Presenters: UCSB Center for Spatial Studies, USC Spatial Sciences Institute, Esri
How would you teach spatial thinking in a general education course to post-secondary students with no formal training in geography? If geographers and GIScientists wish to foster spatial literacy in society this is a question that must be answered. We invite colleagues to contribute to an interactive discussion about how to teach novice learners the central elements of spatial thinking – concepts of space, tools of representation, and processes of reasoning.
An intermittently updated literature discussing concepts and questions related to spatial thinking already exists. Many of those concepts and questions remain the same. However, as new environmental and social challenges emerge and geospatial technologies change, which of those concepts and questions should be prioritized in post-secondary education merits revisiting. Moreover, the existing literature tends to offer abstract, academic treatments of these concepts that are removed from the experiences of non-specialists. This session will draw from and extend that literature by restarting a practical discussion about how to teach spatial thinking with the goal of fostering spatial literacy. Colleagues will be invited to share their own conceptions of spatial thinking, the geographic questions they use to teach key concepts, their pedagogical approaches, and their classroom successes.
Geographic information science (GIScience) has always centered on the dual objectives of developing the basic scientific foundations needed to understand the world through the collection, analysis, and representation of spatial data, and the creation of the technological tools needed for that task. In recent years, the discipline has experienced a period of rapid tool and technology development particularly around the emergence of GeoAI. Paralleling these developments in GIScience, there has been a period of conceptual development across the social and environmental sciences in causal inference. While the pattern-process approach to spatial analysis uses the tools and concepts of GIScience to describe spatial patterns of objects and events, it remains challenging to make inferences about the causal mechanisms generating those patterns.
Within the geographic and spatial statistical literature a series of recent papers have discussed causal paradigms, introduced new spatial statistical techniques, and generally deployed methods of quantitative causal analysis to answer geographic questions. However, a robust discussion of causal inference and its connection to core concepts and questions in GIScience has yet to appear in the literature. We invite colleagues to contribute to an interactive discussion session about the connections between GIScience and causal inference. Discussion topics will include whether GIScience has a unique contribution to make to the causal literature, if the current conceptual and technical foundations of GIScience are prepared to support causal analysis, and what a GIScience curriculum designed to prepare students to undertake causal analyses would look like.
