Paul Bentley

Christian, Educator/Teacher, Writer/Editor

Paul Bentley is an educator, author and senior examiner with more than twenty years’ experience in education. He has worked across state and independent schools, secondary education and further education, primarily teaching Economics and Business. Before entering education, Paul worked in retail management. His move into teaching developed into a career spanning classroom teaching, assessment, sixth-form education and work with the wider teaching community. He holds a Master’s degree in Business and Enterprise Education from the University of Warwick and is currently completing a Doctorate in Education. Alongside teaching, Paul has worked as a senior examiner for more than twenty years, giving him extensive experience of assessment and the examination system. He is also an author and has contributed to the wider subject community through writing, professional collaboration and the development and sharing of educational resources. He is a Fellow of the Economics, Business and Enterprise Association (EBEA) and a member of the Chartered College of Teaching. His involvement in education and supporting others extends beyond his professional career. For more than a decade, Paul has served as a trustee of a theatre-in-education company, supporting the use of performance and creativity to engage and educate young people. He has also volunteered with charities supporting people experiencing poverty, people facing mental health crises and people with learning difficulties. These experiences have contributed to his longstanding interest in inequality, opportunity and the importance of recognising individual experiences that can easily disappear behind statistics. Paul has experienced significant changes in both education and technology during his career. Having entered teaching during the rapid expansion of digital technology in schools, he has seen successive innovations change how teachers teach, communicate, assess and organise their work. The emergence of generative artificial intelligence has given new urgency to questions he has been considering throughout his career about the relationship between technology and education. His doctoral research examines technological change in education from the perspective of a practising teacher, with particular attention to generative AI and its consequences for the people working within schools. His wider interests include education policy, economics, technological change, inequality and the ways in which organisations respond to political and commercial pressures. Despite spending more than two decades teaching and assessing other people, Paul remains happiest when learning something himself. He is particularly interested in ideas that challenge apparently obvious answers and in bringing together insights from education, economics, politics, technology and his own professional experience.

I’m passionate about education and the difference that good teaching can make to people’s lives. After more than twenty years as a teacher, I still find classrooms fascinating places. Put thirty young people and a teacher in a room and it is impossible to predict exactly what will happen. A question takes a discussion in an unexpected direction. Someone suddenly understands something they have struggled with for weeks. A student challenges an assumption that everyone else has accepted. A lesson you thought was brilliantly planned falls completely flat, while something improvised at the last minute works wonderfully. I love that unpredictability. I’m passionate about the idea that education should be about more than qualifications, productivity or preparation for employment. Of course, all of those things matter. But education can also give people the confidence to question what they are told, encounter ideas they would never otherwise meet, understand experiences different from their own and imagine that the world could be organised differently. That is also why I care about Economics and Business, the subjects I teach. Economics is sometimes presented as being primarily about money, graphs and markets. I see it much more broadly. It provides young people with a way of asking questions about power, inequality, choices and the distribution of resources. Business provides another perspective on many of the same questions: why organisations behave as they do, who makes decisions and whose interests those decisions serve. I’m particularly interested in questions that do not have neat answers. One of the things I try to encourage in my students is a willingness to be uncertain. It is easy to teach people to reproduce an argument. It is much harder, and much more interesting, to help them recognise competing explanations, examine evidence and decide what they think while remaining willing to change their minds. That principle shapes my attitude towards technology as well. I have always enjoyed experimenting with technology and remain excited by its possibilities. Generative AI is perhaps the most extraordinary technological development I have encountered during my teaching career. I use it regularly and am fascinated by what it can already do. But fascination should not require uncritical acceptance. I’m interested in the questions surrounding technological change as much as the technology itself. Why are some innovations adopted so enthusiastically? What problems are they intended to solve? Who gets to define those problems? Who gains from particular solutions? What happens when a promising idea encounters the complicated reality of an actual school? Those questions matter because education is fundamentally about people. Decisions that appear to concern software, assessment, data or productivity eventually affect the everyday experiences of teachers and students. I’m also passionate about the craft of teaching. Experienced teachers accumulate thousands of small pieces of knowledge that are difficult to put into a manual: when to intervene and when to wait; when a student needs encouragement and when they need challenging; when a class needs structure and when it needs space; when the plan needs to be abandoned altogether. That does not make teaching mysterious or immune from change. Nor does it mean that new technologies threaten everything valuable about education. It simply means we should be careful about confusing the things that are easiest to see and measure with the whole of what teachers actually do. More broadly, I’m passionate about curiosity. I like finding an idea that makes me reconsider something I thought I understood. I enjoy discovering connections between economics, politics, education, technology and everyday life. I enjoy disagreement when it makes everyone involved think harder. And I like the fact that, after two decades in the profession, teaching still regularly confronts me with questions to which I do not know the answer. Perhaps that is ultimately what connects all of these interests. I care about keeping education open to questions. New technologies will continue to change schools. Economic and political pressures will continue to shape what happens inside them. Young people will enter a world very different from the one in which I grew up. I do not think educators can predict that world with any confidence, and I am sceptical of anyone offering a simple formula for preparing students for it. What we can do is help young people develop the knowledge, curiosity and confidence to interrogate the world they inherit. That is what continues to make teaching exciting to me, and it is what I am most passionate about.

Education has always been susceptible to technological promises. In more than twenty years of teaching, I have watched Virtual Learning Environments, interactive whiteboards, tablets, learning platforms and data dashboards arrive promising better learning, greater personalisation, reduced workload and increased efficiency. Generative AI may be different in scale, but the story surrounding it is remarkably familiar. Debate about AI in education tends to focus on what the technology can do. Can it plan lessons, mark essays, personalise learning, provide feedback or tutor a child? If a machine can perform these tasks faster or more cheaply than a human, it is tempting to conclude that it should. I think we are asking the wrong question. My idea worth spreading is that education should not be redesigned around what machines are capable of doing. Instead, AI gives us an opportunity to decide what we believe is uniquely valuable about human education. I am not a technophobe. I have been fascinated by computers since childhood and have experimented with educational technology throughout my career. I use generative AI and find some of its capabilities extraordinary. It can reduce mundane workload, generate ideas and act as a useful intellectual sparring partner. But technological capability is not the same as educational desirability. AI can already reproduce many of the visible outputs of teaching: explanations, questions, feedback, reports and lesson plans. But teaching is not simply the production of educational content. Teaching is relational. Teachers know their pupils, notice when something has changed, exercise judgement, and, sometimes, abandon the lesson plan because an unexpected conversation has become more important. These things are difficult to quantify precisely because much of what matters in education is difficult to quantify. This creates a particular danger. Schools face intense pressures of workload, accountability, and limited resources. Technologies promising efficiency therefore arrive in an environment already predisposed to value whatever can be measured, standardised, and automated. The greatest risk may not be that AI replaces teachers. It may be that we gradually redefine teaching around the things AI can easily do. Instead of asking machines to fit human education, we may begin making human education fit the machines. Efficiency is not a neutral educational objective. A conversation between a teacher and pupil may be slower than automated feedback. A teacher designing a lesson may be less efficient than generating one instantly. Allowing a pupil to struggle with a difficult problem may be less efficient than providing an immediate answer. But education has never simply been about reaching a predetermined output by the shortest possible route. There is uncertainty, curiosity, frustration, humour, disagreement and surprise in genuine education. Teachers and pupils change each other. Sometimes the most important moment in a lesson is the moment nobody planned. Generative AI therefore presents us with an extraordinary opportunity, not because it will finally solve education, but because it forces us to confront a much more important question: What is education actually for? If education is simply the efficient transmission of information, machines may become extremely good at providing it. But if education is also about relationships, judgement, care, curiosity and helping young people make sense of an uncertain world, then the human beings in our classrooms are not an inefficiency waiting to be engineered out of the system. They are the point of it. Generative AI may prove to be one of the most significant educational technologies of our lifetime. Its greatest contribution, however, could be unexpected. By showing us how convincingly machines can imitate some of the things teachers do, AI may finally force us to articulate the things that imitation cannot capture. So rather than asking of every new educational technology, What can this machine do?, we should ask what kind of education do we want, and does this technology help us create it? The machine should serve the pedagogy. The pedagogy should never serve the machine.

economics and society., Education and pedagogy; Economics and Business education; assessment and examinations; generative AI and educational technology; education policy; teacher workload and professional practice; sixth-form education; and the relationship between technology