Analysis of generative AI’s mathematical problemsolving performance: Focusing on ChatGPT 4, Claude 3 Opus, and Gemini Advanced

As digitalAI-based teaching and learning is emphasized, discussions on the educational use of generative AI are becoming more active.This study analyzed the mathematical performance of ChatGPT 4, Claude 3 Opus, and Gemini Advanced on solving examples and problems from five first-year high school math textbooks.As a result of examining the overall correct answer rate and characteristics of each skill for a total of 1,317 questions, ChatGPT 4 had the highest overall correct answer rate of 0.85, followed by Claude 3 Opus at 0.67, and Gemini Advanced at 0.42.By skills, all three models showed high correct answer rates in 'Find functions' and 'Prove' , while relatively low correct answer rates in 'Explain' and 'Draw graphs' .In particular, in 'Count' , ChatGPT 4 and Claude 3 Opus had a correct answer rate of 1.00, while Gemini Advanced was low at 0.56.Additionally, all models had difficulty in explaining using Venn diagrams and creating images.Based on the research results, teachers should identify the strengths and limitations of each AI model and use them appropriately in class.This study is significant in that it suggested the possibility of use in actual classes by analyzing the mathematical performance of generative AI.It also provided important implications for redefining the role of teachers in mathematics education in the era of artificial intelligence.Further research is needed to develop a cooperative educational model between generative AI and teachers and to study individualized learning plans using AI.