Theoretical Implications of Generative AI for Content Generation in Geoinformatics Training
Munir Ahmad, Weiny Y. Ho, Andrea Paola Goyes Robalino, Maida Maqsood · Advances in educational technologies and instructional design book series · 2024
This chapter explored the potential of generative AI in the context of geoinformatics training. Generative AI techniques can generate realistic synthetic data to support tasks like land cover classification and object detection. Moreover, AI-generated datasets can help students develop skills in remote sensing, GIS, and spatial analysis without the limitations of real-world data. Interactive simulations can provide immersive learning for disaster management and urban planning, despite requiring significant resources. Additionally, AI-generated, diverse geospatial datasets can support analytics training. Customizable AI-generated examples improve learning outcomes, while AI-generated instructional content can boost educational resource quality. The chapter also included demonstration examples of how generative AI can be used for spatial analysis and course material preparation for imparting geoinformatics training to undergraduate students.