Tens of millions of students now use some form of AI to learn—whether through extracurricular tutoring programs like Squirrel’s, through digital learning platforms like 17ZuoYe, or even in their main classrooms. (A Chinese version of the book is coauthored by Squirrel’s founder, Derek Li.)
Squirrel also opened a joint research lab with Carnegie Mellon University this year to study personalized learning at scale, then export it globally. A classroom, showing students on laptops an a teacher assisting, at Squirrel AI The first is tax breaks and other incentives for AI ventures that improve anything from student learning to teacher training to school management.
In the five years since it was founded, the company has opened 2,000 learning centers in 200 cities and registered over a million students—equal to New York City’s entire public school system. In October 2017, for example, a self-funded four-day study with 78 middle school students found that the system was better on average at lifting math test scores than experienced teachers teaching a dozen or so kids in a traditional classroom.
A teacher helping a student via video as part of Squirrel's new remote tutoring program. Every educational expert I spoke to for this story began by making the same point: to understand how AI could improve teaching and learning, you need to think about how it is reshaping the nature of work.
“There’s a difference between adaptive learning and personalized learning,” says Chris Dede, a professor at Harvard University in the Technology, Innovation, and Education Program. Fifteen years ago, he founded his first ed-tech company in China after getting his PhD from the MIT Media Lab. Inspired by his experience in grad school, he focused on building tools for learning English. Students learn English in Alo7's intelligent classroom.
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