Methods of using artificial intelligence technologies in project-based learning in the Fundamentals of Geoeconomics section of school geography

Abstract

The rapid advancement of artificial intelligence (AI) technologies has significantly transformed contemporary educational practices, positioning AI as a key instrument for knowledge construction, data analysis, and digital innovation in school education. Beyond its technical functions, AI increasingly influences pedagogical models, learning personalization, and the development of higher-order cognitive skills. This study examines the role of artificial intelligence technologies in project-based learning within the “Fundamentals of Geoeconomics” section of school geography, focusing on their potential to enhance students’ understanding of spatial-economic processes and global economic interdependencies.

The research adopts an integrated analytical framework that combines insights from digital pedagogy, constructivist learning theory, and geoeconomic education. Drawing on educational practice, curriculum documents, and classroom-based project activities, the study employs comparative and qualitative analysis to assess how the integration of AI-based tools relates to students’ learning outcomes across different instructional contexts. Particular attention is given to the role of AI in supporting information processing, data visualization, scenario modeling, and decision-making in geoeconomic projects.

The findings indicate that the use of AI technologies in project-based learning contributes to improved student engagement, critical thinking, and problem-solving skills. AI-supported projects are shown to facilitate deeper conceptual understanding of regional development, spatial inequalities, and global economic dynamics by enabling students to work with real-world datasets and simulate alternative development scenarios. However, the results also reveal that the benefits of AI integration are unevenly distributed. Educational environments with higher levels of digital infrastructure, teacher preparedness, and technological accessibility benefit disproportionately, while less-resourced schools face structural constraints that may limit the effectiveness of AI-based instruction.

This study contributes to the literature on digital geography education by synthesizing pedagogical, technological, and spatial-economic perspectives within a project-based learning framework. The findings underscore the need for coordinated educational policies and teacher training programs that promote inclusive and ethically informed access to artificial intelligence technologies, ensuring that AI supports balanced, meaningful, and sustainable learning in school geography.