Abstract
Annotation.Artificial intelligence (AI) and computational thinking have opened up opportunities for transformation in the study of geography based on data and technology.However, most geography teachers do not yet have sufficient competence.This community service program aims to increase the proficiency of artificial intelligence and computational thinking among geography teachers through hands-on learning.The methods used include classical seminars and field trips, with materials: artificial intelligence workshop: introduction and practice of working with software based on geospatial examples, as well as direct field trips; training in computational thinking; and direct mentoring of teachers in the implementation of AI-based learning.The assessment was carried out using preliminary and final testing on indicators of artificial intelligence and computational thinking, as well as a public opinion poll.The results of Wilcoxon's analysis showed a significant increase in artificial intelligence scores (the average preliminary test score was 4.00 to 7.98) and computational thinking (from 3.57 to 7.73) with a p-value of <0.001.In addition, 90% of participants expressed willingness to implement AI-based approaches in the learning process.These results show that context-based and hands-on learning can effectively enhance teachers' competence.The Community Service Program recommends further mentoring, especially in technical aspects, to ensure the adoption and sustainability of innovations in geospatial and AI-based learning, as well as practical field work.