用物联网和生成式AI实现气候韧性教育的实时自适应学习。
Harnessing IoT and Generative AI for Weather-Adaptive Learning in Climate Resilience Education
- 通过物联网传感器获取实时气象数据，动态生成本地化学习任务。
- 用户评估显示系统易用且有效提升气候韧性知识。
- 适合教育科技、环境教育领域研究者与实践者参考。
本文提出未来大气条件训练系统（FACTS），一种通过基于地点的自适应学习体验推进气候韧性教育的新平台。FACTS结合物联网传感器采集的实时大气数据与知识库中的精选资源，动态生成本地化学习挑战。学习者的响应由生成式AI驱动的服务器分析，提供个性化反馈与自适应支持。用户评估结果显示，参与者认为该系统既易于使用，又在提升气候韧性相关知识方面效果显著。这些发现表明，将物联网与生成式AI融入大气自适应学习技术，对增强教育参与度和培养气候意识具有巨大潜力。
原文摘要 · Abstract (English)
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.
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