Research on Applied Talent Training Path Based on the In-depth Integration of Artificial Intelligence and Mathematical Modeling Competitions

DOI: https://doi.org/10.62517/jhet.202615331

Author(s)

Tao Chen*, Chao Zhang

Affiliation(s)

Department of Basic Courses, Nanjing Tech University Pujiang Institute, Nanjing, China *Corresponding Author.

Abstract

With the explosive development of artificial intelligence (AI) technologies, traditional modes of learning and working are being transformed. The cultivation of traditional, application-oriented talent requires students to have an extremely solid foundation of knowledge, self-discipline, and learning ability. This results in a persistent shortage of such talent. Mathematical modeling competitions are widely adopted as one of the platforms for training application-oriented talents; nevertheless, many students are deterred from participating in these contests. As a vital bridge linking theory to practice, mathematical modeling competitions are undergoing a paradigm shift from "traditional modeling" to "AI-driven modeling". This paper mainly aims to construct an educational theoretical framework featuring the in-depth integration of "AI + mathematical modeling" by integrating constructivist learning theory, psychological theories and mathematical modeling methodologies. Meanwhile, a multi-dimensional evaluation system is designed for the dynamic process of competency acquisition, so as to address long-standing difficulties in cultivating application-oriented talents and provide theoretical support for the teaching reform of higher education.

Keywords

Artificial Intelligence; Mathematical Modeling; Application-Oriented Talents; Constructivism; Talent Cultivation System

References

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