Harnessing IoT and Generative AI for Weather-Adaptive Learning in Climate Resilience Education
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 42 references that are in the map. First posted on arXiv 29 Aug 2025.
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6 of 42 references.
References · 6
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
- 2024Reducing hallucination in structured outputs via Retrieval-Augmented Generationcited by 93
- 2023Scalable Educational Question Generation with Pre-trained Language Modelscited by 19
- 2023Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectivescited by 16
- 2023ERUDITE: Human-in-the-Loop IoT for an Adaptive Personalized Learning Systemcited by 3
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