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Diagrams as Tools in the Design of Information
Systems

Jeffrey V. Nickerson,
Stevens Institute of Technology, USA

James E. Corter, Barbara Tversky,
Columbia University, USA

Doris Zahner,
Stevens Institute of Technology, USA

and Yun Jin Rho
Columbia University, USA

Design typically relies on diagrams to offload memory and information processing and to promote discovery and inferences. Design of information systems, in contrast to design of buildings and products, depends on topological connectivity rather than Euclidean distance. Understanding graph topology and manipulating graphs are essential skills in the design of information systems, because graph manipulation facilitates the refinement of designs and the generation of alternative designs. Here, we found that students of systems design have difficulties interpreting diagrams, revealing two biases, a sequential bias and a reading order bias. The results have implications for teaching as well as diagram design.

Design Computing and Cognition DCC’08. J.S. Gero and
A. Goel (eds), pp. 103-122. © Springer 2008

103

104

J. V. Nickerson, J. E. Corter, B. Tversky, D. Zahner, Y. Rho

Introduction
Design entails arranging and rearranging real or virtual objects and parts and evaluating the resulting configurations. Although the mind seems to have almost unlimited space to passively store information, its space for actively manipulating information is highly limited. When the mind runs out of mental space, it often turns to external space, using fingers and hands, salt and pepper shakers, the proverbial napkin, and, especially, paper. Sketches, diagrams, charts, models, and other externalizations of the workings of the mind serve many roles in thinking. They support memory, information processing, inferences, and discovery. They structure, reflect, and express ideas, for oneself and for others. They use elements and spatial relations in external space to represent the



References: 1. Larkin JH, Simon H (1987) Why a diagram is (sometimes) worth ten thousand words? Cognitive Science 11: 65–99 122 4. Nickerson JV (2005) The meaning of arrows: Diagrams and other facets in system sciences literature 5. Taylor HA, Tversky B (1992) Descriptions and depictions of environments. 7. Peterson LL, Davie BS (2007) Computer networks: A systems approach. 9. Larkin JH, McDermott J, Simon DP, Simon HA (1980) Expert and novice performance in solving physics problems 10. Chi M, Feltovich P, Glaser R (1981) Categorization and representation of physics problems by experts and novices 11. Suwa M, Tversky B (1997) What do architects and students perceive in their design sketches? A protocol analysis 12. Hevner AR, March ST, Park J, Ram S (2004) Design science in information research 13. March ST, Smith GF (1995) Design and natural science research on information technology. Decision Support Systems 15: 251-266 14 15. Harel D (1988) On visual formalisms, CACM 31: 514-530 16 17. Lange CFJ, Chaudron MRV, Muskens J (2006) In practice: UML software architecture and design description. Software IEEE 23: 40-46 18 19. Corter JE, Zahner DC (2007) Use of external visual representations in probability problem solving. Statistics Education Research Journal 6: 22–50 20

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