人工智能赋能《环境微生物学》教学改革：课程思政的融合路径与实践探索

Artificial Intelligence-Enabled Teaching Reform in Environmental Microbiology: Integration Pathways and Practical Exploration of Ideological and Political Education in Curriculum

摘要: 《环境微生物学》作为我校环境科学专业的专业核心课程，在“双碳”战略与生态文明建设背景下肩负着知识传授与价值引领的双重使命。然而，当前课程教学面临知识体系更新滞后、教学模式单一、课程思政融入浅表化等现实困境。人工智能(Artificial Intelligence, AI)技术的快速发展为破解上述难题提供了新路径，国内多所高校已在环境微生物学课程中开展了AI赋能教学的有益探索，从知识图谱构建到AI助教系统，从智能评价体系到人机协同学习模式，初步形成了“AI赋能 + 思政引领”的教学改革新范式。本文立足课程思政视域，从教学目标重构、教学内容优化、教学模式创新、评价体系完善四个维度，提出了“AI赋能 + 思政引领”的环境微生物学教学改革框架，设计了“知识传授–能力培养–价值塑造”三位一体的育人方案，以学习通(超星学习平台) AI助教为落地平台，选取“持久性有机污染物的微生物降解”为典型案例，具象化AI工具嵌入流程，分层开展科学家精神、生态文明思想等思政元素深度融合教学设计，并配套开发具备可观测点的价值素养评价量规，以期为新工科背景下环境微生物学课程建设提供参考。

Abstract: As a core professional course for the Environmental Science major at our university, Environmental Microbiology undertakes the dual mandate of knowledge delivery and value guidance amid the “Double Carbon” strategy and national ecological civilization development. However, current teaching practice of this course encounters multiple practical challenges: outdated knowledge frameworks, monotonous pedagogical approaches, and superficial integration of ideological and political education into the curriculum. The rapid advancement of Artificial Intelligence (AI) has opened up new avenues to address these issues. Multiple domestic universities have already conducted fruitful explorations of AI-enabled teaching reform for Environmental Microbiology, ranging from knowledge graph construction and AI teaching assistant systems to intelligent evaluation systems and human-machine collaborative learning models. These practices have preliminarily established a novel teaching reform paradigm of “AI empowerment + ideological and political guidance”. Grounded in the perspective of curriculum-integrated ideological and political education, this study proposes a “AI empowerment + ideological and political guidance” teaching reform framework for Environmental Microbiology across four dimensions: reconstruction of teaching objectives, optimization of teaching content, innovation of pedagogical modes, and improvement of evaluation systems. This study further designs a tripartite education scheme integrating “knowledge delivery, competency development, and value shaping”, adopts the Xuexitong (Chaoxing Learning Platform) AI Teaching Assistant as the implementation platform, selects “microbial degradation of persistent organic pollutants” as a typical teaching case, specifies the embedding process of AI tools, develops a layered instructional design that deeply integrates ideological and political elements including the scientist spirit and ecological civilization thought, and formulates a supporting value literacy evaluation rubric with quantifiable observable indicators. The overall aim of this study is to provide a practical reference for the construction of Environmental Microbiology courses under the background of the new engineering education initiative.