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ORIGINAL RESEARCH article

Front. Artif. Intell.
Sec. AI for Human Learning and Behavior Change
Volume 7 - 2024 | doi: 10.3389/frai.2024.1460337
This article is part of the Research Topic Generative AI in Education View all 9 articles

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

Provisionally accepted
Marc Herrmann Marc Herrmann *Frederik Dilling Frederik Dilling
  • University of Siegen, Siegen, Germany

The final, formatted version of the article will be published soon.

    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 it 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.

    Keywords: ChatGPT, mathematics education, Mathematical proofs, Teacher Education, Generative AI, Large Language Model

    Received: 05 Jul 2024; Accepted: 14 Oct 2024.

    Copyright: © 2024 Herrmann and Dilling. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Marc Herrmann, University of Siegen, Siegen, Germany

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.