Gen AI in Proof-based Math Courses: A Pilot Study
Not on the map. Why?
Abstract (arXiv)
With the rapid rise of generative AI in higher education, understanding how students use AI is increasingly important. This exploratory study examines student use and perceptions of generative AI across three proof-based undergraduate mathematics courses: a first-semester abstract algebra course, a topology course, and a second-semester abstract algebra course. In each case, course policy permitted some use of generative AI. Drawing on survey responses and student interviews, we analyze how students engaged with AI tools as well as their perceptions of generative AI's usefulness, accuracy and limitations.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 51 references that are in the map. First posted on arXiv 16 Sep 2025.
Builds on
6 of 51 references.
References · 6
- 2024Large Language Models for Mathematical Reasoning: Progresses and Challengescited by 284
- 2023Mathematical Capabilities of ChatGPTcited by 268
- 2023GPT detectors are biased against non-native English writerscited by 178
- 2023Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Educationcited by 41
- 2024GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Educationcited by 14
- 2024Autograding Mathematical Induction Proofs with Natural Language Processingcited by 4
Built on by
Not cited yet.