Generative AI in mathematics education: analysing student performance and perceptions over three academic years

This study presents an approach in which generative AI (GenAI) chatbots are used to assist students in a problem-solving task resulting in a mathematical essay, introduced in the academic year 2022/2023 in a higher education mathematics course, and continued with in 2023/2024. We compared students' results from these two years with the results from 2021/2022, when GenAI was not part of the task, using Kruskal-Wallis and Dunn tests. The total sample included 966 students. The 2022/2023 results (GenAI introduced) differed significantly from the other two years, with students being less successful. Conversely, 2023/2024 (GenAI standard) showed the best student results and no significant difference from 2021/2022 (no GenAI). In all the three years, results in the problem-solving essay correlated with success in previous formative and summative assessments. Student feedback highlighted advantages and disadvantages of interactions with GenAI, revealing a tendency to utilise GenAI more for theoretical than practical tasks.

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Publication Details

Journal
International Journal of Technology Enhanced Learning
Published
2025-12-17
DOI
https://doi.org/10.1504/ijtel.2026.150520
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Generative AI in mathematics education: analysing student performance and perceptions over three academic years

International Journal of Technology Enhanced Learning
AI in Service Interactions
article

Generative AI in mathematics education: analysing student performance and perceptions over three academic years

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Abstract

This study presents an approach in which generative AI (GenAI) chatbots are used to assist students in a problem-solving task resulting in a mathematical essay, introduced in the academic year 2022/2023 in a higher education mathematics course, and continued with in 2023/2024. We compared students' results from these two years with the results from 2021/2022, when GenAI was not part of the task, using Kruskal-Wallis and Dunn tests. The total sample included 966 students. The 2022/2023 results (GenAI introduced) differed significantly from the other two years, with students being less successful. Conversely, 2023/2024 (GenAI standard) showed the best student results and no significant difference from 2021/2022 (no GenAI). In all the three years, results in the problem-solving essay correlated with success in previous formative and summative assessments. Student feedback highlighted advantages and disadvantages of interactions with GenAI, revealing a tendency to utilise GenAI more for theoretical than practical tasks.

International Journal of Technology Enhanced LearningVol. 18(1)
University of Zagreb (HR)
Quality Education
Openalex Percentile: Top 19%
AI in Service Interactions
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Generative AI in mathematics education: analysing student performance and perceptions over three academic years · International Journal of Technology Enhanced Learning (2025) | TGRS Research Map | TGRS