The Science of Learning

Keith Sawyer
  • 5.0 (2)
  • Education
  • Updated Biweekly

The Science of Learning explores what research tells us about how people learn—and how we can learn better. In each episode, Dr. Keith Sawyer, the Morgan Distinguished Professor of Educational Innovations at the University of North Carolina at Chapel Hill, and the editor of The Cambridge Handbook of the Learning Sciences, talks with leading researchers about the science of learning. These conversations go beyond myths and trends to focus on evidence-based insights from cognitive science, neuroscience, and the learning sciences. The podcast examines how learning really works: from memory and attention to social interaction, embodiment, and the design of learning environments. Episodes connect rigorous research to practical implications for teaching, education, and everyday life. Guests include many of the most influential scholars in the field, offering a rare opportunity to hear directly from the people shaping how we understand learning.

  1. 6d ago

    Why Students Learn More When They Fail: Manu Kapur on Productive Failure

    What if struggling with a problem before you know how to solve it actually helps you learn? My guest is Manu Kapur, the learning scientist who developed the influential concept of productive failure. His research challenges one of our most common assumptions about teaching: that the best way to help students learn something new is to explain it clearly first, and then have them practice it, repeat it, apply it, and give them feedback on whether they do it right or wrong.  Watch the full video interview on YouTube: https://youtu.be/kvAhZuuxNCg Kapur's research suggests that, for complex concepts, it can be more effective to reverse that sequence. In his productive failure pedagogical designs, students first explore a carefully designed problem that they don't yet know how to solve. It's a hard problem, and they struggle. They'll often go down an incorrect path or a dead end. The teacher then explains the expert solution and how that is related to their own experiments and struggles. The initial struggle activates students' prior knowledge and prepares them to understand the instruction at a deeper level. In our conversation, we discuss:  why getting the right answer isn't necessarily the same as understanding; why the timing of instruction matters; and why struggle, mistakes, and even failure can be powerful parts of learning. Kapur explains what productive failure looks like in an actual classroom, using examples from mathematics including standard deviation, calculus, and linear algebra. He also describes research showing that relatively small changes to instruction can produce substantial improvements in student learning. In one university mathematics course, inserting Productive Failure activities before just ten major concepts increased the passing rate from about 55 percent to 75 percent. We also explore a broader lesson about learning: if something is always easy, you may not be learning very much. Productive failure doesn't mean simply letting people fail. Kapur emphasizes that these learning experiences must be deliberately designed, psychologically safe, and followed by expert instruction. The goal is to create low-stakes opportunities for productive struggle so that learners develop deeper understanding—and are less likely to fail when the stakes are high.  We also discuss whether productive failure can work outside mathematics and science, where Kapur originally developed the approach. We talk about how it can be used in workplace learning and apprenticeships, and what athletes, mathematicians, surgeons, and pilots can teach us about learning through struggle.  The Science of Learning is hosted by learning scientist Keith Sawyer and features conversations with leading researchers about what science tells us about how people learn.  Subscribe to The Science of Creativity Substack newsletter: https://keithsawyer.substack.com/ Watch the full video interview on YouTube: https://youtu.be/kvAhZuuxNCg  Music by license from SoundStripe:  "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright ©️2026 Keith Sawyer

    Why Students Learn More When They Fail: Manu Kapur on Productive Failure

  2. Sep 22

    Can Kids Build Their Own A.I.? Reinventing Learning with Yasmin Kafai

    Are computers ruining childhood? It seems to get worse every day. Students are using AI to write all of their homework. Children spend hundreds of hours playing videogames. And then there are cell phones and social media! It seems that with AI, people stop using their creativity. If people no longer make things on their own, then how will they learn to be creative? In this episode, you'll hear about a fascinating way to flip this around. A way to use computers to return creativity to childhood. My guest, Dr. Yasmin Kafai, has developed a way for children to create their own AI systems and to create their own videogames! It sounds far beyond the ability of a child to design an AI or build a computer game. But it's happening, today, and it's not just in the research lab. It's happening in schools around the world. and it could be your child. It could be your neighborhood school.  Watch the video interview on YouTube: https://youtu.be/_A9Iv-A8ZdI In this episode of The Science of Learning, I talk with Dr. Yasmin Kafai, a learning scientist whose research has helped transform how we think about children, technology, and learning. For more than three decades, she has shown that children can learn complex ideas by creating things that matter to them—and sharing what they make with others. Dr. Kafai tells us about her early research at the legendary MIT Media Lab. She worked in the group that developed the first programming language for children, called Scratch. It was a visual drag-and-drop user interface that allowed kids to move images around, on the screen, and control simple robots. This turned into the wildly successful LEGO Mindstorms product line, and then, similar programmable robots from many manufacturers.  In her latest research, Kafai is extending that vision to artificial intelligence. She describes how high school students can build their own generative language models. She calls them "baby GPTs." The students choose the data they will train their models on. Then they develop the models and they test their outputs. Students gain a deeper understanding of how AI works, what it can do, and where it falls short. Imagine: These students are going to understand AI better than 99 percent of everyone out there. Instead of banishing AI, Kafai is performing a kind of jujitsu: She's using AI to guide students to be more creative. She's using AI as a tool to foster creative learning. This episode helps us understand how we can help children become creators and critical thinkers in a world increasingly shaped by AI. You can watch the full video interview on YouTube: https://youtu.be/_A9Iv-A8ZdI Music by license from SoundStripe: "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright (c) 2026 Keith Sawyer

    Can Kids Build Their Own A.I.? Reinventing Learning with Yasmin Kafai

  3. Sep 8

    Can an Entire Society Learn? Educational Reform in Thailand with Paulo Blikstein and Deborah Fields

    What would it mean for an entire society to learn? Most research on learning focuses on individuals—students learning in classrooms, employees learning at work, or people learning new skills. But learning scientists Paulo Blikstein and Deborah Fields have spent years documenting something much more ambitious: a 25-year experiment in Thailand that brought new ideas about learning into schools, villages, farms, factories, and communities. Their new book, The Society That Learns, tells the story of what happened when ideas from constructionism—associated with Seymour Papert and MIT—were introduced in Thailand in the late 1990s. Rather than simply importing an American educational model, Thai educators and communities adapted these ideas to their own culture and circumstances. Prefer video? Watch the full video interview on YouTube: https://youtu.be/i4J3zWuejKY In this episode, we hear remarkable stories of villages using learning to address debt and water shortages, teachers reinventing their classrooms, and factory technicians learning to identify problems before they shut down production. We also discuss some of the larger lessons from this 25-year experiment. Why does lasting educational change take so long? Why do reforms often fail when they're imposed from the top? What happens when teachers are treated as creative professionals and given the freedom to experiment, fail, reflect, and try again? And how can ideas move among individuals, schools, workplaces, and communities until learning becomes a characteristic of an entire society? Blikstein and Fields argue that successful innovation isn't about finding a model that works and copying it everywhere. It's about giving people the agency and support to adapt ideas to their own circumstances—and to learn their way through the problems they encounter. Paulo Blikstein is a professor at Columbia University whose research focuses on constructionism, educational technology, making, and computing education.  Deborah Fields is a learning scientist whose research explores learning across settings, with particular attention to identity, culture, technology, and participation. Their new book is The Society That Learns. You can watch the full YouTube interview as part of The Science of Learning YouTube playlist. Music by license from SoundStripe: "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright ©️ 2026 Keith Sawyer

    Can an Entire Society Learn? Educational Reform in Thailand with Paulo Blikstein and Deborah Fields

  4. Aug 25

    Roger Azevedo: Why AI Isn't Enough—The Science of Metacognition and Learning

    Artificial intelligence is transforming education—but can an AI tutor really help students learn? In this episode of The Science of Learning, Keith Sawyer talks with learning scientist Roger Azevedo, one of the world's leading researchers in artificial intelligence, metacognition, and self-regulated learning. Watch the video interview on YouTube: https://youtu.be/wYQ3r6iE-l0 Roger explains why simply giving students access to ChatGPT or another powerful AI system is not enough. Effective learning depends on understanding what's happening inside the learner's mind. Roger describes decades of research developing intelligent tutoring systems that adapt to individual learners by monitoring their knowledge, attention, motivation, and emotions. He explains how AI can become a true learning partner by building a cognitive model of each student and providing personalized guidance in real time.  They also discuss:  Why today's generative AI still lacks a true model of the learner What metacognition is—and why it is essential for effective learning How students can become better self-regulated learners Multimodal learning analytics, including eye tracking and facial-expression analysis AI tutors that adapt instruction to each student's needs Simulated learners and digital twins as the future of educational technology How AI may eventually help students understand their own thinking Whether you're a teacher, student, researcher, or simply interested in how AI will shape education, this conversation offers an insightful look at the future of learning—and why the human mind remains at the center of that future. Guest: Roger Azevedo, Professor, University of Central Florida Host: Keith Sawyer Watch the full video interview on YouTube: https://youtu.be/wYQ3r6iE-l0 Subscribe to the Substack newsletter: https://keithsawyer.substack.com The Science of Learning explores the latest research on how people learn, featuring conversations with the world's leading learning scientists, cognitive psychologists, and education researchers. Music by license from SoundStripe: "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright (c) 2026 Keith Sawyer

    Roger Azevedo: Why AI Isn't Enough—The Science of Metacognition and Learning

  5. Aug 11

    Janet Kolodner: How the Learning Sciences Began

    How did the learning sciences become a distinct field of research? What inspired scholars from psychology, education, cognitive science, and artificial intelligence to create an entirely new discipline devoted to understanding how people learn? In this episode of The Science of Learning, host Keith Sawyer talks with Janet Kolodner, one of the founders of the learning sciences. Watch the video interview on YouTube: https://youtu.be/8OEeAQbyo_Y  Janet shares the story of the field's origins, beginning with her pioneering work in artificial intelligence and case-based reasoning in the late 1970s and 1980s, and continuing through the founding of the Journal of the Learning Sciences, the first International Conference of the Learning Sciences, and the International Society of the Learning Sciences (ISLS). The conversation explores why traditional laboratory research could not fully explain learning in authentic settings, and how researchers came together to study learning as it occurs in classrooms, museums, communities, workplaces, and everyday life. Janet also discusses several of the field's most influential ideas, including cognitive apprenticeship, design-based research, funds of knowledge, Learning by Design, project-based inquiry science, and the emerging field of learning engineering. Whether you're a researcher, educator, graduate student, or simply curious about how people learn, this episode offers a firsthand account of how one of today's most influential interdisciplinary fields was created—and where it is headed next. For more interviews with leading learning scientists, visit The Science of Learning YouTube playlist About Janet Kolodner Janet Kolodner is Professor Emerita at Georgia Tech and Boston College. She was the founding Editor-in-Chief of the Journal of the Learning Sciences, a co-founder of the International Society of the Learning Sciences (ISLS), and a pioneer of case-based reasoning, Learning by Design, project-based inquiry science, and learning engineering. Music by license from SoundStripe: "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright (c) 2026 Keith Sawyer

    Janet Kolodner: How the Learning Sciences Began

  6. Jul 28

    How Science Happens—Inside the 2026 International Society of the Learning Sciences Conference

    In this special documentary episode of The Science of Learning, I take you inside the 2026 International Society of the Learning Sciences (ISLS) conference at the University of California, Irvine. Watch the full video documentary on YouTube at this link Rather than focusing on technical research presentations, this documentary explores the human side of science—the conversations, friendships, creativity, and sense of community that make scientific discovery possible. You'll hear from many of the world's leading learning scientists as they reflect on why they come to ISLS, what learning means to them, and why collaboration across disciplines is essential for advancing our understanding of teaching and learning. The documentary explores four themes: Why learning scientists are motivated by curiosity and purpose How scientific communities are built through collaboration and connection Why interdisciplinary perspectives lead to new discoveries  How the arts and creativity are becoming an increasingly important part of learning sciences research Thank you to the International Society of the Learning Sciences, the conference organizers, and everyone who generously agreed to participate in this documentary. If you'd like to experience the visuals from the conference—including the campus, artwork, performances, and community that inspired this episode—you can also watch the full documentary on The Science of Learning YouTube podcast. Episode Topics The International Society of the Learning Sciences (ISLS) Educational research Cognitive science Interdisciplinarity Scientific collaboration Academic conferences Creativity and the arts Community in science Music by license from SoundStripe: "Miss Missy" by AFTERNOONZ "The Wild" by Alsever Lake "Cedar Sun" by Rest & Settle Copyright (c) 2026 Keith Sawyer

  7. Jun 30

    Why Students Don't Like School | A Conversation with Daniel Willingham

    Why do students find learning so difficult? According to cognitive psychologist Daniel Willingham, it's because the human mind isn't designed for thinking. Instead, our brains are designed to avoid thinking whenever possible by relying on memory, routines, and past experience. And yet, true learning requires and deep and effortful thinking. Watch the video interview on YouTube: https://youtu.be/DWSn3km6lCc In this episode of The Science of Learning, I sit down with Dan Willingham, professor of psychology at the University of Virginia and author of the influential book Why Don't Students Like School?, to explore what decades of cognitive science reveal about how people learn. We discuss why knowledge is the foundation of understanding, why background knowledge is essential for reading comprehension, and why teaching critical thinking can't be separated from building deep knowledge. Dan talks about curiosity, scientific thinking, creativity, and the relationship between knowledge and expertise. Our conversation dives into the really big questions: how students develop understanding and why learning is often more difficult than we expect. Most of all, this episode offers practical insights for teachers. Whether you're a teacher, professor, student, parent, or simply curious about how the mind works, this episode offers a fascinating introduction to the cognitive science of learning. About Daniel Willingham Dr. Willingham is Professor of Psychology at the University of Virginia. His research focuses on the application of cognitive psychology to K–16 education. He's the author of numerous influential books, including Why Don't Students Like School?, Outsmart Your Brain, When Can You Trust the Experts?, and The Reading Mind. About The Science of Learning For video interviews with leading researchers on learning, education, creativity, and cognitive science, subscribe to The Science of Learning YouTube playlist.   For audio interviews, you can find The Science of Learning on Spotify, Apple Podcasts, and all podcast platforms.   Copyright © 2026 Keith Sawyer

    Why Students Don't Like School | A Conversation with Daniel Willingham

  8. Jun 16

    How Great Teachers Help Students Figure Things Out for Themselves | Joe Krajcik

    How do students learn without the teacher simply giving them the answer? In this episode of The Science of Learning, Keith Sawyer talks with learning scientist Joe Krajcik about project-based learning, scientific modeling, curiosity, and the role of productive struggle in deep understanding. Watch the video interview on YouTube  Krajcik explains why lasting learning happens when students actively construct knowledge for themselves rather than memorizing facts or copying answers. Through carefully designed experiences, teachers can help students build models, ask meaningful questions, test ideas, and connect new concepts to what they already know. The conversation explores: Why learning requires more than asking questions—it requires figuring out answers How teachers provide scaffolding without taking over the learning process The role of firsthand experiences in building understanding Why scientific models are powerful tools for explanation and prediction How students learn to make claims supported by evidence and reasoning The importance of curiosity and question asking in both learning and creativity Examples of project-based learning from elementary and high school science classrooms Along the way, Krajcik shares memorable examples involving squirrels, skateboards, water quality, chemistry, and the famous question: "How come I see so many squirrels, but I don't see any stegosaurus?" Learning happens when we build knowledge, not when we receive it. This episode explores how great teachers help students construct understanding that lasts. For more information Dr. Krajcik is a professor emeritus at Michigan State University and one of the leading researchers in project-based learning and science education. His work has helped shape contemporary approaches to inquiry-based science instruction and the Next Generation Science Standards. Dr. Krajcik's web site The Science of Learning is produced and hosted by Keith Sawyer.  Music by license from SoundStripe "Uptown Lovers Instrumental" by AFTERNOONZ "Miss Missy" by AFTERNOONZ "What's the Big Deal" by Ryan Saranich Copyright (c) 2026 Keith Sawyer

    How Great Teachers Help Students Figure Things Out for Themselves | Joe Krajcik
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The Science of Learning explores what research tells us about how people learn—and how we can learn better. In each episode, Dr. Keith Sawyer, the Morgan Distinguished Professor of Educational Innovations at the University of North Carolina at Chapel Hill, and the editor of The Cambridge Handbook of the Learning Sciences, talks with leading researchers about the science of learning. These conversations go beyond myths and trends to focus on evidence-based insights from cognitive science, neuroscience, and the learning sciences. The podcast examines how learning really works: from memory and attention to social interaction, embodiment, and the design of learning environments. Episodes connect rigorous research to practical implications for teaching, education, and everyday life. Guests include many of the most influential scholars in the field, offering a rare opportunity to hear directly from the people shaping how we understand learning.

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