生成式人工智能驱动下固体废物处理与处置课程教学改革探索

Exploration of Teaching Reform of Solid Waste Treatment and Disposal Course Driven by Generative Artificial Intelligence

摘要: 针对固体废物处理与处置课程知识体系庞杂性与教学模式单一性并存的现实挑战，本研究实施了基于生成式人工智能(AIGC)的教学改革。通过构建智能知识解构系统，实现了对复杂知识模块的有效拆解。运用AIGC技术驱动互动教学过程，显著提升了学生的课堂参与度。搭建跨学科融合平台，强化了理论知识向实践应用的转化能力。建立覆盖教学全周期的评估机制，优化了课程考核方式。深入挖掘并融入思政案例元素，深化了课程思政建设内涵。教学实践证实，该改革方案有效激发了学生的学习动机与创新思维培养效果，切实提升了整体教学质量，为培养契合行业需求的专业人才提供了具有可行性的创新路径。

Abstract: In response to the practical challenges of the coexistence of the complexity of the knowledge system and the singularity of the teaching mode in the solid waste treatment and disposal course, this study implemented a teaching reform based on Generative Artificial Intelligence (AIGC). By constructing an intelligent knowledge deconstruction system, the effective dissection of complex knowledge modules has been achieved. The application of AIGC technology to drive the interactive teaching process has significantly enhanced students’ classroom participation. Building an interdisciplinary integration platform has strengthened the ability to transform theoretical knowledge into practical applications. An assessment mechanism covering the entire teaching cycle has been established, and the course assessment methods have been optimized. The in-depth exploration and integration of ideological and political case elements have deepened the connotation of ideological and political construction in courses. Teaching practice has confirmed that this reform plan has effectively stimulated students’ learning motivation and the cultivation effect of innovative thinking, truly improved the overall teaching quality, and provided a feasible innovative path for cultivating professional talents that meet the needs of the industry.