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Research Papers

Design Fixation and Its Mitigation: A Study on the Role of Expertise

[+] Author and Article Information
Vimal K. Viswanathan

e-mail: v.viswanathan@gatech.edu

Julie S. Linsey

e-mail: julie.linsey@me.gatech.edu
School of Mechanical Engineering,
Georgia Institute of Technology,
801 Ferst Dr NW,
Atlanta, GA 30332

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received July 11, 2012; final manuscript received March 19, 2013; published online April 25, 2013. Assoc. Editor: Jonathan Cagan.

J. Mech. Des 135(5), 051008 (Apr 25, 2013) (15 pages) Paper No: MD-12-1354; doi: 10.1115/1.4024123 History: Received July 11, 2012; Revised March 19, 2013

Engineering idea generation plays a vital role in the development of novel products. Prior studies have shown that designers fixate to the features of example solutions and replicate these features in their ideas. This type of fixation acts as a major hindrance in idea generation, as it restricts the solution space where designers search for their ideas. Building upon the study by Linsey et al. [2010, “A Study of Design Fixation, Its Mitigation and Perception in Engineering Design Faculty,” ASME Trans. J. Mech. Des., 132, 041003], this study hypothesizes that designers fixate to example features and this fixation can be mitigated using certain defixation materials including alternate representations of the design problem. To investigate this, the experiment conducted by Linsey et al. [2010] with engineering design faculty is replicated with novice designers. Participants generate ideas for a design problem in three groups: one group working with a fixating example, a second group working with the same example along with alternate representations of the design problem and a control group. The obtained results show that both the novice designers and design faculty fixate to the same extent, whereas the defixation materials have differential effect on the two groups. This result indicates that design researchers need to be very careful in developing methods and guidelines that are formulated and tested with studies on novice designers. The effectiveness of such measures may vary with the level of expertise of the designer.

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Topics: Design
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References

Pahl, G., and Beitz, W., 2003, Engineering Design: A Systematic Approach, Springer, London, UK.
Otto, K. N., and Wood, K. L., 2001, Product Design: Techniques in Reverse Engineering and New Product Development, Prentice-Hall, New York.
Henderson, S. J., 2004, “Inventors: The Ordinary Genius Next Door,” in Creativity: From Potential to Realization, R. J.Sternberget al. ., eds., American Psychological Association, Washington, DC.
Kelley, T., and Littman, J., 2001, The Art of Innovation: Lessons in Creativity From Ideo, America's Leading Design Firm, Crown Business, NY.
Weisberg, R. W., and Persson, R. S., 1993, Creativity: Beyond the Myth of Genius, Taylor & Francis, New York.
Akin, Ö., 1990, “Necessary Conditions for Design Expertise and Creativity,” Des. Stud., 11(2), pp. 107–113. [CrossRef]
Chase, W. G., and Simon, H. A., 1973, “Perception in Chess,” Cogn. Psychol., 4(1), pp. 55–81. [CrossRef]
Reilly, R. C., 2008, “Is Expertise a Necessary Precondition for Creativity?: A Case of Four Novice Learning Group Facilitators,” Thinking Skills Creativity, 3(1), pp. 59–76. [CrossRef]
Weisberg, R. W., 2006, “Modes of Expertise in Creative Thinking: Evidence From Case Studies,” The Cambridge Handbook of Expertise and Expert Performance, E. A.Ericssonet al. ., eds., Cambridge University Press, New York.
Ericsson, K. A., 1999, “Creative Expertise as Superior Reproducible Performance: Innovative and Flexible Aspects of Expert Performance,” Psychol. Inquiry, 10(4), pp. 329–333. [CrossRef]
Jansson, D., and Smith, S., 1991, “Design Fixation,” Des. Stud., 12(1), pp. 3–11. [CrossRef]
Purcell, A. T., and Gero, J. S., 1996, “Design and Other Types of Fixation,” Des. Stud., 17(4), pp. 363–383. [CrossRef]
Viswanathan, V. K., and Linsey, J. S., 2010, “Physical Models in Idea Generation—Hindrance or Help?,” International Conference on Design Theory and Methodology, Montreal, Quebec, Canada.
Viswanathan, V. K., and Linsey, J., 2012, “Physical Models and Design Thinking: A Study of Functionality, Novelty and Variety of Ideas,” ASME Trans. J. Mech. Des., 134, p. 091004. [CrossRef]
Wiley, J., 1998, “Expertise as Mental Set: The Effects of Domain Knowledge in Creative Problem Solving,” Mem. Cogn., 26(4), pp. 716–730. [CrossRef]
Luchins, A. S., and Luchins, E. H., 1959, Rigidity of Behavior: A Variational Approach to the Effect of Einstellung, University of Oregon Books Eugene, OR.
Linsey, J., Tseng, I., Fu, K., Cagan, J., Wood, K., and Schunn, C., 2010, “A Study of Design Fixation, Its Mitigation and Perception in Engineering Design Faculty,” ASME Trans. J. Mech. Des., 132, p. 041003. [CrossRef]
Goldschmidt, G., 1989, “Problem Representation Versus Domain of Solution in Architectural Design Teaching,” J. Archit. Plann. Res., 6(3), pp. 204–215.
Voss, J. F., Vesonder, G. T., and Spilich, G. J., 1980, “Text Generation and Recall by High-Knowledge and Low-Knowledge Individuals,” J. Verbal Learn. Verbal Behav., 19(6), pp. 651–667. [CrossRef]
Simon, H. A., 1973, “The Structure of Ill Structured Problems,” Artif. Intell., 4(3–4), pp. 181–201. [CrossRef]
Reitman, W. R., 1965, Cognition and Thought, Wiley, New York.
Chrysikou, E. G., and Weisberg, R. W., 2005, “Following the Wrong Footsteps: Fixation Effects of Pictorial Examples in a Design Problem-Solving Task,” J. Exp. Psychol. Learn. Mem. Cogn., 31(5), pp. 1134–1148. [CrossRef] [PubMed]
Cardoso, C., Badke-Schaub, P., and Luz, A., 2009, “Design Fixation on Non-Verbal Stimuli: The Influence of Simple vs. Rich Pictorial Information on Design Problem-Solving,” ASME International Design Engineering Technical Conferences, San Diego, CA.
Cardoso, C., and Badke-Schaub, P., 2011, “The Influence of Different Pictorial Representations During Idea Generation,” J. Creat. Behav., 45(2), pp. 130–146. [CrossRef]
Kiriyama, T., and Yamamoto, T., 1998, “Strategic Knowledge Acquisition: A Case Study of Learning Through Prototyping,” Knowledge-Based Syst., 11(7–8), pp. 399–404. [CrossRef]
Christensen, B. T., and Schunn, C. D., “The Relationship of Analogical Distance to Analogical Function and Pre-Inventive Structure: The Case of Engineering Design,” Memory & Cognition, 35(1), pp. 29–38.
Youmans, R. J., 2011, “The Effects of Physical Prototyping and Group Work on the Reduction of Design Fixation,” Des. Stud., 32(2), pp. 115–138. [CrossRef]
Gentner, D., and Stevens, A., 1983, Mental Models, Lawrence Erlbaum, NJ.
Badke-Schaub, P., Neumann, A., Lauche, K., and Mohammed, S., 2007, “Mental Models in Design Teams: A Valid Approach to Performance in Design Collaboration?,” CoDesign, 3(1), pp. 5–20. [CrossRef]
Goldschmidt, G., 2007, “To See Eye to Eye: The Role of Visual Representations in Building Shared Mental Models in Design Teams,” CoDesign, 3(1), pp. 43–50. [CrossRef]
Matlin, M. W., 2005, Cognition, Wiley, NJ.
Collins, A. M., and Loftus, E. F., 1975, “A Spreading-Activation Theory of Semantic Processing,” Psychol. Rev., 82(6), pp. 407–428. [CrossRef]
Anderson, J. R., 1983, “A Spreading Activation Theory of Memory,” J. Verbal Learn. Verbal Behav., 22(3), pp. 261–295. [CrossRef]
DeGroot, A. D., 1966, “Perception and Memory Versus Thought: Some Old Ideas and Recent Findings,” Problem Solving, Wiley, New York, pp. 19–50.
Charness, N., 1979, “Components of Skill in Bridge,” Can. J. Psychol., 33(1), pp. 1–16. [CrossRef]
Sloboda, J. A., 1976, “Visual Perception of Musical Notation: Registering Pitch Symbols in Memory,” Q. J. Exp. Psychol., 28(1), pp. 1–16. [CrossRef]
Jeffries, R., Turner, A. A., Polson, P. G., and Atwood, M. E., 1981, The Process Involved in Designing Software in Cognitive Skills and Their Acquisition, J. R. Anderson, ed., Lawrence Erlbaum, NJ, pp. 255–283.
Suwa, M., and Tversky, B., 1996, “What Architects See in Their Sketches: Implications for Design Tools,” Proceedings of CHI '96 Conference Companion on Human Factors in Computing Systems: Common Ground Vancouver, Canada, ACM, New York.
Larkin, J. H., 1981, Enriching Formal Knowledge: A Model for Learning to Solve Textbook Problems in Cognitive Skills and Their Acquisition, J. R. Anderson, eds., Lawrence Erlbaum, NJ, pp. 311–334.
Mcdermott, J., and Larkin, J. H., 1978, “Re-Representing Text Book Physics Problems,” Proceedings of 2nd National Conference, The Canadian Society for Computational Studies of Intelligence, University of Toronto Press, Toronto.
Barnett, S. M., and Koslowski, B., 2002, “Adaptive Expertise: Effects of Type of Experience and the Level of Theoretical Understanding It Generates,” Thinking Reason., 8(4), pp. 237–267. [CrossRef]
Hatano, G., and Inagaki, K., 1986, “Two Courses of Expertise,” Research and Clinical Center for Child Development Annual Report, 6, pp. 27–36.
Glaser, R., 1989, “Expertise and Learning: How Do We Think About Instructional Processes Now That We Have Discovered Knowledge Structures,” Complex Information Processing: The Impact of Herbert A. Simon, pp. 269–282.
Newell, A., and Simon, H. A., 1972, Human Problem Solving, Prentice-Hall, Englewood Cliffs, NJ.
Casakin, H., and Goldschmidt, G., 1999, “Expertise and the Use of Visual Analogy: Implications for Design Education,” Des. Stud., 20(2), pp. 153–175. [CrossRef]
Brown, A. L., 1989, Analogical Learning and Transfer: What Develops?, in Similarity and Analogical Reasoning, S.Vosniadou and A.Ortony, eds., Cambridge University Press, Cambridge.
Vosniadou, S., 1989, Analogical Reasoning as a Mechanism in Knowledge Acquisition: A Developmental Perspective, in Similarity and Analogical Reasoning, S.Vosniadou and A.Ortony, eds., Cambridge University Press, Cambridge.
Bransford, J. D., Franks, J. J., Vye, N. J., and Sherwood, R. D., 1989, New Approaches to Instruction: Because Wisdom Can't Be Told, in Similarity and Analogical Reasoning, S.Vosniadou and A.Ortony, eds., Cambridge University Press, Cambridge.
Needham, D. R., and Begg, I. M., 1991, “Problem-Oriented Training Promotes Spontaneous Analogical Transfer: Memory-Oriented Training Promotes Memory for Training,” Mem. Cogn, 19(6), pp. 543–557. [CrossRef]
Schwartz, D. L., Bransford, J. D., and Sears, D., 2005, “Efficiency and Innovation in Transfer,” Transfer of Learning From a Modern Multidisciplinary Perspective, J. P. Mestre, ed., Information Age Publishing, NC, pp. 1–51.
Linsey, J., Clauss, E. F., Kurtoglu, T., Murphy, J. T., Wood, K. L., and Markman, A. B., 2011, “An Experimental Study of Group Idea Generation Techniques: Understanding the Roles of Idea Representation and Viewing Methods,” ASME Trans. J. Mech. Des., 133(3), p. 031008. [CrossRef]
Linsey, J., Green, M. G., Murphy, J., Wood, K. L., and Markman, A. B., 2005, “Collaborating to Success: An Experimental Study of Group Idea Generation Techniques,” ASME IDETC—Design Theory and Methodology, Long Beach, CA.
Dugosh, L. K., and Paulus, P. B., 2005, “Cognitive and Social Comparison Processes in Brainstorming,” J. Exp. Soc. Psychol., 41(3), pp. 313–320. [CrossRef]
Perttula, M., and Sipilä, P.,2007, “The Idea Exposure Paradigm in Design Idea Generation,” J. Eng. Des., 18(1), pp. 93–102. [CrossRef]
Linsey, J. S., Markman, A. B., and Wood, K. L., 2012, “Design by Analogy: A Study of the Wordtree Method for Problem Re-Representation,” ASME Trans.: J. Mech. Des., 134, p. 041009.
Shah, J. J., Kulkarni, S. V., and Vargas-Hernandez, N.,2000, “Evaluation of Idea Generation Methods for Conceptual Design: Effectiveness Metrics and Design of Experiments,” ASME Trans. J. Mech. Des., 122(4), pp. 377–384. [CrossRef]
Stone, R. B., and Wood, K. L.,2000, “Development of a Functional Basis for Design,” ASME Trans. J. Mech. Des., 122, pp. 359–370. [CrossRef]
Hirtz, J., Stone, R. B., and Mcadams, D. A., 2002, “A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts,” Res. Eng. Des., 13(2), pp. 65–82. [CrossRef]
Clark-Carter, D., 1997, Doing Quantitative Psychological Research: From Design to Report, Psychology Press/Erlbaum, UK.
Howell, D. C., 2009, Statistical Methods for Psychology, Wadsworth Publishing Group, Pacific Grove, CA.
Tabachnick, B. G., and Fidell, L. S., 2007, Experimental Designs Using Anova, Thomson/Brooks/Cole, Belmont, CA.
Anderson, M. J., 2001, “Permutation Tests for Univariate or Multivariate Analysis of Variance and Regression,” Can. J. Fish. Aquat. Sci., 58(3), pp. 626–639. [CrossRef]
Good, P. I., 2000, Permutation Tests, Springer, New York.

Figures

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Fig. 1

Design problem description provided to the participants

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Fig. 2

Example solution provided to the participants in the Fixation and Defixation groups [17]

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Fig. 3

Defixation material provided to the participants in the Defixation Group [17]

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Fig. 4

Ideas in example solution categorized based on function

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Fig. 5

Sample solutions showing high degree of fixation to the example. Some of the texts in the concepts are modified for clarity

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Fig. 6

Sample solutions with low degree of fixation to the example. Some of the texts in the concepts are modified for clarity.

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Fig. 7

Quantity, number of example features used and number of energy sources used by the design faculty followed a linear pattern with idea generation time. The error bars show (±1) standard error.

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Fig. 8

Percentage of example features used and percentage of concepts with gas engine by the design faculty followed a linear pattern with idea generation time. The error bars show (±1) standard error.

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Fig. 9

The pattern of variation of the quantity of nonredundant ideas reveals a difference between experts and novices. Error bars show (±1) standard error.

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Fig. 10

Both expert and novice designers replicate example solution features in their designs. Error bars show (±1) standard error.

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Fig. 11

The mean percentage of example features used varied significantly across the conditions. Error bars show (±1) standard error.

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Fig. 12

The Fixation Group produced lower number of ideas for energy sources compared to the Control Group. Error bars show (±1) standard error.

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Fig. 13

Both design faculty and novices tend to fixate upon the energy source specified in the example solution. Error bars show (±1) standard error.

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