In August 2024, we used Ian Muehlenhaus's Map Doctor – a freely available GPT on the OpenAI store – to examine how it might enhance learning at a tertiary-level Introduction to Geographic Information Systems course.

GIS education represents a unique context in which Generative AI tools can make a significant impact. GIS courses emphasize not only technical proficiency in software but also the application of cartographic principles to communicate complex spatial data effectively.

In the study, the curriculum combined weekly one-hour lectures with two-hour laboratory sessions, during which students developed proficiency in industry-standard GIS software, specifically ArcGIS. The class comprised nine undergraduates and was facilitated by a lecturer and a teaching assistant. Students engaged in both theoretical learning and practical applications, with an emphasis on understanding human-environment interactions and addressing contemporary sustainability issues. A significant component of the course involved hands-on map creation and spatial data analysis. Students learnt to display, manipulate, and analyse spatial data, create thematic maps, and conduct environmental analyses using digital elevation models. The study explored how Map Doctor provided automated, iterative feedback to improve map design and how it influenced students’ learning processes. The course assessment structure included laboratory work, presentations, and a final project, providing multiple opportunities for students to develop and demonstrate their cartographic skills.

The study documented how students strategically combined AI tools to support different aspects of their work. While they turned to ChatGPT for technical implementation guidance, they relied on Map Doctor for specialized cartographic feedback. This dual approach allowed students to maintain focus on both technical accuracy and effective visual communication.

The findings suggest that AI tools, when thoughtfully integrated into GIS education, can serve as effective scaffolding for student learning, supporting both technical skill development and design thinking while maintaining focus on core analytical objectives. These perspectives suggest that while students valued the skills learned, they recognized both institutional and practical constraints on their application. The students' experiences highlight the importance of structured learning support and the potential role of AI tools in scaffolding the development of technical and design skills in GIS education.

Our analyses suggest how AI tools can support GIS education:

• progressive skill development: students demonstrated clear progression from basic implementation questions to sophisticated design considerations;

• strategic tool use: learners developed facility in choosing appropriate AI tools for different aspects of their work, matching tools to specific learning needs;

• iterative learning: students used AI feedback to refine both their technical implementation and design decisions through multiple iterations; and

• integration of technical and design skills: students' interactions with AI tools supported the development of both technical competency and design sensibility, which were – in turn – key objectives of the course.

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