使用大型语言模型来支持预服务教师的数学推理 - - 一项探索性研究,使用ChatGPT作为创建几何数学证明的工具
Frederik Dilling1, Marc Herrmann1
1Mathematics Education, Department of Mathematics, University of Siegen, Siegen, Germany.
Frontiers in artificial intelligence
|November 7, 2024
概括
这项研究探讨了像ChatGPT这样的大型语言模型 (LLM) 可以如何帮助预服务数学教师进行几何证明. 调查结果显示,教师的经验有限,对LLM的理解肤浅,这影响了它们在数学证明构建中的使用.
科学领域:
- 数学教育教育 数学教育
- 教育中的人工智能
背景情况:
- 研究大型语言模型 (LLM) 在教师培训中的作用.
- 了解预服务教师与数学任务的AI工具的互动.
研究的目的:
- 探索ChatGPT在支持初等教育数学教师构建几何证明方面的潜力.
- 在乐器起源的框架内,分析教师与LLM的先前经验,信念和互动.
主要方法:
- 服务前教师与ChatGPT互动的定性内容分析.
- 利用仪器起源的理论框架来分析用户的经验和信仰.
- 根据先前的经验,信念和交互模式,开发诱导类别.
主要成果:
- 预服务教师报告说,他们以前对LLM的经验有限,主要是用于非数学应用.
- 大多数参与者表现出对LLM运行原则的肤浅知识和常见误解.
- 分析揭示了各种提示策略,从单个查询到复杂的聊天交互,并确定了一些特定于数学的模式.
结论:
- 预服务教师对LLM的有限理解和经验对其有效融入数学教师培训提出了挑战.
- 需要进一步的研究来开发教学策略,利用LLMs来完成复杂的数学任务,例如证明构造.
- 该研究强调了解决误解和为教育工作者建立关于人工智能工具的基础知识的重要性.
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