Communities worldwide face urgent societal and environmental challenges, including climate change, urban heat, rapid urbanization, and social inequities. At the same time, geospatial technologies and AI are advancing at unprecedented speed, creating opportunities for actionable spatial solutions while exposing a critical skills and knowledge gap among graduates. Traditional GIS teaching, focused primarily on system development, is insufficient to prepare students to integrate AI-driven workflows with real-world applications effectively.

To address this gap, our curriculum centers on scaffolded project-based learning, guiding students to progressively master an applied three-tier GIS system architecture—Presentation, Application Logic, and Data layers—within cloud-based open-source GIS platforms enhanced with AI workflows. Each project is designed to close the loop between technology and real-world pressing issues, enabling students to translate complex spatial and socio-environmental data into actionable insights, maps, and reports that inform stakeholder-focused solutions. Scaffolded projects gradually increase in complexity, helping students gain technical competence in system design while developing strategic understanding of applying GIS and AI to societal and environmental challenges.

Students learn a range of industry-relevant tools, including PostGIS for spatial databases, QGIS for geospatial analysis, GeoAI plugins for AI-assisted workflows, Cesium for 3D visualization, Google Earth Engine (GEE App) for environmental monitoring, and Leaflet and Mapbox for interactive web mapping. These tools are embedded in projects that address regenerative futures challenges such as urban heat mitigation, green infrastructure planning, disaster resilience, and sustainable urban development.

Student learning is tracked at multiple stages. Initial responses capture prior knowledge, experience, and confidence in GIS, AI, and spatial problem-solving. During the course, students develop individual cloud-based GIS projects applying the tools to authentic challenges. End-of-course responses and reflective statements highlight progression in adaptive skills, critical thinking, and stakeholder-oriented problem-solving, demonstrating how students synthesize knowledge from geospatial science, computer science, and social-environmental studies.

Examples from student projects show how scaffolded learning enables students to apply the three-tier architecture in practical contexts, integrate AI-assisted analysis, and produce actionable geospatial solutions. By embedding system development within project-based learning, the curriculum ensures that graduates acquire technical expertise and the judgment necessary to apply geospatial technologies meaningfully, addressing both rapid technological change and pressing societal-environmental needs.

This innovative curriculum provides a comprehensive model for adaptive GIS education, linking scaffolded project learning, applied three-tier system development, AI integration, cloud-based open-source GIS tools, and real-world problem solving. It prepares graduates to design innovative, socially responsive, and environmentally regenerative solutions, equipping them to navigate the rapidly evolving landscape of geospatial technology and societal challenges.