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AI-Empowered Student-Centered Teaching Optimization Path and Empirical Analysis for Mathematics Courses in Private Universities

Author(s)

Jinru Ma

Affiliation(s)

School of General Education, Liaoning University of International Business and Economics, Dalian, Liaoning, China

Abstract

In light of the digitalization of education, it is of great importance to solve the issue of the lack of student subjectivity in the private university mathematics course. In this paper, we analyze the defects of the teaching in the traditional way, we argue the reason for the value of the AI in the process of the instruction from the side of the student, and we construct the path of optimization in three stages: precise pre-class guidance, in-class inquiry-based learning, and post-class personalized expansion. The quasi-experimental results indicate that in the teaching model empowered by AI, the students' internal learning drive is stimulated, the differentiated teaching and the personalized assessment are achieved, and the academic performance and the ability of self-regulated learning are improved, which provides the paradigm for the teaching reform that can be replicated.

Keywords

Artificial Intelligence; Mathematics Courses; Student-Centered Teaching; Value-Added Assessment; Teaching Reform

References

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