Smart Educational Ecosystems: AI-supported modeling for outdoor learning

Abstract

Learning in external environments is gaining increasing international recognition as a flexible and experiential educational approach capable of integrating observation, inquiry, and digital technologies. This approach promotes active engagement with the surrounding envi-ronment and supports the development of transversal and digital competences. Within this framework, modelling—supported by artificial intelligence—plays a crucial role in trans-forming empirical observations into structured representations that enhance reflection and conceptual understanding. AI tools assist students in collecting, organising, and analysing data gathered outdoors, identifying patterns, and generating visual or conceptual models that sustain higher-order cognitive processes. The combination of modelling, AI, and learning in external environments leads to the creation of intelligent educational ecosystems in which students interact dynamically with space, technology, and knowledge-building processes. This con-tribution investigates how these elements intertwine to support situated learning, promote autonomy and collaboration, and encourage students to develop a systemic understanding of the phenomena they encounter. The proposed perspective highlights the potential of AI-supported modelling in educational contexts and, through evidence-based literature, de-velops an “AI-Enhanced Situated Modelling Framework” capable of guiding the design of meaningful, situated, adaptive and digitally mediated learning experiences, enhancing the in-teraction among learners, data, space and technologies.