Pathways for AI-empowered reform of Advanced Mathematics teaching in the new era

Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v8i4.5341

Lintao LIU1, Shuai YUAN2, Guiquan SUN1, Senli LIU3

1. School of Mathematics, North University of China
2. School of Mathematical Sciences, Hebei Normal University
3. College of Mathematics and Computing Science, Hunan University of Science and Technology

Abstract

Advanced Mathematics is a core foundational course for majors in science and engineering as well as economics and management in higher education. Characterized by rigorous logic, abstract nature and practical applicability, it plays an important role in cultivating students' logical thinking, mathematical analytical ability, and capacity for innovative practice. Traditional Advanced Mathematics teaching has long been constrained by rigid instructional models, abstract knowledge presentation, delayed diagnosis of students' learning status, and a single-dimensional evaluation system, making it difficult to meet the new era's requirements for personalized education and precision teaching in higher education. With the rapid development of artificial intelligence, technologies such as intelligent data analysis, visualization-based teaching, personalized content recommendation, and whole-process assessment have become deeply integrated with education and teaching, thereby opening up new pathways for the reform of Advanced Mathematics teaching. Against the background of the development of higher education in the new era, this paper analyzes the advantages of AI-empowered reform in Advanced Mathematics teaching and explores implementation pathways for the deep integration of artificial intelligence with Advanced Mathematics instruction across the full teaching process, including before-class preparation, in-class teaching, and after-class consolidation, which can serve as a practical reference for colleges to carry out digital and intelligent transformation of Advanced Mathematics teaching.

Keywords

artificial intelligence; Advanced Mathematics; teaching reform; personalized teaching; whole-process education

Funding

This work is supported by the Shanxi Provincial Higher Education Teaching Reform and Innovation Project (No. J20240925)and Hunan Provincial Teaching Reform Research Project for Regular Undergraduate Higher Education Institutions (No. 202502000822)

References

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Copyright © 2026 Lintao LIU, Shuai YUAN, Guiquan SUN, Senli LIU

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