A Review of Methods for Generating AI to Drive Cognitive Development in Junior High School Mathematics Education

Main Article Content

Keyi Shen
Taizhou University, Zhejiang, China

DOI: https://doi.org/10.70267/iclpce.2026297303

Keywords

generative AI, mathematics education, cognitive development, personalized teaching, mathematical thinking

Abstract

The learning of junior high school mathematics often becomes a bottleneck in students' cognitive development due to its high abstraction and strong logic. Traditional classroom teaching is unable to take into account individual differences. The deep integration of artificial intelligence and mathematics education provides a new possibility for this. It adopts the literature review method to systematically explore the cognitive development support models of generative AI in junior high school mathematics teaching, including visual design, intelligent diagnosis, hierarchical push, and real-time interaction. It also focuses on analyzing the positive effects of generative AI in enabling personalized teaching on the cultivation of mathematical thinking, while also revealing the mechanism shortcomings and the problems such as cognitive inertia and weakened independent thinking that may arise from its excessive use. Studies have shown that generative AI can significantly enhance conceptual understanding and logical reasoning abilities, but it also has limitations such as insufficient non-logical cognitive processing and insufficient space for resolving cognitive conflicts. Excessive reliance on it may hinder the natural transformation of thinking. This review aims to provide theoretical references for the boundaries of using generative AI in mathematics teaching, while summarizing the existing controversies and shortcomings in current research, and offering systematic practical insights for future human-machine collaborative cognitive development.

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Published
Jul 15, 2026
Conference Proceedings Volume
Vol. 24 (2026): Proceedings of the 2nd International Conference on Linguistics, Psychology and Creative Education (ICLPCE 2026)
Section
Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Shen, Keyi. “A Review of Methods for Generating AI to Drive Cognitive Development in Junior High School Mathematics Education”. Exploring Science Academic Conference Series, vol. 24, July 2026, pp. 297-03, https://doi.org/10.70267/iclpce.2026297303.