没有护的生成AI可能会损害学习:来自高中数学证据的证据
Hamsa Bastani1,2, Osbert Bastani3, Alp Sungu1
1Department of Operations, Information, and Decisions, Wharton School, University of Pennsylvania, Philadelphia, PA 19104.
概括
生成型人工智能工具可以提高性能,但如果用作拐杖,可能会损害学习. 保证的人工智能导师减轻负面的教育结果,保持长期的技能发展.
科学领域:
- 人工智能的人工智能
- 教育技术的教育技术
- 认知科学 认知科学
背景情况:
- 生成性AI (人工智能) 显示出提高生产力的潜力.
- 了解其对技能获取和学习的影响对于长期生产力至关重要.
- 生成性AI的错误性需要用户监督,强调有效的学习策略的重要性.
研究的目的:
- 调查生成性AI导师如何影响高中数学学习.
- 为了比较一个标准的生成AI接口与一个具有学习保障的接口的影响.
- 评估生成性AI工具使用的长期教育成果.
主要方法:
- 一个涉及近一千名高中数学学生的实地实验.
- 部署两个生成AI教师:一个标准的ChatGPT接口 (GPT基础) 和一个受保护的版本 (GPT教师).
- 分析学生的表现和学习成果,并没有生成人工智能访问,并在访问删除后.
主要成果:
- 生成型人工智能访问显著改善了学生的表现 (GPT基础的48%,GPT导师的127%).
- 删除生成人工智能访问导致比从未访问 (17%的GPT基数减少) 更糟糕的性能.
- 在GPT Tutor中的保障措施在很大程度上减轻了学习的负面影响,防止学生使用人工智能作为拐杖.
结论:
- 无限制的生成人工智能访问可能会对教育成果和技能学习产生负面影响.
- 精心设计生成性人工智能工具,结合学习保障,对于积极的教育影响至关重要.
- 决策者必须考虑人工智能设计,以确保技能保存和长期生产力.
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