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A fix for fixation? Rerepresenting and abstracting as creative processes in the design of information systems

Published online by Cambridge University Press:  26 April 2010

Doris Zahner ,
Jeffrey V. Nickerson ,
Barbara Tversky ,
James E. Corter  and
Jing Ma
Doris Zahner
Affiliation:
Stevens Institute of Technology, Castle Point on Hudson, Hoboken, New Jersey, USA
Jeffrey V. Nickerson
Affiliation:
Stevens Institute of Technology, Castle Point on Hudson, Hoboken, New Jersey, USA
Barbara Tversky
Affiliation:
Teachers College, Columbia University, New York, New York, USA
James E. Corter
Affiliation:
Teachers College, Columbia University, New York, New York, USA
Jing Ma
Affiliation:
Stevens Institute of Technology, Castle Point on Hudson, Hoboken, New Jersey, USA
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Abstract

Fixation prevents the associations that are bridges to new designs. The inability to see alternative solutions, or even to see how to map known solutions onto current problems, is a particularly acute problem in the design of software-intensive systems. Here, we explored two related ways of liberating fixated thinking: abstracting and rerepresenting. Although both techniques helped designers generate original ideas, not all the added ideas fit the problem constraints. We discuss ways the results might be used to generate reflective design aids that help designers to first generate original ideas and later prune them.

Keywords

AbstractionDesign of Information SystemsFluency: OriginalityRerepresentation
Type
Special Issue Articles
Information
AI EDAM , Volume 24 , Issue 2: Creativity: Simulation, Stimulation, and Studies , May 2010 , pp. 231 - 244
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

Amabile, T.M. (1996). Creativity in Context. Boulder, CO: Westview Press.Google Scholar
Anderson, J.A. (1993). Rules of the Mind. Hillsdale, NJ: Erlbaum.Google Scholar
Bergman, M., King, J., & Lyytinen, K. (2001). Large scale requirements analysis as heterogeneous engineering. Scandinavian Journal of Information Systems 12 (1), 37–55.Google Scholar
Bergman, M., King, J., & Lyytinen, K. (2002). Large scale requirements analysis revisited: the need for understanding the political ecology of requirements engineering. Requirements Engineering Journal 7 (3), 152–171.Google Scholar
Booch, G., Jacobson, I., & Rumbaugh, J. (1998). The Unified Modelling Language User Guide. Reading, MA: Addison–Wesley.Google Scholar
Choi, H., & Thompson, L. (2005). Old wine in a new bottle: impact of membership change on group creativity. Organizational Behavior and Human Decision Processes 98 (2), 121–132.Google Scholar
Christensen, B.T., & Schunn, C.D. (2004). The relationship of analogical distance to analogical function and preinventive structure: the case of engineering design. Memory & Cognition 35 (1), 29–38.CrossRefGoogle Scholar
Dunker, K. (1945). On problem solving. Psychological Monographs 55(No. 270).Google Scholar
Finke, R. (1990). Creative Imagery: Discoveries and Inventions in Visualization. Hillsdale, NJ: Erlbaum.Google Scholar
Fowler, M. (2004). UML Distilled: A Brief Guide to the Standard Object Modeling Language. Reading, MA: Addison–Wesley.Google Scholar
Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1995). Design Patterns: Elements of Reusable Object-Oriented Software. Upper Saddle River, NJ: Addison–Wesley.Google Scholar
Gasper, K. (2004). Do you see what I see? Affect and visual information processing. Cognition and Emotion 18 (3), 405–421.Google Scholar
Gentner, D., & Markman, A.B. (2006). Defining structural similarity. Journal of Cognitive Science 6 (1), 1–20.Google Scholar
Gentner, D., & Stevens, A.L. (Eds.). (1983). Mental Models. Hillsdale, NJ: Erlbaum.Google Scholar
Gentner, D., & Wolff, P. (2000). Metaphor and knowledge change. In Cognitive Dynamics: Conceptual and Representational Change in Humans and Machines (Dietrich, E., & Markman, A.B., Eds.), pp. 294–342. Hillsdale, NJ: Erlbaum.Google Scholar
Gick, M.L., & Holyoak, K.J. (1980). Analogical problem solving. Cognitive Psychology 12 (3), 306–355.CrossRefGoogle Scholar
Gick, M.L., & Holyoak, K.J. (1983). Schema induction and analogical transfer. Cognitive Psychology 15 (1), 1–39.Google Scholar
Goldschmidt, G. (1991). The dialectics of sketching. Creativity Research Journal 4 (2), 123–143.Google Scholar
Goldschmidt, G. (1994). On visual design thinking: the vis kids of architecture. Design Studies 15 (2), 158–174.Google Scholar
Goldstone, R.L., & Sakamoto, Y. (2003). The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology 46 (4), 414–466.CrossRefGoogle ScholarPubMed
Goldstone, R.L., & Son, J.Y. (2005). The transfer of scientific principles using concrete and idealized simulations. Journal of the Learning Sciences 14 (1), 69–110.Google Scholar
Hamming, R.W. (1986). You and your research. Proc. Bell Communication Research Colloquium Seminar.Google Scholar
Holyoak, K.J., & Cheng, P.W. (1995). Pragmatic reasoning with a point of view. Thinking & Reasoning 1 (4), 289–313.Google Scholar
Holyoak, K.J., & Thagard, P. (2002). Analogical mapping by constraint satisfaction. In Cognitive Modeling (Polk, T.A., & Siefert, C.M., Eds.), pp. 849–909. Cambridge, MA: MIT Press.Google Scholar
Johnson-Laird, P.N. (1983). Mental Models: Toward a Cognitive Science of Language, Inference, and Consciousness. Cambridge, MA: Harvard University Press.Google Scholar
Kahneman, D., & Frederick, S. (2005). A model of heuristic judgment. In Cambridge Handbook of Thinking and Reasoning (Holyoak, K., & Morrison, R., Eds.). Cambridge: Cambridge University Press.Google Scholar
Karmiloff-Smith, A. (1993). Constraints on representational change: evidence from children's drawing. Cognition 34 (1), 57–83.Google Scholar
Kotovsky, L., & Gentner, D. (1996). Comparison and categorization in the development of relational similarity. Child Development 67 (6), 2797–2822.Google Scholar
Lee, A.S. (2000). Systems thinking, design science and paradigms: heeding three lessons from the past to resolve three dilemmas in the present to direct a trajectory for future research in the information systems field. Proc. 11th Int. Conf. Information Management. Accessed at http://www.people.vcu.edu/∼aslee/ICIM-keynote-2000Google Scholar
Lee, A.S., & Nickerson, J.V. (2010). Theory as a case of design: lessons for design from the philosophy of science. Proc. 43rd Annual Hawaii Int. Conf. Systems Science.Google Scholar
Maher, M.L. (2008). CreativeIT: does IT enhance creativity or does creativity enhance IT? Keynote Address. Proc. Design, Computing, and Cognition Conf.Google Scholar
Nickerson, J.V. (2006). Teaching the integration of information systems technologies. IEEE Transactions on Education 49 (2), 271–277.Google Scholar
Nickerson, J.V., Corter, J.E., Tversky, B., Zahner, D., & Rho, Y. (2008). The spatial nature of thought: understanding information systems design through diagrams. Proc. 29th Int. Conf. Information Systems.Google Scholar
Novick, L. (1990). Representational transfer in problem solving. Psychological Science 1 (2), 128–132.Google Scholar
Novick, L., & Hmelo, C. (1994). Transferring symbolic representations across nonisomorphic problems. Journal of Experimental Psychology: Learning, Memory, and Cognition 20 (6), 1296–1321.Google Scholar
Osborn, A.F. (1963) Applied Imagination: Principles and Procedures of Creative Problem Solving, 3rd ed.New York: Charles Scribner's Sons.Google Scholar
Oxman, R. (1997). Design by re-representation: a model of visual reasoning in design. Design Science 18 (4), 329–347.Google Scholar
Redmiles, D., & Nakakoji, K. (2004). Supporting reflective practitioners. Proc. 9th Int. Conf. Software Engineering, pp. 688–690.Google Scholar
Ross, B.H. (1989). Distinguishing types of superficial similarities: different effects on the access and use of earlier problems. Journal of Experimental Psychology: Learning, Memory, and Cognition 15 (4), 456–468.Google Scholar
Ross, B.H., & Kennedy, P.T. (1990). Generalizing from the use of earlier examples in problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition 16, 42–55.Google Scholar
Rumelhart, D.E., & McClelland, J.L. (1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 1. Cambridge, MA: MIT Press.Google Scholar
Rundus, D., & Atkinson, R.C. (1970). Rehearsal processes in free recall: a procedure for direct observation. Journal of Verbal Learning and Verbal Behavior 9 (2), 99–105.Google Scholar
Schön, D.A. (1983). The Reflective Practitioner: How Professionals Think in Action. Jackson, TN: Basic Books.Google Scholar
Schwartz, D.L., & Black, J.B. (1996). Shuttling between depictive models and abstract rules: induction and fallback. Cognitive Science 20 (4), 457–497.Google Scholar
Simon, H.A. (1995). Problem forming, problem finding and problem solving in design. In Design & Systems (Collen, A., & Gasparski, W., Eds.), pp. 245–257. Edison, NJ: Transaction Publishers.Google Scholar
Sloman, S.A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin 119 (1), 3–22.Google Scholar
Southey, R. (1837). The story of the three bears. In The Doctor, Vol. 4. London: Longman.Google Scholar
Suwa, M., & Tversky, B. (1997). What do architects and students perceive in their design sketches? A protocol analysis. Design Studies 18 (4), 385–403.Google Scholar
Suwa, M., & Tversky, B. (2003). Constructive perception: a skill for coordinating perception and conception. In Proc. 25th Annual Conf. Cognitive Science Society (Alterman, R., & Kirsh, D., Eds.), pp. 1140–1145. Austin, TX: Cognitive Science Society.Google Scholar
Suwa, M., Tversky, B., Gero, J.S., & Purcell, T. (2001). Seeing into sketches: regrouping parts encourages new interpretations. In Visual and Spatial Reasoning in Design II (Gero, J.S., Tversky, B., & Purcell, T., Eds.), pp. 207–219. Sydney: Key Centre of Design Computing and Cognition.Google Scholar
Tversky, B., Corter, J.E., Nickerson, J.V., Zahner, D., & Rho, Y. (2008). Transforming descriptions and diagrams to sketches in information systems design. In Diagrams 2008 (Stapleton, G., Howse, J., & Lee, J., Eds.), pp. 242–256. Berlin: Springer–Verlag.Google Scholar
Visser, W. (1991). Evocation and elaboration of solutions: different types of problem-solving actions. An empirical study on the design of an aerospace artifact. In Cognitiva 90. At the Crossroads of Artificial Intelligence, Cognitive Science and Neuroscience. Proc. 3rd COGNITIVA Symp. (Kohonen, T., & Fogelman-Soulié, F., Eds.). Amsterdam: Elsevier.Google Scholar
Wallach, M.A., & Kogan, N. (1965). Modes of Thinking in Young Children: A Study of the Creativity Intelligence Distinction. New York: Holt, Rinehart & Winston.Google Scholar
Wason, P., & Johnson-Laird, P. (1972). Psychology of Reasoning: Structure and Content. Cambridge, MA: Harvard University Press.Google Scholar