Students finish AI-friendly math problems faster, but they seem to learn less from them.

The researchers studied 3.2 million ALEKS math learning records across 10 years to see what changed after ChatGPT became available.

Finishing faster is not automatically learning more efficiently, because math practice builds knowledge through the friction of choosing a representation, testing a step, making an error, and correcting it.

When a chatbot supplies the path, the student may still submit the answer, but the mind has skipped the work that turns exposure into memory.

They compare word problems, which students can easily paste into an AI chatbot, with graph problems, which are harder to hand off because they require visual work inside the platform.

After ChatGPT, high school and college students spent much less time on the AI-friendly word problems, while younger students showed smaller or no change.

This time drop disappeared when tests were proctored, which suggests the faster work was not just students getting better or the platform changing.

The learning cost showed up later: on proctored retention questions, students became about 25% less likely to answer AI-friendly items correctly, even though they looked better on non-proctored items where AI could still help.

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Paper Link – arxiv. org/abs/2605.21629

Paper Title: "Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build"