利用IoT和生成式AI在气候韧性教育中实现天气自适应学习
Harnessing IoT and Generative AI for Weather-Adaptive Learning in Climate Resilience Education
AI总结：
本文提出FACTS系统，结合IoT实时数据与生成式AI，动态生成气候韧性学习挑战并提供个性化反馈，有效提升了教育参与度和气候意识。
摘要：
本文介绍了未来大气条件训练系统（FACTS），这是一个通过基于地点的自适应学习体验推进气候韧性教育的新颖平台。FACTS将IoT传感器收集的实时大气数据与Knowledge Base中的精选资源相结合，动态生成本地化学习挑战。由生成式AI驱动的服务器分析学习者的回答，提供个性化反馈和自适应支持。用户评估结果表明，参与者认为该系统易于使用，且能有效构建与气候韧性相关的知识。这些发现表明，将IoT和生成式AI集成到大气自适应学习技术中，对于增强教育参与度和培养气候意识具有巨大潜力。
英文摘要：
This paper introduces the Future Atmospheric Conditions Training System (FACTS), a novel platform that advances climate resilience education through place-based, adaptive learning experiences. FACTS combines real-time atmospheric data collected by IoT sensors with curated resources from a Knowledge Base to dynamically generate localized learning challenges. Learner responses are analyzed by a Generative AI powered server, which delivers personalized feedback and adaptive support. Results from a user evaluation indicate that participants found the system both easy to use and effective for building knowledge related to climate resilience. These findings suggest that integrating IoT and Generative AI into atmospherically adaptive learning technologies holds significant promise for enhancing educational engagement and fostering climate awareness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
