AI赋能下的应急避难场所规划课程改革与学生数据素养培养

AI-Empowered Course Reform in Emergency Shelter Planning and Fostering Data Literacy

摘要: 本文针对传统应急避难场所规划课程中人口数据获取与预测环节存在的计算方法依赖人工、数据处理效率低、学生参与深度不足等问题，提出将AI技术与Python编程引入教学过程的改革思路。以规划人口预测为切入点，构建“AI辅助编程–ArcGIS Pro集成–数据可视化”的实践教学方法，引导学生利用大语言模型生成人口预测代码，在ArcGIS Pro平台中直接运行并获得规划人口分布数据。实践表明，该教学改革有效降低了编程门槛，将学生从繁琐的手工计算中解放出来，使其将更多精力聚焦于空间分析与规划决策能力的培养，同时引导学生建立“人机协作”的技术思维，合理利用AI工具提升学习效率。此外，通过增设代码审计、反事实推理和专题辩论等批判性思辨环节，引导学生正视AI模型的偏见、幻觉及责任归属等局限，在提升数据素养与AI协作能力的基础上，强化了对技术的批判性审视能力。本课程改革为应急技术与管理专业的数据驱动型课程教学提供了可借鉴的范式。

Abstract: Traditional emergency shelter planning courses show problems in reliance on manual calculation methods for population data acquisition and prediction, low data processing efficiency, and insufficient student engagement. In order to solve these problems, this paper proposes a reform approach that integrates AI technology and Python programming into the teaching process. Taking planning population prediction as the entry point, a practical teaching module of “AI-assisted programming - ArcGIS Pro integration - data visualization” is construct. Students are guided to use large language models to generate population prediction code, which is then run directly in the ArcGIS Pro platform to obtain planning population distribution data. Practice shows that this teaching reform effectively lowers the programming threshold, liberates students from tedious manual calculations, enables them to focus more on spatial analysis and planning decision-making capabilities, and simultaneously helps students develop a “human-AI collaboration” technical mindset, using AI tools reasonably to improve learning efficiency. Besides, by incorporating critical thinking components such as code auditing, counterfactual reasoning, and thematic debates, the course guides students to confront the limitations of AI models. These include biases, hallucinations, and accountability issues, which will strengthen their critical examination of technology while improve data literacy and AI collaboration capabilities. This course reform provides a replicable paradigm for data-driven course teaching in the Emergency Technology and Management major.