Stanford Psychology Podcast 172 - Julia Chatain: Embodied Learning and Educational Technology in Mathematics and Beyond (REAIR)
Mar 20, 2026
Julia Chatain, a computer scientist and learning scientist specializing in embodied learning and educational tech, discusses making abstract math concrete with VR, AR, robots and low-tech manipulatives. She covers measuring learning through movement, scalable low-tech alternatives, co-design with teachers and students, and AI-generated interactive exercises. The conversation highlights interdisciplinary teamwork and FELT’s focus on accessibility and scalability.
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Use Tangible And Mixed Reality Tools For Concreteness
- Use physical, hybrid, or VR representations to make abstract math concepts tangible for learners.
- Chatain lists simple manipulatives, augmented reality overlays, robots, and VR with hand tracking as concrete options depending on scale and cost.
Gestures Reveal Early Learning Hidden By Tests
- Traditional written post-tests miss early signs of learning expressed through gestures and movement.
- Chatain suggests using automatic movement analysis (e.g., AI on hand gestures) to capture preliminary learning before written mastery appears.
Solve Policy And Logistics Before Scaling Movement Learning
- Anticipate cultural, workload, and logistic barriers when introducing movement-based learning in classrooms.
- Chatain emphasizes policy-level support, teacher workload limits, and classroom layout changes as prerequisites for scale.