AI赋能的多专业案例导入《材料力学》课程思政探索与实践

Exploration and Practice of AI-Empowered Multi-Disciplinary Case Introduction for Ideological and Political Education in the Course of “Mechanics of Materials”

摘要: 在新工科建设与课程思政全面推行的双重背景下，《材料力学》课程面临理论抽象难懂、工程案例与知识点关联薄弱、思政融入生硬等现实困境。本文以飞行器制造、材料加工工程和机械制造及其自动化三个专业为研究对象，提出人工智能(AI)辅助建设多专业专属动态案例库的教学改革路径。通过构建“知识点–工程案例–思政元素”三级关联体系，并据此设计了“三段式”案例导入法、例题工程化改造和超星学习通平台三级案例库协同联动的教学模式。AI赋能的专业案例库建设能够提升学生对抽象概念的理解能力和知识迁移能力，有效增强了思政融入的自然度与专业匹配度，为新工科背景下《材料力学》课程思政建设提供了可操作的实践范式。

Abstract: Against the dual background of Emerging Engineering Education construction and the comprehensive implementation of ideological and political education in all courses, the “Mechanics of Materials” course faces practical difficulties such as abstract theories that are difficult to understand, weak connections between engineering cases and knowledge points, and rigid integration of ideological and political elements. This paper takes three majors—Aircraft Manufacturing, Materials Processing Engineering, and Mechanical Manufacturing and Automation—as research objects, and proposes a teaching reform path that uses Artificial Intelligence (AI) to assist in building a dynamic case library exclusive to multiple majors. By constructing a three-level association system of “knowledge points–engineering cases–ideological and political elements,” and accordingly designing a synergistic teaching model that integrates a “three-stage” case introduction method, engineering-oriented transformation of exercises, and a three-level case library on the Chaoxing Learning Platform, this study demonstrates that AI-empowered construction of professional case libraries can enhance students’ ability to understand abstract concepts and transfer knowledge, effectively improve the naturalness of ideological and political integration and professional relevance, and provide an operable practical paradigm for ideological and political education in “Mechanics of Materials” under the context of Emerging Engineering Education.