Students’ use of generative artificial intelligence for proving mathematical statements

Abstract In this exploratory study, we investigate undergraduate students’ engagement with generative Artificial Intelligence (genAI) in proving mathematical statements. We selected six mathematical statements to conduct interviews with three students. We present the emergent framework, Students’ Interactive Proving Experience with AI (SIPE-AI), which explains the processes of students’ use of genAI in their proving and the factors influencing these processes. Our findings identify three factors that shape students’ use of genAI: conceptions of proof, conceptions of genAI, and ethical considerations. The results suggest a need to guide undergraduate students in critically engaging with genAI tools, rather than passively accepting their outputs. We also discuss the implications of these findings for enhancing undergraduate mathematics education by fostering informed and critical use of genAI in mathematical proving.

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Publication Details

Journal
ZDM
Published
2024-08-26
DOI
https://doi.org/10.1007/s11858-024-01629-0
Citations
26
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
20.26

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article

Students’ use of generative artificial intelligence for proving mathematical statements

Hyunkyoung Yoon, Jihye Hwang, Oh Nam Kwon, Kyeong Hah Roh et al.
26 citations
ZDM
Artificial Intelligence in Education
20.26
article

Students’ use of generative artificial intelligence for proving mathematical statements

Hyunkyoung Yoon, Jihye Hwang, Oh Nam Kwon, Kyeong Hah Roh, Kyung Won Lee
article en
26 citations

Abstract

Abstract In this exploratory study, we investigate undergraduate students’ engagement with generative Artificial Intelligence (genAI) in proving mathematical statements. We selected six mathematical statements to conduct interviews with three students. We present the emergent framework, Students’ Interactive Proving Experience with AI (SIPE-AI), which explains the processes of students’ use of genAI in their proving and the factors influencing these processes. Our findings identify three factors that shape students’ use of genAI: conceptions of proof, conceptions of genAI, and ethical considerations. The results suggest a need to guide undergraduate students in critically engaging with genAI tools, rather than passively accepting their outputs. We also discuss the implications of these findings for enhancing undergraduate mathematics education by fostering informed and critical use of genAI in mathematical proving.

ZDMVol. 56(7)
Seoul National University (KR), Arizona State University (US), California State Polytechnic University (US)
Seoul National University
Quality Education
Openalex Percentile: Top 1%
Artificial Intelligence in Education
20.26
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