Preparedness Without Pedagogy? An AI-Assisted Web Scraping Analysis of Informal Online Disaster Preparedness Resources for the Public

Informal learning increasingly occurs in digital environments, where citizens access, evaluate and apply knowledge outside of formal education. In the context of disaster preparedness, such informal learning is crucial for promoting individual and collective self-protection. This study examines how disaster preparedness knowledge is represented in German-language online resources, and how these materials can be categorised from an adult education perspective. An exploratory mixed-methods design combining expert-guided sampling, a qualitatively developed coding scheme, large-scale web scraping and AI-assisted classification was employed. A total of 7305 webpages were analysed in terms of actor type, topic, media format, and didactic design. The findings suggest that government and commercial organisations dominate the online preparedness landscape, with limited contributions from civil society and individuals. Thematically, most resources focus on general preventive measures and checklists, whereas scenario-specific and procedural content is underrepresented. Didactically rich and interactive formats are rare, with most materials relying on static, text-based communication. From an adult education perspective, these results suggest a gap between raising awareness and active learning. While online resources offer easy access to preparedness knowledge, they rarely facilitate deeper understanding, participation or collaborative learning. Methodologically, the study illustrates how AI-assisted analysis can combine qualitative interpretive depth with computational scalability in educational research.