Sungu, Lira and Duckworth, “Generative AI Can Harm Teaching”
In a randomized field experiment across a chain of middle and high schools in Turkey, giving teachers a generative-AI support tool reduced students’ intrinsic motivation by 0.11 standard deviations. Average academic performance did not change, but students taught by lower-performing teachers experienced significant declines in both performance and confidence, showing that a tool that makes lesson preparation easier for teachers does not automatically improve the student experience.
AI support improved the teacher workflow without improving average achievement and produced measurable student-side harms.
Why it matters
Most participating teachers used the tool to create lecture materials, syllabi, and exercises. The result exposes a principal-agent problem in AI-assisted education: the person receiving the productivity benefit is not necessarily the person bearing the learning cost.
The uneven performance effect also matters. A neutral average can conceal greater harm where teaching quality is already weaker, making implementation support and student-centered evaluation essential before broad deployment.
Primary trail
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