Abstract
Schematic diagrams (e.g., circuit diagrams, Euler circles), which depict abstract concepts, are important tools for thinking. Three interrelated diagrams that belong in this category—hierarchies, matrices, and networks—are common in both everyday and scientific contexts. For example, a hierarchy can be used to represent relations among members of the animal kingdom or the search space at a given point in a chess game; a matrix can be used to represent the grade sheet for a class or possible item pairings in a deductive-reasoning problem; and a network can be used to represent the food web for an ecosystem or the alliances among nations. Because these diagrams highlight structural similarities across situations that are superficially very different, by successfully constructing these diagrams, solvers would be led to see deep (i.e., structural) similarities among diverse situations that otherwise might not be salient (Novick, 2001). Structural understanding is a key factor underlying expertise. Thus, it is important to understand when hierarchies, matrices, and networks are each most appropriate to use, how they should be constructed, and what makes them easier or harder to understand (Hurley & Novick, 2006; Novick & Hurley, 2001).
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Novick, L.R., Catley, K.M. (2006). Interpreting Hierarchical Structure: Evidence from Cladograms in Biology. In: Barker-Plummer, D., Cox, R., Swoboda, N. (eds) Diagrammatic Representation and Inference. Diagrams 2006. Lecture Notes in Computer Science(), vol 4045. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783183_24
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DOI: https://doi.org/10.1007/11783183_24
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