# 学生完成AI友好型数学题更快，但学到的似乎更少

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-06-01 08:08
- AIHOT 分数：64
- AIHOT 链接：https://aihot.virxact.com/items/cmpuh6mci03okslagzsiz1xba
- 原文链接：https://x.com/rohanpaul_ai/status/2061238295603122262

## AI 摘要

研究分析了跨越10年的320万条ALEKS数学学习记录，发现自ChatGPT可用后，学生完成“AI友好”数学题（如单词题）的速度显著变快，但这并非意味着学得更好。研究指出，数学练习通过选择方法、试错和修正的过程构建知识，而当AI直接提供路径时，学生可能跳过了这个关键心智过程。关键证据是，在有监考的测试中，学生答对这类AI友好题目的可能性下降了约25%，表明更快的完成速度是以牺牲知识保留为代价的。论文链接：arxiv.org/abs/2605.21629。

## 正文

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"