Data and AI Literacy in Geography Education: A Needs Assessment of Pre-Service Geography Teachers

The growing importance of data and the ongoing developments in artificial intelligence (AI) necessitate data and AI literacy in various domains. In geography education, successful integration of data and AI requires geography teachers to exhibit competencies. These have been outlined by various frameworks and models, such as TPACK, DPACK, and AI-PACK. However, despite the existence of such frameworks and the recognition that data and AI are relevant to geography education, research with a focus on pre-service geography teachers remains limited, despite its importance to geography education and its ability to provide insights into teacher education by pre-service teachers. This study investigates perceived data- and AI-related needs of pre-service geography teachers who are still in teacher education training but who have gained practical experience in planning and teaching geography lessons. Eighteen pre-service geography teachers from Germany were subjected to semi-structured interviews. The interview transcripts were analyzed using qualitative content analysis (QCA) involving a deductive-inductive approach. The results show that the participants perceive a need for specific competencies in the context of data (e.g., needs for teacher education, such as data literacy) and AI (content-related AI knowledge). Our findings strongly emphasize the importance of integrating data and AI into geography teacher education.