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.

https://cepr.org/publications/dp21577

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