Exploring the Possibility of Using Embodied Artificial Intelligence in Geography Education

This study explored the possibility of using embodied AI based on sensory interaction and physical experience in accordance with the recent discussion and development of embodied artificial intelligence. Existing Generative AI has advantages in terms of information utilization and data analysis but has limitations in promoting sensory experiences in space and affective understanding of places. Accordingly, this study attempted to present a teaching plan and model using embodied AI in geography education based on embodied geographic concept and embodied cognitive theory. Specifically, various design principles and models that can be applied to geography classes using embodied AI were proposed. Furthermore, a hybrid geographic exploration class model that combines Generative AI and embodied AI was devised, and an inquiry learning model that can be applied to various geographic education topics such as spatial thinking, reading affective landscapes, and responding to climate change was presented. Geographic education using embodied AI proposed in this study is expected to play a role as a 'geographic experience amplifier' in which students embody geographic concepts through physical and sensory experiences and actively expand geographic experiences beyond simple knowledge transfer. In the current rapid AI development trend, it can be said that it has a timely meaning to proactively seek ways to utilize embodied AI in geo-education. In the follow-up study, a realistic approach should be sought focusing on embodied AI utilization design principles, feasibility within the school environment, and instructional strategies that promote student participation and immersion. Embodied AI is expected to contribute to students forming an identity as a geographic being and deepening geo-learning in a complementary relationship with the existing Generative AI.