Exploring the Role of Generative Artificial Intelligence in Transforming Mathematics Teaching and Learning: A Systematic Mapping Review

Authors

  • Nur Syaza Afrina Muhamad Sani International Islamic University Malaysia image/svg+xml
  • Muhammad Akmal Azri Omar International Islamic University Malaysia image/svg+xml
  • Mohamad Ridhuan Abdullah International Islamic University Malaysia image/svg+xml

DOI:

https://doi.org/10.11113/itlj.v10.256

Keywords:

Generative artificial intelligence, Large language models, Mathematics education, Systematic mapping review, Educational technology

Abstract

Recent advances in generative artificial intelligence (GenAI), in particular, large language models (ChatGPT, Gemini, Claude, etc.) have reshaped digital innovation in education. While prior studies have examined specific classroom applications, few studies to date have provided a comprehensive mapping of the empirical research landscape across tools, educational levels, mathematical domains, research designs, and geographical distribution, leaving structural patterns and research gaps insufficiently synthesized. This paper presents a systematic mapping review on the integration of GenAI in mathematics education. Using the PRISMA framework, studies published between 2022 and 2025 (final search conducted in December 2025) were retrieved from Web of Science and Scopus, complemented by a full-text search in ScienceDirect. After screening and eligibility procedure, 30 peer-reviewed empirical articles were included for analysis. The mapping results indicate that ChatGPT is the most frequently examined tool, with research predominantly concentrated at the tertiary education level and focused largely on algebra and calculus topics. Most studies employed qualitative or mixed-method designs, and the majority were conducted in Asia and Europe, reflecting emerging but uneven global research distribution. Thematic analysis was employed to identify commonly reported pedagogical applications, including problem-solving support, content generation, scaffolding, lesson planning, and differentiated instruction, as well as frequently reported challenges such as conceptual errors, limitations in abstract and spatial reasoning, and variability in output quality across platforms. Rather than evaluating effectiveness, this review provides an overview of research trends, identifies concentrations and gaps in the literature, and highlights directions for future empirical and theoretical work on GenAI-supported mathematics education.

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Published

10-07-2026

Issue

Section

Articles

How to Cite

Exploring the Role of Generative Artificial Intelligence in Transforming Mathematics Teaching and Learning: A Systematic Mapping Review. (2026). Innovative Teaching and Learning Journal, 10(2), 155-174. https://doi.org/10.11113/itlj.v10.256