
Why do we cram for an exam only to forget everything a week later? And why is applying knowledge in a new context - transfer - so incredibly difficult?
In this essential episode, host Rudi Adigbli speaks with Professor Manu Kapur (Learning Sciences & Higher Education at ETH Zurich), who shares two decades of research and his groundbreaking learning model: Productive Failure.
We break down the three major problems in learning (Retention, Understanding, and Transfer) and reveal why failure, when designed correctly, is the key to deep learning and creativity. Professor Kapur also details how his startup, LearnPF, is harnessing Generative AI to scale this robust pedagogical model and transform education.
In this episode, you will learn:
[00:00] Introduction & Prof. Kapur’s Five Careers
[03:27] The Three Major Problems in Learning (Retention, Understanding, Transfer)
[09:04] What is Productive Failure?
[14:48] Cognitive Activation: Why Struggle is Better Than Listening
[20:00] Contextual Learning: The Home Advantage Effect in Memory
[24:59] Encoding Strategies & The Working Memory Bottleneck
[27:49] Hacking Emotions: How Wonder, Awe, and Frustration Drive Attention
[34:43] LearnPF: Training Generative AI on a Robust Learning Model
[44:07] The Future of Education: Fighting Unproductive Success with AI
Join the Journey:
👉 Read the full episode summary on my Substack: [Substack]
👉 Join The ReeShaper Circle to connect with others shaping the neurotech industry: [ReeShaper Circle]
#ProductiveFailure #LearningScience #Education #AIinEducation #LearningTheory #CognitiveScience #TransferLearning #Retention #MemoryHacks #ETHZurich #LearnPF #GenerativeAI #Neuroscience #ReeThink