The Journal of The Korean Association of Geographic and Environmental Education ISSN:1226-511X(Print) 2586-5641(Online) 한국지리환경교육학회지

This study aims to explore how school geography education is responding to the rapid diffusion of generative artificial intelligence (AI) and to identify future tasks in terms of curriculum, teaching–learning, and assessment. Although the fundamental goals of geography education remain unchanged, the processes for achieving those goals are being restructured through AI. Accordingly, curriculum design should move beyond the acquisition of knowledge toward reorganizing inquiry processes and enabling deeper and more expanded understanding through the use of AI. In the teaching–learning domain, where responses to generative AI have been most active, five major application types have been identified: (1) deepening data-based inquiry, (2) supporting personalized learning through chatbots, (3) creating multimodal and creative outputs, (4) exploring geographical principles through no-code simulations, and (5) facilitating real-time fieldwork learning. These applications have contributed to enriching geographical inquiry and enhancing students’ creativity, conceptual understanding, and individualized learning experiences. In terms of assessment, the focus has shifted from product-oriented judgments—easily replicated by AI—toward examining students’ cognitive processes and reflections on AI use. This requires new approaches that encompass tasks ranging from those that limit AI involvement to those that emphasize reflection on AI-assisted learning and the comparison or critique of AI-generated information against real-world data. Finally, it is imperative for the geography education community to systematically develop and share AI-integrated teaching and learning cases and to establish professional development programs that can effectively disseminate these practices into classroom contexts.