Applications, multidimensional challenges, and innovative pedagogical practices of generative AI in mathematics education: a systematic review 2022–2026

A systematic review of 268 articles from 2022-2026, narrowing to 66 core research articles, analyzes the application of generative AI in mathematics education. The study identifies student learning support as the dominant application area, alongside teacher instruction assistance, assessment and feedback, and special education. Generative AI demonstrates positive effects on learning motivation and personalized support, though the full scope of findings is not detailed in the provided source.

Why it matters

This research highlights the emerging role of generative AI in educational settings, particularly its potential to transform mathematics instruction and learning outcomes. Understanding these applications and their effectiveness is crucial for institutions to develop forward-looking strategies for technology integration and pedagogical innovation. It can inform resource allocation and curriculum development to leverage AI's benefits while addressing potential challenges.

Key insights

• Generative AI applications in mathematics education span student learning support (64%), teacher instruction assistance (38%), assessment and feedback innovation (27%), and special education (2%).
• Student learning support is the predominant application area for generative AI in mathematics education.
• Generative AI shows positive effects in enhancing learning motivation.
• Generative AI provides personalized support for learners.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1931535