AI in mathematics education: Potential ranging from automation to personalized learning
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Resumo
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.
Dados da obra
- Tipo
- Artigo
- Periódico
- LINEAR Journal of Mathematics Education, v. 6, n. 1, p. 85-99
- Ano
- 2025 (2025-07-02)
- Idioma
- en
- Palavras-chave
- artificial intelligence in education; mathematics education; personalized learning; adaptive learning; mathematical thinking; problem solving; teacher readiness; AI ethics; implementation barriers; educational equity
- Temas
- Resolução de Problemas
- DOI
- 10.32332/46xc9p64
- ISSN
- 2722-6913, 2722-760X
- Licença
- cc-by-sa
- Acesso
- Download disponível
- Fontes
- OpenAlex
- Na Biblioteca desde
- 01/10/2026 · verificada em 03/10/2026
Como citar
ABNT
RAMADHANI, Alifia Kania; RAMADANI, Iqbal. AI in mathematics education: Potential ranging from automation to personalized learning. LINEAR Journal of Mathematics Education, v. 6, n. 1, p. 85-99, 2025. DOI: https://doi.org/10.32332/46xc9p64.
APA
Ramadhani, A. K., & Ramadani, I. (2025). AI in mathematics education: Potential ranging from automation to personalized learning. LINEAR Journal of Mathematics Education, 6(1), 85-99. https://doi.org/10.32332/46xc9p64
BibTeX
@article{ramadhani2025,
author = {Ramadhani, Alifia Kania and Ramadani, Iqbal},
title = {AI in mathematics education: Potential ranging from automation to personalized learning},
year = {2025},
journal = {LINEAR Journal of Mathematics Education},
volume = {6},
number = {1},
pages = {85-99},
doi = {10.32332/46xc9p64},
language = {en}
}RIS
TY - JOUR AU - Ramadhani, Alifia Kania AU - Ramadani, Iqbal TI - AI in mathematics education: Potential ranging from automation to personalized learning PY - 2025 JO - LINEAR Journal of Mathematics Education VL - 6 IS - 1 SP - 85 EP - 99 DO - 10.32332/46xc9p64 LA - en ER -
Referência gerada automaticamente a partir dos metadados das fontes; confira com o documento original. Baixar BibTeX · Baixar RIS
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