Abstract
Conveying information through a diagram depends to some extent on how well it is designed as an input to our visual system. Results of previous work by the author (and collaborators) show that diagrams based on a perceptual syntax (Geon diagrams) can improve the legibility of the semantic content in a diagram. The present work evaluates the learnability of semantic information using a perceptual notation. Results of one experiment are reported. These show that Geon diagrams are easier to learn and remember in comparison to equivalent diagrams using conventional line and box drawings.
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References
Biederman, I., "Recognition-by-Components: A Theory of Human Image Understanding", Psychological Review, 94:2, 115–147, 1987.
Marr, D., "Vision: A computational investigation into the human representation and processing of visual information", San Fransisco, CA: Freeman, 1978.
Irani, P. and Ware, C., "Diagrams Based on Structural Object Perception", Conference on Advanced Visual Interfaces, Palermo, Italy, 2000.
Irani, P. and Ware, C., "Should the Elements of Diagrams Be Rendered in 3D?", Late Breaking Hot Topics, IEEE Information Visualization Proc., Salt Lake City, Utah, 2000.
Irani, P., Ware, C. and Tingley, M., "Using Perceptual Syntax to Enhance Semantic Content in Diagrams", IEEE Computer Graphics & Applications, 21:5, 76–85, 2001.
Zhang, J., "The nature of external representation in problem solving", Cognitive Science, 21:2, 179–217, 1997.
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© 2002 Springer-Verlag Berlin Heidelberg
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Irani, P. (2002). The Learnability of Diagram Semantics. In: Hegarty, M., Meyer, B., Narayanan, N.H. (eds) Diagrammatic Representation and Inference. Diagrams 2002. Lecture Notes in Computer Science(), vol 2317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46037-3_31
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DOI: https://doi.org/10.1007/3-540-46037-3_31
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