Exploration of Teaching Reform in Computational Physics in the Context of Artificial Intelligence

Abstract

Abstract: Against the backdrop of Artificial Intelligence (AI), the traditional teaching model of computational physics, featuring the teaching of numerical methods combined with basic programming exercises, has become disconnected from cutting-edge knowledge, necessitating an urgent reform of teaching methodologies. The core direction of this reform is to integrate AI technology as both a tool and a methodology into the core teaching tasks of computational physics, striving to cultivate students'ability to solve complex physical problems using AI techniques. This paper identifies the existing problems from three dimensions including teaching content, teaching modes, and teaching evaluation. Based on these problems, it conducts an in-depth analysis of the teaching reform path of AI-empowered computational physics and proposes targeted implementation countermeasures.

Key words: Artificial intelligence, Computational physics, Teaching methodologies, Teaching content, Teaching modes, Teaching evaluation

CLC Number:

G642

LIU Min, ZHOU Jinjian. Exploration of Teaching Reform in Computational Physics in the Context of Artificial Intelligence[J]. The Theory and Practice of Innovation and Enntrepreneurship, 2026, 9(8): 56-58.

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