Morpheus

From The Future of Everything

The future of learning

Published
March 27, 2026
Length
36:16
Starts at
22:29

Audio is streamed from the publisher.

Chapters

Read from the show notes

  1. 0:00 **Introduction**
  2. 3:16 **Path into Learning Science**
  3. 3:47 **The Science of Learning**
  4. 4:42 **Training Educators**
  5. 5:17 **The Research to Practice Gap**
  6. 6:43 **Technology Supporting Teachers**
  7. 9:00 **The Open Learning Initiative (OLI)**
  8. 11:08 **Learning with OLI**
  9. 13:14 **Building OLI Across Disciplines**
  10. 14:36 **The Accelerated Learning Study**
  11. 18:02 **Learning Science at Amazon**
  12. 22:29 **Research as a Feedback Loop**
  13. 24:49 **The Importance of Infrastructure**
  14. 25:37 **Predictive AI for Learning Science**
  15. 28:22 **Generative AI as a Learning Interface**
  16. 31:01 **The Myth of Learning Styles**
  17. 33:30 **Future In a Minute**
  18. 35:24 **Conclusion**

Not from the publisher — times may be approximate.

[https://ed.stanford.edu/faculty/cthille"]( Candace Thille is an authority in learning science, educational technology, and AI-enabled learning environments. She is closing the two-way gap between the science of learning research and the hands-on practice of instruction to help students learn better. Timely and targeted feedback with the opportunity to apply that feedback is critical to learning, Thille says, and this is an area where AI supporting humans excels. She imagines a day in the not-too-distant future when human educators and AI-enabled assistants unite to help students learn faster and better than ever before. Learning is not a spectator sport, and AI can help us engage with learners – and educators – in new ways, Thille tells host [https://profiles.stanford.edu/russ-altman"]( Russ Altman on this episode of Stanford Engineering’s _The Future of Everything_ podcast. _Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to_ [_thefutureofeverything@stanford.edu_](mailto:thefutureofeverything@stanford.edu)_._ **Episode Reference Links:** - Stanford Profile: [https://profiles.stanford.edu/candace-thille"]( Candace Thille **Connect With Us:** - Episode Transcripts >>> [https://engineering.stanford.edu/magazine/collection/future-everything-podcast"]( The Future of Everything Website - Connect with Russ >>> [https://www.threads.net/@russbaltman"]( Threads / [https://bsky.app/profile/rbaltman.bsky.social"]( Bluesky / [https://mastodon.social/@rbaltman"]( Mastodon - Connect with School of Engineering >>> [https://twitter.com/stanfordENG"]( Twitter/X / [https://www.instagram.com/stanfordeng/"]( Instagram / [https://www.linkedin.com/school/stanford-university-school-of-engineering/posts/?feedView=all&viewAsMember=true"]( LinkedIn / [https://www.facebook.com/stanford.engineering/"]( Facebook **Chapters:** (00:00:00) **Introduction** Russ Altman introduces guest Candace Thille, a professor of education at Stanford University. (00:03:16) **Path into Learning Science** How Candace became interested in improving how people learn. (00:03:47) **The Science of Learning** An overview of the field and why it’s still developing. (00:04:42) **Training Educators** How learning science is applied in teacher education. (00:05:17) **The Research to Practice Gap** Why insights from classrooms rarely feed back into research. (00:06:43) **Technology Supporting Teachers** Using AI and other technological tools to enhance teaching. (00:09:00) **The Open Learning Initiative (OLI)** The origins of one of the first large-scale digital learning systems. (00:11:08) **Learning with OLI** How feedback and structured practice improved student outcomes. (00:13:14) **Building OLI Across Disciplines** The collaboration between researchers, instructors, and engineers. (00:14:36) **The Accelerated Learning Study** Evidence that students can learn faster without sacrificing outcomes. (00:18:02) **Learning Science at Amazon** Applying learning science research to workplace education. (00:22:29) **Research as a Feedback Loop** Why teaching practice should continuously inform research. (00:24:49) **The Importance of Infrastructure** Using captured learning data to improve instruction at scale. (00:25:37) **Predictive AI for Learning Science** The applications of older AI models in learning science research. (00:28:22) **Generative AI as a Learning Interface** How generative AI can make education more accessible. (00:31:01) **The Myth of Learning Styles** The misconception that most people have different learning styles. (00:33:30) **Future In a Minute** Rapid-fire Q&A: new tools, data infrastructure, and supporting learners. (00:35:24) **Conclusion** **Connect With Us:** Episode Transcripts >>> [The">https://engineering.stanford.edu/magazine/collection/future-everything-podcast">The]( >> [Threads]( https://www.threads.net/@russbaltman">Threads / [Bluesky]( https://bsky.app/profile/rbaltman.bsky.social">Bluesky / [Mastodon]( https://mastodon.social/@rbaltman">Mastodon Connect with School of Engineering >>>[Twitter/X]( https://twitter.com/stanfordENG">Twitter/X / [Instagram]( https://www.instagram.com/stanfordeng/">Instagram / [LinkedIn]( https://www.linkedin.com/school/stanford-university-school-of-engineering/posts/?feedView=all&viewAsMember=true">LinkedIn / [Facebook]( https://www.facebook.com/stanford.engineering/">Facebook Hosted by Simplecast, an AdsWizz company. See [pcm.adswizz.com]( https://pcm.adswizz.com">pcm.adswizz.com for information about our collection and use of personal data for advertising.