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A teacher and two primary pupils compare equivalent fraction bars on a worksheet beside a tablet practice activity.
期刊论文2026
期刊论文 194

Computer-assisted learning in the real world: How Khan Academy influences student math learning

Taryn Eames, Emma Brunskill, Bogdan Yamkovenko, Kodi Weatherholtz, Philip Oreopoulos

Proceedings of the National Academy of Sciences

A large United States study links Khan Academy use with mathematics progress across roughly 214,000 students. Its observational design uses changes in classmates’ usage and extensive statistical controls, rather than random assignment. Average exposure was modest, and higher prior achievers appeared to benefit more. The findings highlight implementation and access to practice, while leaving uncertainty about causation. They concern established computer-assisted learning and should not be read as evidence for generative-AI chatbots.

Mathematics EducationAdaptive LearningLearning Analytics
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AIEDHKAI in Education Hub of Knowledge

AIEDHK 是面向 AI in Education 研究、开发与负责任学习创新的多语言知识枢纽。

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