Hostname: page-component-76fb5796d-2lccl Total loading time: 0 Render date: 2024-04-25T16:30:47.495Z Has data issue: false hasContentIssue false

Modality and representation in analogy

Published online by Cambridge University Press:  14 March 2008

J.S. Linsey
Affiliation:
Department of Mechanical Engineering, Texas A&M University, College Station, Texas, USA
K.L. Wood
Affiliation:
Manufacturing and Design Research Laboratory, Department of Mechanical Engineering, University of Texas, Austin, Texas, USA
A.B. Markman
Affiliation:
Similarity and Cognition Lab, Department of Psychology, University of Texas, Austin, Texas, USA

Abstract

Design by analogy is a powerful part of the design process across the wide variety of modalities used by designers such as linguistic descriptions, sketches, and diagrams. We need tools to support people's ability to find and use analogies. A deeper understanding of the cognitive mechanisms underlying design and analogy is a crucial step in developing these tools. This paper presents an experiment that explores the effects of representation within the modality of sketching, the effects of functional models, and the retrieval and use of analogies. We find that the level of abstraction for the representation of prior knowledge and the representation of a current design problem both affect people's ability to retrieve and use analogous solutions. A general semantic description in memory facilitates retrieval of that prior knowledge. The ability to find and use an analogy is also facilitated by having an appropriate functional model of the problem. These studies result in a number of important implications for the development of tools to support design by analogy. Foremost among these implications is the ability to provide multiple representations of design problems by which designers may reason across, where the verb construct in the English language is a preferred mode for these representations.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Balazs, M.E., & Brown, D.C. (1998). A preliminary investigation of design simplification by analogy. Proc. Artificial Intelligence in Design ‘98Lisbon, Portugal.Google Scholar
Balazs, M.E., & Brown, D.C. (2002). Design simplification by analogical reasoning. In From Knowledge Intensive CAD to Knowledge Intensive Engineering (Cugini, U., & Wozny, M.J. Eds.), pp. 2944. Dordrecht: Kluwer Academic.Google Scholar
Ball, L.J., Ormerod, T.C., & Morley, N.J. (2004). Spontaneous analogizing in engineering design: a comparative analysis of experts and novices. Design Studies 25(5), 495508.Google Scholar
Barrlett, J.C., Till, R.E., & Leavy, J.C. (1980). Retrieval characteristics of complex pictures: effect of verbal encoding. Journal of Verbal Learning and Verbal Behavior 19, 430449.CrossRefGoogle Scholar
Barsalou, L.W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences 22(4), 577660.CrossRefGoogle ScholarPubMed
Basalla, G. (1988). The Evolution of Technology. Cambridge: Cambridge University Press.Google Scholar
BBC. (2000, Nov. 7). Wings take to the water. BBC News. Accessed at http://news.bbc.co.uk/1/hi/sci/tech/1011107.stm: in April 2006.Google Scholar
Blanchette, I., & Dunbar, K. (2001). Analogy use in naturalistic settings: the influence of audience, emotion, and goals. Memory & Cognition 29(5), 730735.Google Scholar
Casakin, H., & Goldschmidt, G. (1999). Expertise and the use of visual analogy: implications for design education. Design Studies 20(2), 153175.Google Scholar
Catrambone, R. (2002). The effects of surface and structural feature matches on the access of story analogs. Journal of Experimental Psychology: Learning, Memory, and Cognition 28(2), 318334.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B.S. (2005a). A behavioural model for representing biological and artificial systems for inspiring novel designs. In Proc. 15th Int. Conf. Engineering Design (ICED05)Melbourne, Australia.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B.S. (2005b). A functional representation for biomimetic and artificial inspiration of new ideas. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19, 113132.Google Scholar
Chandrasekaran, A. (2005). Representing function: relating functional representation and functional modeling research streams. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19(2), 6574.Google Scholar
Chandrasekaran, B., Goel, A.K., & Iwasaki, Y. (1993). Functional representation as design rationale. Computer 26(1), 4856.Google Scholar
Chi, M.T.H., Feltovich, P.J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science 5, 121132.Google Scholar
Christensen, B.T., & Schunn, C.D. (2007). The relationship of analogical distance to analogical function and pre-inventive structure: the case of engineering design. Memory & Cognition 35(1), 2938.CrossRefGoogle Scholar
Chiu, M. (2003). Design moves in situated design with case-based reasoning. Design Studies 24, 125.Google Scholar
Clement, C.A. (1994). Effect of structural embedding on analogical transfer: manifest versus latent analogs. American Journal of Psychology 107(1), 139.CrossRefGoogle Scholar
Clement, C.A., Mawby, R., & Giles, D.E. (1994). The effects of manifest relational similarity on analog retrieval. Journal of Memory & Language 33(3), 396420.Google Scholar
Devore, J.L. (1999). Probability and Statistics for Engineering and the Sciences. Duxbury, MA: Duxbury Press.Google Scholar
Dunbar, K. (1997). How scientists think: on-line creativity and conceptual change in science. In Creative Thought: An Investigation of Conceptual Structures and Processes (Ward, T.B., Smith, S.M., & Vaid, J., Eds.). Washington, DC: American Psychological Association.Google Scholar
Falkenhainer, B.F., Forbus, K.D., & Gentner, D. (1989). The structure mapping engine: algorithm and examples. Artificial Intelligence 41(1), 163.Google Scholar
Forbus, K.D., Gentner, D., & Law, K. (1995). MAC/FAC: a model of similarity-based retrieval. Cognitive Science 19(2), 141205.Google Scholar
French, M. (1988). Invention and Evolution: Design in Nature and Engineering. Cambridge: Cambridge University Press.Google Scholar
French, M. (1996). Conceptual Design. London: Springer–Verlag.Google Scholar
Gentner, D. (1983). Structure mapping—a theoretical framework. Cognitive Science 7(1), 155177.Google Scholar
Gentner, D., Holyoak, K.J., & Kokinov, B. (2001). The Analogical Mind. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Gentner, D., & Landers, R. (1985). Analogical remindings: a good match is hard to find. Proc. Int. Conf. Systems, Man, and Cybernetics, Tucson, AZ.Google Scholar
Gentner, D., & Markman, A.B. (1997). Structure mapping in analogy and similarity. American Psychologist 52, 4556.CrossRefGoogle Scholar
Gentner, D., Rattermann, M.J., & Forbus, K.D. (1993). The roles of similarity in transfer: Separating retrievability from inferential soundness. Cognitive Psychology 25(4), 524575.Google Scholar
Gero, J., & Kannengiesser, U. (2003). The situated function–behaviour–structure framework. Design Studies 25, 373391.Google Scholar
Gick, M.L., & Holyoak, K.J. (1980). Analogical problem solving. Cognitive Psychology 12, 306355.Google Scholar
Goel, V. (1995). Sketches of Thought. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Goel, A. (1997). Design, analogy, and creativity. IEEE Expert 12(3), 6270.Google Scholar
Goldschmidt, G., & Weil, M. (1998). Contents and structure in design reasoning. Design Issues 14(3), 85100.Google Scholar
Hacco, E., & Shu, L.H. (2002). Biomimetic concept generation applied to design for remanufacture. Proc. DETC 2002, ASME 2002 Design Engineering Technical Conf. Computer and Information in Engineering Conf., Montreal.CrossRefGoogle Scholar
Hirtz, J., Stone, R.B., & McAdams, D.A., Szykman, S., & Wood, K. (2002). A functional basis for engineering design: reconciling and evolving previous efforts. Research in Engineering Design 13(1), 6582.Google Scholar
Holyoak, K.J., & Koh, K. (1987). Surface and structural similarity in analogical transfer. Memory and Cognition 15(4), 332340.Google Scholar
Holyoak, K.J., & Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science 13(3), 295355.Google Scholar
Hummel, J.E., & Holyoak, K.J. (1997). Distributed representations of structure: a theory of analogical access and mapping. Psychological Review 104(3), 427466.CrossRefGoogle Scholar
Kitamura, Y., Sano, T., Namba, K., & Mizoguchi, R. (2002). Functional concept ontology and its application to automatic identification of functional structures. Advanced Engineering Informatics 16(2), 145163.Google Scholar
Kolodner, J.L. (1997). Educational implications of analogy: a view from case-based reasoning. American Psychologist 52(1), 5766.Google Scholar
Kryssanov, V.V., Tamaki, H., & Kitamura, S. (2001). Understanding design fundamentals: how synthesis and analysis drive creativity, resulting in emergence. Artificial Intelligence in Engineering 15, 329342.Google Scholar
Kurfman, M., Stock, M.E., Stone, R.B.Rajan, J., & Wood, K.L. (2003). Experimental studies assessing the repeatability of a functional modeling derivation method. Journal of Mechanical Design 125(4), 682693.CrossRefGoogle Scholar
Kutner, M.H., Nachtsheim, C.J., Neter, J., & Li, W. (2005). Applied Linear Statistical Models. Boston: McGraw–Hill.Google Scholar
Leclercq, P., & Heylighen, A. (2002). 5.8 analogies per hour. In Artificial Intelligence in Design ‘02 (Gero, J.S., Ed.), pp. 285303.Google Scholar
Linsey, J.S., Murphy, J.T., Wood, K.L., Markman, A.B., & Kurtoglu, T. (2006). Representing analogies: increasing the probability of success. Proc. ASME Design Theory and Methodology Conf.Philadelphia, PA.Google Scholar
Loftus, G.R., & Kallman, H.J. (1979). Encoding and use of detail information in picture recognition. Journal of Experimental Psychology: Human Learning and Memory 5, 197211.Google ScholarPubMed
Markman, A.B. (1999). Knowledge Representation. Mahwah, NJ: Erlbaum.Google Scholar
McAdams, D., & Wood, K. (2002). A quantitative similarity metric for design by analogy. Journal of Mechanical Design 124(2), 173182.Google Scholar
Nagai, Y., & Noguchi, H. (2002). How designers transform keywords into visual images. Proc. 4th Conf. Creativity & CognitionLoughborough, UK.Google Scholar
Novick, L.R. (1988). Analogical transfer, problem similarity, and expertise. Journal of Experimental Psychology: Learning, Memory, and Cognition 14(3), 510520.Google Scholar
Otto, K., & Wood, K. (2001). Product Design: Techniques in Reverse Engineering and New Product Development. Upper Saddle River, NJ: Prentice–Hall.Google Scholar
Paivio, A. (1986). Mental Representations: A Dual Coding Approach. New York: Oxford University Press.Google Scholar
Purcell, A.T., & Gero, J.S. (1998). Drawings and the design process. Design Studies 19(4), 389430.CrossRefGoogle Scholar
Qian, L., & Gero, J.S. (1996). Function–behavior–structure paths and their role in analogy-based design. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 10(3), 289312.Google Scholar
Reed, J. (2006). The future of shipping. Popular Science May, 5051.Google Scholar
Schooler, J.W., Fiore, S.M., & Brandimonte, M.A. (1997). At a loss from words: verbal overshadowing of perceptual memories. In The Psychology of Learning and Motivation (Medin, D.L., Ed.), Vol. 37, pp. 291340. New York: Academic Press.Google Scholar
Schunn, C.D., & Dunbar, K. (1996). Priming, analogy, and awareness in complex reasoning. Memory & Cognition 24(3), 271284.CrossRefGoogle ScholarPubMed
Scientific American. (1998, Dec. 21). Ask the experts: biology. How do bats echolocate and how are they adapted to this activity? Accessed at http://www.sciam.com/askexpert_question.cfm?articleID=000D349B-6752-1C72-9EB7809EC588F2D7&catID=3&topicID=3 on January 4, 2008.Google Scholar
Shah, J.J., Vargas-Hernández, N., Summers, J.S., & Kulkarni, S. (2001). Collaborative sketching (C-Sketch)—an idea generation technique for engineering design. Journal of Creative Behavior 35(3), 168198.Google Scholar
Stahovich, T.F., Davis, R., & Shrobe, H. (1998). Generating multiple new designs from a sketch. Artificial Intelligence 104, 211264.CrossRefGoogle Scholar
Stone, R., & Chakrabarti, A. (2005). Engineering applications of representations of function. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19(2), 63.Google Scholar
Stone, R., & Wood, K. (2000). Development of a functional basis for design. Journal of Mechanical Design 122(4), 359370.Google Scholar
Suwa, M., & Tversky, B. (1997). What do architects and students perceive in their design sketches?: a protocol analysis. Design Studies 18, 385403.Google Scholar
Tinsley, A., Midha, P., Nagel, R., McAdams, D., Stone, R., & Shu, L. (2007). Exploring the use of functional models as a foundation for biomimetic conceptual design. ASME Design Theory and Methodology Conf., Paper No. DETC2007-35604, Las Vegas, NV.Google Scholar
Thompson, L., Gentner, D., & Loewenstein, J. (2000). Avoiding missed opportunities in managerial life: analogical training more powerful than individual case training. Organizational Behavior and Human Decision Processes 82(1), 6075.Google Scholar
Tulving, E., & Thomson, D.M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review 80, 352373.Google Scholar
Ullman, D.G., Wood, S., & Craig, D. (1990). The importance of drawing in the mechanical design process. Computer Graphics 14(2), 263274.CrossRefGoogle Scholar
Umeda, Y., & Tomiyama, T. (1997). Functional reasoning in design. IEEE Expert 12(2).Google Scholar
Vakili, V., Chiu, I., Shu, L., McAdams, D., & Stone, R. (2007). Functional models of biological phenomena as design stimuli. ASME Design Theory and Methodology Conf., Paper No. DETC2007-35776, Las Vegas, NV.Google Scholar
Vidal, R., Mulet, E., & Gómez-Senent, E. (2004). Effectiveness of the means of expression in creative problem-solving in design groups. Journal of Engineering Design 15(3), 285298.Google Scholar
Yaner, P.W., & Goel, A.K. (2006a). From diagrams to models by analogical transfer. Proc. 4th Int. Conf. Diagrams 2006 (Barker-Plummer, D., Cox, R., & Swoboda, N., Eds.), pp. 5569. Stanford, CA: Springer.Google Scholar
Yaner, P.W., & Goel, A.K. (2006b). From form to function: from SBF to DSSBF. Proc. Design Computing and Cognition 2006 (Gero, J.S., Ed.), pp. 423441. Berlin: Springer.Google Scholar
Yaner, P.W., & Goel, A.K. (2007). Understanding drawings by compositional analogy. Proc. 20th Int. Joint Conf. Artificial Intelligence, pp. 11311137, Hyderabad, India.Google Scholar
Yang, M.C., & Cham, J.G. (2007). An analysis of sketching skill and its role in early stage engineering design. Journal of Mechanical Design 129(5), 476482.Google Scholar