Artificial intelligence in geography fieldwork: pre-service teacher perspectives

Abstract

This study examines how pre-service geography teachers utilize artificial intelligence (AI) tools in fieldwork, by focusing selection criteria, usage patterns, and areas. A qualitative approach was employed, using open-ended questionnaires distributed to 31 final-year geography education (GE) students at Universiti Sains Malaysia. Participants had prior fieldwork experience across Malaysia, allowing them to share their experiences and perspectives on data collection, mapping, and geospatial analysis using AI. Findings show that AI is predominantly used for data analysis (90.3%), mapping (87.1%), and information searching (83.9%), with usability and relevance to field studies being primary consideration in tool selection. AI tools such as Google Earth Engine, GeoAI, and ChatGPT enhance geospatial analysis, automate large-scale data processing, and streamline literature reviews, thereby improving the accuracy of spatial assessments, reducing manual workload, and enabling more efficient decision-making in traditional fieldwork methods. Despite these advantages, several challenges have resulted in hindering the maximum usage of AI-generated data. The findings contribute to the broader field of AI integration in education and geography by demonstrating how AI enhances data collection, geospatial analysis, and digital fieldwork methods, while also highlighting the need for AI literacy and critical thinking to ensure effective and ethical implementation in GE.