Empowering K-12 mathematics teachers with artificial intelligence: a systematic review of insights, applications, and challenges - Li, Dantong; Osman, Sharifah; Ahmad Alhassora, Najua Syuhada; Kumar, Jeya Amantha; Said Husain, Sharifah Kartini (Institute of Electrical and Electronics Engineers, 2025)
The integration of artificial intelligence (AI) into education is rapidly transforming teaching practices across various subjects, including mathematics. However, research specifically focusing on K-12 mathematics teachers’ use of AI remains limited, and this study fills this gap. Therefore, this systematic review explores the current practices of AI integration among K-12 mathematics teachers, focusing on a range of factors, such as demographics, research methodologies, AI tools, models, mathematical content, and the challenges encountered in this process. Following PRISMA guidelines, 18 articles published between 2020 and 2024, focusing on the integration of AI in education by K-12 mathematics teachers, were analysed from WOS, Scopus, and arXiv. The value of this study lies in the following findings: The research focuses on pre-service teachers, especially from the United States and China, which is also the main development trend in the future. The selected studies often utilized quantitative, qualitative, and mixed-methods approach, applying models such as the Technology Acceptance Model (TAM) to measure acceptance and adopting frameworks such as TPACK to guide teachers in effectively integrating technology in their teaching. Prominent AI tools frequently integrated into educational settings include ChatGPT and Intelligent Tutoring Systems (ITSs). However, there are also limitations, such as ITSs research often focusing on hypothetical applications rather than direct implementation in the classroom. Furthermore, the review emphasizes the absence of specific mathematical content or tasks for K-12 teachers, especially in secondary schools where barriers were noted regarding teacher-specific, tool-specific, and systemic issues. This underscores the necessity for professional development, improved AI tools, and comprehensive systemic frameworks.