Abstract
Abstract The use of realistic visualizations has gained considerable interest due to the proliferation of virtual reality equipment. This review is concerned with the theoretical basis, technical implementation, cognitive effects, and educational implications of using realistic visualizations. Realism can be useful for learners, but in several studies, more abstract illustrations have resulted in higher performance. Furthermore, a preference for realistic visualization has been declared as being based on misconceptions regarding the cognitive system. However, we argue that this perspective is unable to fully explain the conflicting results found in the literature. To fill this theoretical gap, we devised a model to describe and compare the various levels of realism found in visualizations. We define realism as a combination of three dimensions: geometry, shading, and rendering. By varying these dimensions, it is possible to create a variety of realistic graphics. Thus, when comparing different visualizations, the realism of each of these three dimensions needs to be considered individually. Based on this technical definition, we introduce a cognitive model of learning with realistic visualizations that includes three different stages: perception, schema construction, and testing. At these three stages, variables such as the perceptual load generated by the visualization, learner characteristics influencing how well details are processed, and test types that demand concrete or flexible representations can affect whether realism fosters or hinders learning. Using the cognitive model presented in this paper, more accurate predictions and recommendations concerning the use of realism can be formulated.
Highlights
When hearing the term “realism,” common associations are computer graphics and virtual reality
Using the cognitive load theory (CLT) terminology, we can assume that different learning goals can transform realistic details from being a form of extraneous load towards contributing towards ICL as recently discussed by Skulmowski and Xu (2021)
Depending on the learning task, one should carefully choose which facet of the GSR model should feature a higher level of realism and find ways to balance the total mental load
Summary
When hearing the term “realism,” common associations are computer graphics and virtual reality. While the schematic version used by Scheiter et al (2009) features a high level of abstraction consisting of basic two-dimensional shapes, the schematic learning materials presented in the study by Brucker et al (2014) still contain enough visual information to be considered simplified drawings with some amount of detail. The complexity and styling of the geometry underlying a visual rendering determines the amount of detail and the similarity to the overall shape of a real object (Paquette, 2013); shading techniques such as image textures or parameters such as the specularity of an object can further contribute to the realism of a rendered object (Paquette, 2013); and rendering options such as cartoon shading (e.g., Todo et al, 2009) can be used to give a visualization a hand-drawn look, while current ray-tracing technologies can be utilized to create visualizations with physically correct lighting (Paquette, 2013). Arriving at generalizable claims concerning realism can be much more straightforward and fine-grained than relying on vague descriptions such as “realistic” and “schematic.” Acknowledging that realism in computer-generated imagery is the result of the combination of different design choices that can be varied more or less independently puts research on realism on a more solid theoretical ground and facilitates replication
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