelligence from a nonprofit perspective. Hosted by Daniel Emmerson, the Executive Director of Good Future Foundation, a non profit whose mission is to equip educators to confidently prepare all students, regardless of their background, to benefit from and succeed in an AI infused world. This podcast series sets out to explore the trials and tribulations of building a non profit from the ground up, while also investigating the changing world of technology in life, learning, and work.

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October 27, 202624 min

How Teacher Training Change When AI Enters the Picture with Prof Miles Berry

In this episode from the Festival of Education 2026, host Daniel Emmerson speaks with Professor Miles Berry, Professor of Computing Education at the University of Roehampton. Miles discusses what AI changes for teaching and learning, the importance of universal AI literacy in national curriculum reforms, and how initial teacher training is evolving to address generative AI. He shares insights on balancing teacher efficiency with preparation quality, the ethical nuances of machine-generated feedback and academic integrity, and how tools like "vibe coding" are changing software development for educators. Key Topics & Timestamps 00:00 Vibe Coding and Software Creation 00:28 Host Introduction 01:00 Live at the Festival of Education 01:19 Modeling Ethical AI and Transparency 02:54 AI Literacy and the Head, Hands, Heart Approach 04:07 Curriculum Reform and Universal AI Literacy 05:23 Teacher Training and Lesson Planning 07:41 Quality vs. Efficiency in Planning 10:16 AI Marking and Student Motivation 12:28 Teacher Education Frameworks and SEND 13:49 Multimodal Tools and Language Acquisition 15:22 Roehampton’s AI Strategy for Graduates 17:56 Handling AI Integrity in School Interviews 20:02 Defining Cheating and Transparency Acknowledgements 22:09 The Joy of Vibe Coding Key Takeaways & Highlights Head, Hands, and Heart: Teaching AI requires a balanced framework—understanding how models work (head), practical prompt engineering and bias mitigation (hands), and analyzing societal and ethical implications (heart). Universal AI Literacy: AI education cannot be reserved solely for computer science students; upcoming curriculum reforms aim to ensure every young person develops core AI literacy. Preparation Over Output: While AI can generate lesson plans quickly, the true value of planning lies in teacher preparation and thinking through the lesson, which automated tools might inadvertently bypass. The Human Element in Feedback: Students often value feedback because it signals that a human teacher cared enough to review their effort; automated AI marking risks demotivating learners, especially in creative subjects. Embracing Vibe Coding: Natural language programming tools allow non-traditional developers to build tailored, useful educational software through simple, iterative conversations. Resources Mentioned University of Roehampton Secondary PGCE: Initial teacher training programmes for secondary education. https://www.roehampton.ac.uk/study/postgraduate-taught-courses/pgce-secondary/ AI4K12 Project: Initiative providing resources and guidelines for AI education in K-12 schooling. https://ai4k12.org/ BCS, The Chartered Institute for IT: England computing curriculum committee promoting digital skills and computing education. https://www.computingatschool.org.uk/digital-themes/cas-ai-zone/ Guest Contact Information Guest: Professor Miles Berry (Professor of Computing Education, University of Roehampton) Miles is Professor of Computing Education at the University of Roehampton, where he is head of curriculum and recruitment for the secondary PGCE as well as leading the PGCE in computing course. He supervises doctoral students and is a member of the University's AI development and innovation group. Prior to joining Roehampton, he spent 18 years in four schools, much of the time as an ICT coordinator and most recently as a head teacher. He has worked with Cambridge University Press and Assessment on a number of curriculum and training development projects. He helped write England's national curriculum computing programmes of study. He gave evidence to the House of Lords AI select committee, was an expert advisor to the US-based AI4K12 project, and supported Georgian universities in developing academic integrity policies. He chairs the BCS England computing curriculum committee, and until recently was chair of the National Centre for Computing Education's academic board.

October 20, 202626 min

AI Trends in Schools Revealed by Teacher Tapp Data with Grainne Hallahan

In this episode live from the Festival of Education at Wellington College 2026, host Daniel Emmerson speaks with Grainne Hallahan, Head of Community at Teacher Tapp. Grainne shares unique data-driven insights into how UK teachers feel about artificial intelligence, the shifting patterns in subject-specific AI adoption, and why asking precise, time-bound questions is essential for capturing classroom realities. She also offers practical guidance for school leaders on policy formulation, teacher anonymity, and effective survey design. Key Topics & Timestamps 00:00 Friday Behaviour Questions 00:20 Introducing Grainne Hallahan 01:49 What Is Teacher Tapp 03:10 Designing Daily Questions and Finding Insights 06:38 Panel Randomisation and Response Experiments 10:22 Longitudinal Data and Behaviour Tracking 11:13 Tracking Teacher AI Adoption Trends Over Time 12:51 The 10 Percent Non-User Group and Environmental Concerns 13:50 Subject Trends and Primary vs Secondary Usage 16:42 Sharing Findings with Policymakers and the Media 18:36 Teacher Motivation and Anonymity 23:21 School AI Policies and Future Research Areas 24:54 Tips for School Leaders Writing Effective Surveys Takeaways & Highlights Data-Driven Teacher Voice: Daily three-question surveys sent to a re-weighted panel of 10,000 teachers allow Teacher Tapp to capture real-time classroom sentiment and represent the profession accurately across government consultations and media broadcasts. Shifting AI Adoption Patterns: The proportion of teachers who have never used AI for schoolwork has fallen to under 10%. Primary teachers initially led adoption for generating exemplars and short-form questions, while maths teachers have seen a major turnaround since tools gained image and diagram generation capabilities. Environmental and Ethical Concerns: Environmental impact has emerged as a primary reason why the remaining minority of teachers choose to abstain from using AI tools in their professional duties. Anonymity Drives Honest Reporting: True data separation and absolute respondent anonymity are vital for understanding shadow AI usage and unearthing candid feedback that school policies might otherwise mask. Designing Actionable School Surveys: When surveying staff, school leaders should restrict questions to recent, specific timeframes (such as "this week"), keep options below ten, and eliminate unnecessary verbiage to obtain clear, reliable responses. Resources Mentioned Teacher Tapp: Daily survey app for educators in England. https://teachertapp.com/ Guest: Grainne Hallahan (Head of Community, Teacher Tapp) Grainne Hallahan is a teacher-turned-journalist who now sets the questions at Teacher Tapp. She is interested in all things education, but gets particularly excited about what keeps teachers teaching, and how changes to education policy can make a difference to those doing the hard work in the classroom and school leadership.

October 13, 202618 min

Navigating AI Friction and Future Work Anxiety in Schools with Dr. Iro Konstantinou

In this episode from the Festival of Education at Wellington College 2026, host Daniel Emmerson speaks with Dr Iro Konstantinou, Head of Research and Impact at Eton College. Dr Konstantinou discusses the role of artificial intelligence in education, highlighting findings from primary data gathered across diverse UK schools. She explores the concept of cognitive offloading, how students' perceptions of AI are influenced by their background and social media, and how schools can prepare students for an AI-impacted workplace by fostering critical thinking and transferable skills. Key Topics & Timestamps 00:00 Cognitive Struggle and Early AI Perceptions 00:28 Introducing Dr Iro Konstantinou 01:23 Highlights from the Festival of Education 02:00 Overview of Research at Eton College 03:25 Gathering Primary Evidence on Student AI Use 05:24 Regional Disparities and Student Attitudes Towards AI 06:57 Personal AI Usage and Data Privacy Awareness 08:24 The Role of Social Media in Shaping AI Perceptions 09:19 Teachers' Concerns and the Cognitive Offloading Trap 11:04 Classroom Strategies: Prohibition vs Socratic Prompting 12:11 Workplace Anxiety and Changing University Choices 14:27 Supporting Schools with Industry Skills and Best Practice 15:25 Community Outreach and Collaboration at CIRL 17:11 How to Connect and Get Involved with Eton’s Research Key Takeaways & Highlights Academic Skepticism vs. Overconfidence: Students at highly selective academic schools often express a desire to maintain "cognitive struggle" and avoid AI, whereas students in other settings use AI for personal tasks without fully grasping data privacy risks. The Influence of Social Media: Many young people rely on social media platforms rather than formal guidance to form their understanding of AI ethics, safety, and application. Diverse Classroom Approaches: Teacher responses range from strict prohibition to incorporating Socratic prompting, highlighting the need for explicit metacognitive training to support critical thinking. Shift in Workplace Expectations: Students are altering higher education paths due to career automation concerns, pointing to a need for schools to emphasize transferable human skills and philosophy-driven thinking. Democratising Educational Research: Outreach initiatives focus on sharing best practices and supporting schools in underserved areas to ensure AI evidence-based guidance is accessible across the sector. Resources Mentioned The Tony Little Centre for Innovation and Research in Learning (CIRL) at Eton College: Research hub focusing on pedagogy, evidence-informed practice, and AI impact. https://cirl.etoncollege.com/ Department for Education (DfE) Gen AI Product Safety Standards: Standards addressing friction in learning and cognitive offloading risks. https://www.gov.uk/government/publications/generative-ai-product-safety-standards Guest Contact Information Guest: Dr Iro Konstantinou (Head of Research and Impact, Eton College) Dr Iro Konstantinou is an education researcher and adviser specialising in evidence-informed practice across schools, universities, and the wider education sector. She currently serves as Head of Research and Impact at Eton College, where she leads research on curriculum development, professional learning, equity, and the impact of AI on education. Previously, she held academic and leadership roles at Pearson, UCL, and the University of Warwick. She is also a trained coach, having completed an undergraduate course in coaching at the University of Cambridge. LinkedIn: https://www.linkedin.com/in/dr-iro-konstantinou/

October 6, 202627 min

Equity versus Productivity in the Age of AI Education

Episode Overview In this episode from the Festival of Education at Wellington College 2026, host Daniel Emmerson speaks with Victoria Hedlund, founder of GenEd Labs. Victoria discusses bias in generative artificial intelligence, the importance of inclusion, and what meaningful human oversight should look like in education. She also explores how educators can challenge AI outputs, balance productivity with equity, and preserve the essential human element in teaching. Key Topics & Timestamps 00:00 Putting Output on Trial 00:33 Introduction to Victoria Hedlund 01:37 Researching Bias and Human Oversight 03:11 Why Schools Must Focus on Bias 05:56 Sparks, Lightbulbs, and Gender Stereotypes 08:12 Frequency of Exposure: Teachers vs AI 09:09 Visual Representation and Image Bias 13:06 Questioning Assumptions and Model Iteration 17:09 Equity Versus Productivity 20:49 The Human in the Loop 24:30 Embracing Messy Humanness in Education Key Takeaways & Highlights Putting AI on Trial: Teachers and students should treat AI outputs critically, challenging assumptions and testing validity rather than accepting generated content at face value. Deficit vs Strengths-Based Framing: Standard AI prompts often apply deficit-based language to neurodivergent or marginalised learners, requiring specific contextual framing from educators to deliver equitable outputs. Frequency of Exposure: While human teachers hold natural biases, students interact with AI models through hundreds of continuous iterations, amplifying potential harm if outputs remain unmitigated. Average vs Instantaneous Productivity: Relying on AI for quick administrative wins can sacrifice long-term accuracy, making upfront contextual alignment crucial for meaningful workload reduction. Preserving the Human Element: Complex emotional needs, non-verbal communication, and relational learning cannot be replicated by software, keeping human teachers central to classroom learning. Resources Mentioned GenEd Labs: Innovation lab focused on artificial intelligence research, inclusion, and educational tools. https://www.genedlabs.com/ Guest Contact Information Guest: Victoria Hedlund (Founder, GenEd Labs) Victoria is a thought leader, researcher and consultant focused on fair AI use in education. Known as the ‘AI Bias Girl,’ she creates practical awareness and mitigation strategies for educators and leaders, using her research of emergent AI bias in educational contexts. She is a major voice in AI pedagogical alignment and has contributed to the updated DfE and Chartered College Safe and Effective Use of Generative AI in Education Guidance , and to the British Computing Society's AI course ‘AI Confidence’. She is editor of AI Bias in Education and author of 100 Quick GenAI Prompts for Teachers and Educators . She sits on the advisory board for the Institute of AI Education, is a member of the Centre for Digital Information Literacy in Schools Expert Working Group, and is part of Oxford University's AIEOU network. She convenes the Teacher Education AI Network (TEANs).

September 29, 20260 min

Foundational Impact | Official Trailer

Foundational Impact is a Good Future Foundation podcast exploring how artificial intelligence is changing education. Through conversations with people whose work is shaping the direction education takes next, we examine the evidence, the challenges facing schools and the decisions being made across the sector. Hosted by Daniel Emmerson. Follow Foundational Impact on Spotify, Apple Podcasts or wherever you listen. Website: www.goodfuture.foundation

September 29, 202623 min

The Role of AI in Student Feedback with Daisy Christodoulou

Episode Overview In this episode from the Festival of Education at Wellington College 2026, host Daniel Emmerson speaks with Daisy Christodoulou, Director of Education at No More Marking. Daisy discusses the role of artificial intelligence in educational assessment, emphasising the importance of actionable feedback over lengthy written notes, the mechanics of comparative judgment, and why handwritten work remains vital for learning. She also addresses the potential pitfalls of AI in schools and offers key guidance for school leaders navigating integration. Key Topics & Timestamps 00:00 Speed As Quality 00:36 Meet Daisy Christodoulou 01:57 Is Written Feedback Useful 02:29 Thermostat Feedback Model 03:32 Comparative Judgment Explained 04:53 AI Judges And Benefits 06:09 Avoiding The Doom Loop 10:48 Student Trust And Emotions 12:48 Fast Feedback Tradeoffs 14:59 Handwriting Versus Typing 17:14 Digitizing Handwritten Work 17:57 Assessment Tradeoffs And Standards 20:21 Advice For School Leaders 21:56 Hopes For AI In Schools Key Takeaways & Highlights Thermostat vs. Thermometer: Assessment feedback shouldn't just measure performance; it needs to change performance by providing actionable steps such as personalised quizzes. Speed as Quality: A scrappy, immediate response can be significantly more effective for student improvement than a polished response delivered weeks late. The 90/10 Rule: Integrating AI into comparative judgment (90% AI, 10% human judging) ensures every paper is reviewed multiple times while maintaining human oversight. Cognitive Differences in Mediums: Research shows moving tests to screens can lower student outcomes compared to paper-based assessments, making handwriting recognition a vital bridge for digital reporting. Action on Shadow AI: Leaders who delay setting AI policies risk teachers resorting to unvetted, consumer-facing tools during high-workload periods. Resources Mentioned No More Marking: Comparative judgment platform for student assessment. https://www.nomoremarking.com/ John Jerrim / PISA Research: Natural experiment study comparing student performance on paper vs. digital test formats. https://johnjerrim.com/papers/ Guest Contact Information Guest: Daisy Christodoulou (Director of Education, No More Marking) Daisy Christodoulou is the Director of Education at No More Marking, a provider of comparative judgement assessments. She works closely with schools in the UK, Australia and USA on developing new approaches to assessment, and on applications of artificial intelligence in the classroom.Before that, she was Head of Assessment at Ark Schools, a network of academy schools. She has taught English in two London comprehensives and has been part of UK government commissions on the future of teacher training and assessment. Daisy is the author of three books about education: Seven Myths about Education (2013), Making Good Progress? The future of Assessment for Learning (2017), and Teachers vs Tech (2020).

July 21, 202636 min

Stop buying tools before you’ve answered this

Our guest in this episode is Dr Fiona Aubrey-Smith, an independent researcher who studies the relationship between pedagogy and digital tools, and the lived experience of students in the classroom. Fiona opens by explaining why identical classroom practices can produce completely different outcomes depending on the belief system behind them. Her example of two teachers greeting students at the classroom door in seemingly the same way, but for very different underlying reasons, shows how policies alone don't determine impact; the intent behind them does. The conversation moves into belonging and dignity, including research showing that struggling students typically ask for help only 1-3 times in a lesson regardless of how much support they need, while confident students almost never ask to be pushed further. Daniel and Fiona discuss the tension between protecting a student's dignity and the value of productive vulnerability. From there, Fiona lays out her framework for introducing technology into schools: start with the purpose of school, define the role of the learner, describe what the learning experience should feel like, define the role of the teacher, and only then decide which tools will help deliver it. Starting with the tool itself, before asking why, is a costly and common mistake. Two school case studies illustrate this in practice. At Haileybury, an embedded one-to-one, on-demand digital provision (available at the point of need rather than simply issued to every student) has freed teachers to rethink classroom layout entirely. At Connect Education Trust, a similar model has extended digital skills and connectivity into the home, empowering families to support learning without needing their own digital capability, coinciding with outstanding inspection outcomes. On generative AI, Fiona shares some thoughtful use cases she sees, such as chaining AI tools to help secondary students revise, and using AI image generation to help primary students with their descriptive writing. She wraps up with a challenge for school leaders. Rather than starting with policies or tools, ask what your school would leave behind if it closed tomorrow, since that gap is where the real human value lies. From there, let AI and digital tools take on the automation and acceleration, so teachers are freed up for the parts of the job only a human can do.

June 30, 202631 min

Are Young People Forming Relationships with AI?

What does AI mean for the way young people relate to each other and to technology itself? That's the focus of the conversation in this episode when Daniel speaks with Jonathan Baggaley, CEO of the PSHE Association and former head of the Child Exploitation and Online Protection Centre. It begins, perhaps unexpectedly, with a Sun Ra poster. Jono uses it to make a point that runs through everything that follows. That is, many of the narratives about AI are being presented as inevitable, and educators have both the right and the responsibility to push back on that. PSHE has been on a long road to statutory recognition in England. Jono maps that journey from the near-miss of the 2010 election wash-up to the introduction of compulsory Relationships, Sex and Health Education in 2019. The results are becoming visible. Between 2022 and last year, the share of young people rating their RSE as good or very good roughly doubled. Yet the subject now faces a technology landscape that changes faster than any curriculum can follow, and it was never designed for that. Much of the conversation focuses on something schools have been slow to address, which is the emotional attachment to AI chatbots. Evidence from a Reddit study found that 60–70% of people who had developed an AI relationship hadn't gone looking for one. They'd simply been chatting. Jono explains this isn't surprising as humans are neurologically primed to anthropomorphise from infancy, attributing intention and agency to moving shapes before they can speak. Even Jono, who understands exactly what large language models are, has caught himself feeling the presence of something in a chatbot conversation. The question is how schools can build resilience to that instinct by giving young people the understanding they need to use them critically. Language, Jono argues, is part of the problem. The word "chatbot" suggests conversation, when what's actually happening is an engagement with a probabilistic automation system. Shifting that framing is one starting point. Another is cross-curricular. Computing can explain the move from rule-based to data-driven AI, citizenship can explore the environmental and geopolitical implications, and PSHE can build on its existing relationships curriculum to examine what young people are and aren't getting from these interactions. The episode sits with a harder question too. Consumer AI is designed for frictionless ease, age verification is often a checkbox, and young people will encounter these tools whether schools introduce them or not. But Jono is clear-eyed about what the evidence shows. When young people genuinely understand what they're dealing with and what they're trading away, they are willing to increase their own friction. None of this requires a new policy or a perfect tool. The conversation is the intervention, and any curriculum that starts with the human already has what it needs.

June 9, 202631 min

Education on the Front Line

What does great education look like when the classroom is a refugee camp? When the teacher is under-resourced, under-supported, and still showing up? We are delighted to welcome Jane Mann, Managing Director of the Partnership for Education and Education Director for International Education at Cambridge University Press and Assessment. Jane leads work spanning 30 countries, including some of the world's most fragile and complex contexts, from refugee camps to conflict zones. And while no two contexts are ever quite the same, she is clear that the fundamentals of great education do not change. Wherever you are in the world, the foundations look the same: a coherent curriculum, meaningful assessment, well-supported teachers, strong leadership, and quality materials. In conversation with Daniel, Jane reflects on the role of technology and the importance of letting context lead. Where it is available and appropriate, technology can be transformative. But it carries real risks too: widening equity gaps and creating new vulnerabilities in settings where a device is a valuable and coveted object. On AI specifically, rather than rushing it into students’ hands, Cambridge's focus is on the adults in the room to empower teachers, streamline curriculum mapping, support lesson planning in under-resourced regions like sub-Saharan Africa, and help governments build policy frameworks. The HP Cambridge EdTech Policy Fellowship extends this work further to facilitate structured cross-national learning and conversations and drive systemic change. Tune in for a conversation that is as expansive in its thinking as it is grounded in the realities of education on the front line.

May 19, 202630 min

Philanthropy Filling the AI Education Gap

The conversation between Elizabeth Moore and Daniel in this episode provides a window into how the Gates Foundation is navigating the evolving landscape of AI in K-12 education. As Deputy Director with the U.S. K-12 team, Elizabeth explains that the Gates Foundation operates at multiple levels to improve classroom instruction through research, quality standards, and strategic investments. This includes influencing frontier AI labs like OpenAI and Google, developing evaluation frameworks, and creating networks to disseminate evidence-based practices. They choose this approach hoping to help bridge gaps that neither government nor markets adequately address, particularly important as AI development outpaces traditional curriculum cycles. One concerning trend that Elizabeth observes when discussing AI adoption in schools is the well-meaning but counterproductive “no AI” policies that prevent students from developing critical skills for their futures. She, instead, advocates for thoughtful implementation guided by clear educational purposes and robust evaluation of outcomes. The conversation also highlights mathematics as an area with AI potential. Elizabeth describes how AI can support personalised learning by instantly diagnosing specific prerequisite skill gaps and delivering targeted instruction which is a process that traditionally required extensive teacher time and effort. Other suggestions for school leaders that are mentioned by Elizabeth in the episode include: Involve teachers in evaluating AI tools by encouraging them to test the systems' boundaries Align on the specific educational problems AI should solve before implementation Look beyond data security to broader considerations of pedagogical quality Create transparent communication channels with parents about AI's purpose and impact Throughout the discussion, Elizabeth emphasises the need for healthy skepticism about AI-generated data, balanced with recognition of its potential to enhance parent engagement and address learning gaps when implemented with clear purpose and ongoing assessment. Tune in to discover how one of education's most powerful philanthropies is working behind the scenes to ensure AI serves teachers and students, not the other way around.