The Generative AI Learning Penalty: Evidence from Chinese Secondary Education
Using 30 months of panel data on 26,811 Chinese students in grades 7-12, we study how generative AI affects homework productivity and learning. The data combine monthly closed-book exams, high-school and college entrance exams, and homework scores and completion time across nine subjects. We exploit staggered AI adoption in a difference-in-differences design. AI adoption raises homework scores by 18% and reduces completion time by 30%, but lowers monthly exam scores by 20% within six months. High-stakes entrance-exam scores fall by 18 and 24%, with the full penalty emerging only after about two years. The losses are largest in social science subjects, followed by STEM and languages, and are especially large for junior students, high-achieving students, and boys. The learning losses are concentrated among roughly 80% of AI users whose behavior is consistent with homework outsourcing, as indicated by exceptionally short homework completion time coupled with high homework scores. AI users who maintain similar homework completion time as non-AI users experience small learning losses.
Edit: moving my comment up here
Just in case as it’s formatted a bit weirdly
X-Axis: Homework scores
Y-Axis: Exam scores
The values aren't a score. They normalized the average score to 100 for non-AI in both homework and exam. Then noted the deviation. People using AI to get very high scores (130% of the average) were tank the test (40% of the average) six months later.
Thanks. Before my edit was my original comment before I realized their was a PDF of the paper available. Should have answered my own question. Appreciated.