How AI Adaptive Technology can upgrade Education
summary
Squirrel AI Learning builds an adaptive engine that maps nano-sized knowledge components with a multi-dimensional probabilistic knowledge state model plus multimodal integrated behavioral analysis and NLP, uses facial, transdermal and EEG signals and a virtual personal assistant for inner-loop tutoring, and runs outer-loop sequencing via knowledge graphs. Deployed across 1,700 Chinese learning centers, randomized trials (18+ studies, four shown) report higher test gains, faster mastery and better engagement versus traditional classes or small-group tutoring, demonstrating scalable one-on-one personalization.
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chapters (28)
- 0:00Intro
- 0:26Dr KPs background
- 1:18Why AI for education
- 1:29How technology can impact education
- 3:50Passive learning vs active learning
- 4:50Focus on the learner
- 5:38Revolution of education method
- 7:04Personalized Adaptive Teaching
- 8:26How do we implement AI
- 10:27We are not alone
- 10:45B2B model
- 14:10AI based adaptivity
- 15:06What students need to learn
- 15:20Individual differences
- 16:23Personalized content recommendation
- 17:07AI engine
- 17:35Instructional Framework
- 18:42Continuous formative assessment
- 19:19Outer loop adaptivity
- 19:54Virtual Personal Assistant
- 21:00Research Areas
- 22:22How does it work
- 24:14Currently in China
- 24:35Are we getting there
- 25:26Continuous data driven improvement
- 26:04Research partners
- 26:28Small data
- 27:29QA
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