【摘要】 “食品安全监督管理学”是食品质量与安全专业的核心课程，其内容与多元化食物供给体系深度契合。针对农业院校该课程实践薄弱、参与度低及思政教育形式化问题，构建AI赋能的混合教学模式，集成机器学习与虚拟仿真技术，开发动态案例库及智能测评系统。结果显示：课堂参与度、知识掌握度及优秀方案产出分别提升43.5%、21%和36.3%;AI案例模拟使92%学生强化社会责任认知。研究提出“人机协同”优化路径，为新农科改革提供技术范式。更多还原

【Abstract】 Food Safety Supervision and Management is a core course in the Food Quality and Safety discipline, critically aligned with the construction of a diversified food supply system. To address the challenges of insufficient practical training, low student engagement, and formalized ideological education in agricultural universities, this study developed an AI-enhanced hybrid teaching model. By integrating machine learning and virtual simulation technologies, the model incorporates a dynamic case repository and an intelligent assessment system to optimize pedagogical workflows. Empirical results demonstrate significant improvements: classroom participation increased by 43.5%, knowledge mastery improved by21%, and high-quality solution outputs rose by 36.3%. Furthermore, AI-driven case simulations enhanced social responsibility awareness in 92% of participants. The study proposes a "human-machine collaboration" optimization path to provide a technical paradigm for New Agricultural Education reforms.更多还原