区域产业数据驱动的线性代数课程思政教学实践路径

Regional Industrial Data-Driven Practical Pathways for Curriculum-Based Ideological and Political Education in Linear Algebra

摘要: 本文以列昂惕夫逆矩阵的求解为切入点，探索经管类专业线性代数课程思政教学的有效路径。选取浙江省数字经济核心产业中通信设备、软件信息服务、电气机械三个代表性行业的投入产出真实数据，构建三部门投入产出模型，将逆矩阵运算嵌入区域供需平衡测算的实际情境。教学以BOPPPS为框架，遵循问题驱动、认知冲突、概念建构、应用拓展的认知逻辑，引导学生在区域产业数据分析中完成理论内化与实践迁移，在知识传授过程中自然融入系统思维与产业协同发展理念。该案例可为地方高校以区域产业案例深化课程思政建设提供实践参考。

Abstract: This paper takes the solution of the Leontief inverse matrix as the entry point to explore effective paths for curriculum-based ideological and political education in Linear Algebra for economics and management majors. This study establishes a three-sector input-output model based on authentic data from Zhejiang’s three core digital economy industries: communication equipment, software and information services, and electrical machinery. The inverse matrix operation is then embedded into the practical task of regional supply-demand balance measurement. Adopting the BOPPPS teaching framework, the instructional design follows a complete cognitive logic covering problem-driven inquiry, cognitive conflict, concept construction, and practical application. By analyzing regional industrial data, students realize the internalization of theoretical knowledge and the transfer of practical abilities, while systematic thinking and industrial collaborative development are seamlessly integrated throughout the teaching process. This case provides local universities with a feasible approach to deepen the construction of curriculum-based ideological and political education with regional industrial cases.