Abstract:
“Mathematical Physics Equations” is a fundamental core course for engineering disciplines such as geophysics, with broad applications in seismic wave propagation modeling, electromagnetic field analysis, and fluid dynamics. However, traditional teaching approaches primarily focus on theoretical derivations, with limited emphasis on practical applications. This results in students having insufficient skills in numerical computation and programming, thereby restricting their ability to solve complex engineering problems. With the rapid advancement of artificial intelligence (AI), technologies such as automated programming, intelligent derivation, and visualization have demonstrated immense potential in scientific computing, offering new perspectives and tools for the reform of “Mathematical Physics Equations” teaching. This paper proposes an AI-driven intelligent teaching reform framework that integrates automated programming demonstrations, problem-driven teaching, and industry-oriented case studies to enhance students’ computational thinking and engineering practice skills. The research findings indicate that this approach not only significantly improves students’ understanding and application of mathematical physics equations but also strengthens their overall innovative capabilities, providing a viable pathway for the modernization of teaching in this domain.
“数学物理方程”是地球物理等工科专业的核心基础课程,在地震波传播模拟、电磁场分析、流体动力学等领域具有广泛应用。然而,传统教学模式主要以理论推导为主,实践环节相对薄弱,导致学生在数值计算和编程应用方面能力不足,影响其在复杂工程问题中的应用能力。随着人工智能(AI)技术的迅猛发展,自动编程、智能推导和可视化模拟在科学计算领域展现出巨大潜力,为“数学物理方程”课程的教学改革提供了新的视角和手段。本文提出了一种基于AI的智能化教学改革方案,融合自动化编程演示、问题驱动式教学和行业案例导向,以提升学生的计算思维和工程实践能力。研究结果表明,该模式不仅能显著提高学生对数学物理方程的理解与应用能力,还能增强其综合创新能力,为“数学物理方程”课程的教学改革提供了一种可行的实施路径。