Academic journal article Journal of Geoscience Education

Using a Web GIS Plate Tectonics Simulation to Promote Geospatial Thinking

Academic journal article Journal of Geoscience Education

Using a Web GIS Plate Tectonics Simulation to Promote Geospatial Thinking

Article excerpt

INTRODUCTION

Spatial thinking is inherent to the geosciences for both experts in the field and for novice learners (Manduca and Kastens, 2012). Spatial thinking is characterized by understanding the nature of space, the methods used to represent spatial information, and the processes of spatial reasoning (National Research Council, 2006). Spatial thinking includes spatial knowledge of orientation, scale, distance, site, association, and other elements involved in a spatial reference frame (Tversky, 1996). It also includes spatial ways of thinking and acting, such as understanding change over space versus change over time, recognizing patterns in data, and using cognitive strategies to facilitate problem-solving and decision-making (Schultz et al., 2008; Titus and Horseman, 2009; Liben and Titus, 2012). In the geosciences, spatial thinking involves abilities and skills that recognize spatial distribution and spatial patterns, identifying shapes, associating and correlating spatially distributed phenomena, imaging maps, and comparing maps and map imagery. These spatial abilities involve cognitive processes such as spatial perception, mental rotation, and spatial visualization (Kastens and Ishikawa, 2006). The ability to visualize spatial relations-such as object shapes, relative locations, and how these change over time-is a fundamental skill necessary to understand and reason about geoscience concepts (Ormand et al., 2014). Studies that have used standardized psychometric measures of spatial skills have found that spatial ability has a critical role in developing expertise in science, technology, engineering, and mathematics (STEM) outcomes (Wai et al., 2009) and has been linked to earned undergraduate and graduate degrees in STEM and the pursuit of professional STEM careers (Shea et al., 2001).

Spatial thinking processes that are bound by the Earth's surface, or to the Earth's representation through maps and computer displays are classified as geospatial thinking, a subset of spatial thinking (Huynh and Sharpe, 2013). Geospatial thinking involves using tools of representation for making inferences about space, geospatial patterns, and geospatial relationships related to the Earth's surface. These representations include map and globe visualizations that are used as tools to organize and understand data that are georeferenced to the Earth's surface. Thinking geospatially requires knowing, understanding, and remembering geospatial information and concepts. It provides a way of examining data and information that reveals properties or relations about the Earth's surface that may or may not be readily apparent. It also involves cognitive processing of georeferenced data that have been encoded and stored in memory or that are represented externally to the mind by map visualizations (Uttal, 2000). In the geosciences, the capacity to visualize data patterns and relationships on the Earth's surface is integral to the process of geospatial thinking and involves geospatial abilities such as geospatial visualization, orientation, and geospatial relations, which can be facilitated by a geographic information system (GIS) (Albert and Golledge, 1999).

Educators have recognized that GIS has the capacity to promote teaching and learning by (1) enabling powerful, multidisciplinary visualization, analysis, and synthesis of data; (2) expanding student understandings of important discipline-based content; and (3) enhancing inquiry in the sciences (National Research Council, 2006; Baker et al., 2012; Bodzin et al., 2015). GIS is a class of software applications that organizes Earth's features into thematic layers and then uses computer-based tools to aid in examining and analyzing spatial patterns, linkages, relationships, and trends. The GIS tool set enables learners to view, manipulate, and analyze rich data sets from local to global scales, including data related to geology, seismic hazards, flora and fauna distribution, climate, land cover, infrastructure, and other data that can be georeferenced using two- and threedimensional, visualization and analytical software. …

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