AI in mathematics education: Potential ranging from automation to personalized learning

Alifia Kania Ramadhani; Iqbal Ramadani

doi:10.32332/46xc9p64

Authors

Alifia Kania Ramadhani Universitas Islam Negeri Sunan Kalijaga
Iqbal Ramadani Universitas Islam Negeri Sunan Kalijaga

DOI:

https://doi.org/10.32332/46xc9p64

Keywords:

artificial intelligence, mathematics education, literature review, learning innovation, education technology

Abstract

The rapid development of artificial intelligence (AI) is reshaping many aspects of education, yet its meaningful contribution to mathematics instruction and student learning outcomes remains underexplored. Understanding how AI can enhance mathematical thinking, problem-solving, and personalized learning is critical in preparing students for future competencies. One of the challenges in learning mathematics is how to make it relevant to the times. One emerging approach was using artificial intelligence (AI) in mathematics education. Based on a literature review, this study aimed to explore and describe the potential of artificial intelligence (AI) in mathematics education. The method used was a literature review with a narrative design. Literature searches were conducted through reputable international sites such as Scopus, ScienceDirect, Springer, and World Scientific, with English keywords and years from 2015 to 2025. The collected literature was thematically analyzed to identify key themes such as AI usage trends, AI development potential, and implementation challenges. The results indicated that AI was increasingly used in mathematics education, particularly in various AI-assisted instructional tasks. Further potential in AI shows promise in personalizing learning and automating tasks, though challenges remain. In conclusion, AI is promising to transform mathematics education through adaptive, individualized, and data-informed learning approaches. However, its success depended on careful planning, teacher readiness, ethical frameworks, and alignment with educational goals and local contexts. These findings underscored the need for further research and context-specific development to ensure AI's effective and equitable integration into mathematics learning environments.

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