On the robustness of ChatGPT in teaching Korean Mathematics
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Abstract (arXiv)
ChatGPT, an Artificial Intelligence model, has the potential to revolutionize education. However, its effectiveness in solving non-English questions remains uncertain. This study evaluates ChatGPT's robustness using 586 Korean mathematics questions. ChatGPT achieves 66.72% accuracy, correctly answering 391 out of 586 questions. We also assess its ability to rate mathematics questions based on eleven criteria and perform a topic analysis. Our findings show that ChatGPT's ratings align with educational theory and test-taker perspectives. While ChatGPT performs well in question classification, it struggles with non-English contexts, highlighting areas for improvement. Future research should address linguistic biases and enhance accuracy across diverse languages. Domain-specific optimizations and multilingual training could improve ChatGPT's role in personalized education.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 24 references that are in the map. First posted on arXiv 17 Feb 2025.
Builds on
6 of 24 references.
References · 6
- 2024MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?cited by 586
- 2023Mathematical Capabilities of ChatGPTcited by 268
- 2024Enhancing Large Vision Language Models with Self-Training on Image Comprehensioncited by 70
- 2024MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Modelscited by 70
- 2023ChatGPT for Programming Numerical Methodscited by 26
- 2023ChatGPT for Computational Topologycited by 3
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