AI-TPACK：《营养调查与评价》课程智慧教学体系优化

AI-TPACK: Optimizing the Smart Teaching System for the “Nutrition Survey and Evaluation”

摘要: 由于《营养调查与评价》课程内容可能存在教学内容枯燥、形式单一、实践效果不佳等问题，本文通过以人工智能的学科教学知识(Artificial Intelligence Technological Pedagogical Content Knowledge, AI-TPACK)为理论框架，把人工智能技术、教学方法、课程内容三者自然融合，系统设计课前、课中、课后一体化智慧教学体系。其中又借助虚拟仿真、智能学情分析、问题导向学习(Problem-Based Learning, PBL)课堂、多维智能评价等方式优化教学流程，激发学生学习主动性。为解决课程教学可能存在问题，也有利于提高人才培养质量，对医学实践类课程的教学改革有一定的探索意义。

Abstract: The course “Nutrition Survey and Evaluation” faces challenges including monotonous content, limited pedagogical approaches, and suboptimal practical outcomes. Grounded in the Technological Pedagogical Content Knowledge (TPACK) framework, this study leverages Artificial Intelligence (AI) to seamlessly integrate technology, pedagogy, and subject matter. We systematically designed an intelligent instructional system spanning pre-class, in-class, and post-class phases, incorporating virtual simulation, AI-powered learning analytics, problem-based learning (PBL) classrooms, and multi-dimensional assessment tools. This approach optimizes the instructional process, enhances student engagement, and addresses existing pedagogical challenges. The findings contribute to improving the quality of talent cultivation and offer valuable insights for reforming practice-oriented medical courses.