Assessment of Evolving Large Language Models in Upper Secondary Mathematics
On the map: LLM reasoning → Mathematical reasoning
Abstract (arXiv)
Large language models (LLMs) have shown increasing promise in educational settings, yet their mathematical reasoning has been considered evolving. This study evaluates the mathematical capabilities of various LLMs using the Finnish matriculation examination, a high-stakes digital test for upper secondary education. Initial tests yielded moderate performance corresponding to mid-range grades, but later evaluations demonstrated substantial improvements as the language models evolved. Remarkably, some models achieved near-perfect or perfect scores, matching top student performance and qualifying for university admission. Our findings highlight the rapid advances in the mathematical proficiency of LLMs and illustrate their potential as underlying tools to support learning and teaching in a variety of ways.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Mathematical reasoning, one of 17 directions in LLM reasoning. Builds on 13 of its 37 references that are in the map. First posted on arXiv 15 Apr 2025.
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13 of 37 references.
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- 2024GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models7 Oct
- 2024Large Language Models for Mathematical Reasoning: Progresses and Challenges31 Jan
- 2023Investigating the Effectiveness of ChatGPT in Mathematical Reasoning and Problem Solving: Evidence from the Vietnamese National High School Graduation Examination10 Jun
- 2023MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems23 May
Other references · 9
- 2023GPT-4 Technical Reportcited by 18,396
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- 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
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- 2023A Comprehensive Overview of Large Language Modelscited by 648
- 2023Mathematical Capabilities of ChatGPTcited by 268
- 2022The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialoguescited by 79
- 2025Brief analysis of DeepSeek R1 and its implications for Generative AIcited by 10
- 2024Beyond Text-to-Text: An Overview of Multimodal and Generative Artificial Intelligence for Education Using Topic Modelingcited by 6
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- 2025Evaluating Large Language Models on the 2026 Korean CSAT Mathematics Exam: Measuring Mathematical Ability in a Zero-Data-Leakage Setting
- 2024From Next-Token to Mathematics: The Learning Dynamics of Mathematical Reasoning in Language Models
- 2026Large Language Models for Math Education in Low-Resource Languages: A Study in Sinhala and Tamil
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- 2025A Report on the llms evaluating the high school questions