Using large language models to support pre-service teachers mathematical reasoning-an exploratory study on ChatGPT as an instrument for creating mathematical proofs in geometry.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2024-10-23 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1460337
Frederik Dilling, Marc Herrmann
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引用次数: 0

Abstract

In this exploratory study, the potential of large language models (LLMs), specifically ChatGPT to support pre-service primary education mathematics teachers in constructing mathematical proofs in geometry is investigated. Utilizing the theoretical framework of instrumental genesis, the prior experiences of students with LLMs, their beliefs about the operating principle and their interactions with the chatbot are analyzed. Using qualitative content analysis, inductive categories for these aspects are formed. Results indicate that students had limited prior experiences with LLMs and used them predominantly for applications that are not mathematics specific. Regarding their beliefs, most show only superficial knowledge about the technology and misconceptions are common. The analysis of interactions showed multiple types of in parts mathematics-specific prompts and patterns on three different levels from single prompts to whole chat interactions.

使用大型语言模型支持职前教师进行数学推理--以 ChatGPT 为工具创建几何数学证明的探索性研究。
在这项探索性研究中,我们调查了大型语言模型(LLM),特别是 ChatGPT 在支持小学数学教师职前几何数学证明建构方面的潜力。利用工具性创生理论框架,分析了学生使用 LLMs 的先前经验、他们对操作原理的信念以及他们与聊天机器人的互动。通过定性内容分析,对这些方面进行了归纳分类。结果表明,学生以前使用 LLM 的经验有限,而且主要用于非数学应用。至于他们的观念,大多数人对该技术的了解都很肤浅,误解也很普遍。对互动的分析表明,在从单一提示到整个聊天互动的三个不同层面上,存在多种类型的数学提示和模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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