生成型人工智能和ChatGPT能否打破人类在数学上的优势,并重塑认知要求高的解决问题的能力?
1Department of Mathematics Education, Faculty of Education, Nevsehir Hacı Bektas Veli University, 50300 Nevsehir, Türkiye.
Journal of Intelligence
|April 25, 2025
概括
像ChatGPT-4o和GPT-4这样的生成人工智能工具在数学评估中表现强,经常超过学生的成绩. 虽然它们通常随着认知需求的提高而得到改善,但这种效应在12年级水平上不那么明显.
科学领域:
- 人工智能的人工智能
- 认知科学 认知科学
- 教育评估的教育评估
背景情况:
- 生成性AI工具越来越多地被用于认知支持.
- 了解AI对解决问题和学习的影响至关重要.
- 国家教育进步评估 (NAEP) 数学评估为学生的成绩提供了一个基准.
研究的目的:
- 评估聊天GPT-4o和GPT-4在NAEP数学评估中的表现.
- 分析与认知复杂性和需求相关的AI性能.
- 将AI能力与不同年级的学生表现进行比较.
主要方法:
- 根据认知复杂度,分析了60个NAEP数学评估任务.
- 聊天GPT-4o和GPT-4生成了对这些任务的响应.
- 人工智能反应使用NAEP的标准得分.
- 用学生平均分数和项目智能响应百分比来分析绩效.
主要成果:
- 聊天GPT-4o和GPT-4在单个NAEP数学项目中表现优于大多数学生.
- 较高的认知需求与需要更高的绩效得分来正确回答相关.
- 这一趋势在四年级,八年级和十二年级都是一致的.
结论:
- 生成型人工智能模型在数学问题解决方面显示出显著的潜力.
- 人工智能表现显示对认知需求的敏感性,尽管有年级级别的变化.
- 需要进一步的研究来了解人工智能与高等教育层面的复杂认知任务的微妙相互作用.
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