Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-17T22:11:28.903Z Has data issue: false hasContentIssue false
  • English
  • Français

Psychological challenges for the analysis of style

Published online by Cambridge University Press:  27 June 2006

MARTIN STACEY
MARTIN STACEY
Affiliation:
School of Computing, De Montfort University, Leicester, UK
Get access Rights & Permissions [Opens in a new window]

Abstract

Analyses of styles in design have paid little attention to how people see style and how designers use perceptions of style to guide designing. Although formal and computational methods for analyzing styles and generating designs provide impressively parsimonious accounts of what some styles are, they do not address many of the factors that influence how humans understand styles. The subtlety of human style judgments raises challenges for computational approaches to style. This paper differentiates between a range of distinct meanings of “style” and explores how designers and ordinary people learn and apply perceptual similarity classes and style concepts in different situations to interpret and create designed artifacts. A range of psychological evidence indicates that style perception is dependent on knowledge and involves the interaction of perceptual recognition of style features and explanatory inference processes that create a coherent understanding of an object as an exemplar of a style. This article concludes by outlining how formal style analyses can be used in combination with psychological research to develop a fuller understanding of style perception and creative design.

Keywords

Psychology of DesignStyle
Type
Research Article
Information
AI EDAM , Volume 20 , Issue 3 , August 2006 , pp. 167 - 184
Copyright
© 2006 Cambridge University Press

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

Ackerman, J.S. (1967). A theory of style. In Aesthetic Inquiry: Essays in Art Criticism and the Philosophy of Art (Beardsley, M.C. & Schueller, H.M., Eds.), pp. 54–66. Belmont, CA: Dickenson.
Ahn, W. (1999). Effect of causal structure on category construction. Memory & Cognition, 27, 1008–1023.Google Scholar
Ahn, W., Kalish, C., Gelman, S.A., Medin, D.L., Luhmann, C., Atran, S., Coley, J.D., & Shafto, P. (2001). Why essences are essential in the psychology of concepts. Cognition, 82(1), 59–69.Google Scholar
Akın, Ö. (1978). How do architects design? In Artificial Intelligence and Pattern Recognition in Computer-Aided Design (Latombe, J.-C., Ed.), pp. 65–104. New York: North-Holland.
Akın, Ö. (1986). The Psychology of Architectural Design. London: Pion.
Anderson, J.R. (1978). Arguments concerning representations for mental imagery. Psychological Review, 85(3), 249–277.Google Scholar
Anderson, J.R. (1982). Representational Types: A Tricode Proposal. Technical Report ONR-82-1. Pittsburgh, PA: Carnegie Mellon University, Department of Psychology.
Anderson, J.R. (1983). The Architecture of Cognition. Cambridge, MA: Harvard University Press.
Asimow, M. (1962). Introduction to Design. Englewood Cliffs, NJ: Prentice-Hall.
Barsalou, L.W. (1985). Ideals, central tendency, and frequency of instantiation as determinants of graded structure of categories. Journal of Experimental Psychology: Learning, Memory and Cognition, 11(3), 629–654.Google Scholar
Bartlett, F.C. (1932). Remembering. Cambridge: Cambridge University Press.
Bell, C.P., Dawes, W.N., Jarrett, J.P., & Clarkson, P.J. (2005). Improving the conceptual design of turbine rotor blade cooling systems. Proc. 15th Int. Conf. Engineering Design, Melbourne, Australia.
Carmichael, L.P., Hogan, H.P., & Walter, A.A. (1932). An experimental study of the effect of language on the reproduction of visually perceived form. Journal of Experimental Psychology, 15(1), 73–86.Google Scholar
Cavanagh, P., Arguin, M., & Treisman, A. (1990). Effects of surface medium on visual search for orientation and size features. Journal of Experimental Psychology: Human Perception and Performance, 16(3), 479–491.Google Scholar
Cha, M.Y. & Gero, J.S. (1998). Shape pattern recognition using a computable shape pattern representation. In Artificial Intelligence in Design '98 (Gero, J.S. & Sudweeks, F., Eds.), pp. 169–188. Dordrecht: Kluwer.
Cha, M.Y. & Gero, J.S. (1999). Style learning: inductive generalisation of architectural shape patterns. In Architectural Computing from Turing to 2000. Proc. eCAADe 99 (Brown, A., Knight, M. & Berridge, P., Eds.), pp. 629–644. Liverpool: University of Liverpool.
Chan, C.-S. (2000). Can style be measured? Design Studies, 21(2), 277–291.Google Scholar
Chan, C.-S. (2001). An examination of the forces that generate a style. Design Studies, 22(2), 319–346.Google Scholar
Ding, L. & Gero, J.S. (2001). The emergence of the representation of style in design. Planning and Environment B: Planning and Design, 28(5), 707–731.Google Scholar
Dorst, K. & Cross, N.G. (2001). Creativity in the design process: co-evolution of problem-solution. Design Studies, 22(3), 425–438.Google Scholar
Dunbar, K. (2001). The analogical paradox: why analogy is so easy in naturalistic settings yet so difficult in the psychological laboratory. In The Analogical Mind: Perspectives From Cognitive Science (Gentner, D., Holyoak, K.J. & Kokinov, B.N., Eds.), pp. 313–334. Cambridge, MA: MIT Press.
Eckert, C.M. (2001). The communication bottleneck in knitwear design: analysis and computing solutions. Computer Supported Cooperative Work, 10(1), 29–74.Google Scholar
Eckert, C.M. & Stacey, M.K. (2000). Sources of inspiration: a language of design. Design Studies, 21(3), 523–538.Google Scholar
Eckert, C.M. & Stacey, M.K. (2001). Designing in the context of fashion—designing the fashion context. In Design in Context: Proc. Fifth Design Thinking Research Symp., pp. 113–129. Delft: Delft University Press.
Eckert, C.M. & Stacey, M.K. (2003). Sources of inspiration in industrial practice. The case of knitwear design. Journal of Design Research, 3. Available online at http://jdr.tudelft.nlGoogle Scholar
Edelman, S., Hiles, B.P., Yang, H., & Intrator, N. (2001). Probabilistic principles in unsupervised learning of visual structure: human data and a model. In Proc. 2001 Conf. Neural Information Processing Systems (Becker, S., Ed.). Cambridge, MA: MIT Press.
Edwards, A.T. (1945). Style and Composition in Architecture. London: John Tiranti.
Egan, D.E. & Schwartz, B.J. (1979). Chunking in recall of symbolic drawings. Memory & Cognition, 7(1), 149–158.Google Scholar
Filoteo, J.V., Maddox, W.T., & Davis, J.D. (2001). Quantitative modeling of category learning in amnesiac patients. Journal of the International Neuropsychological Society, 7(1), 1–19.Google Scholar
Freyd, J. & Tversky, B. (1984). The force of symmetry in form perception. American Journal of Psychology, 97(1), 109–126.Google Scholar
Gentner, D. (1983). Structure-mapping: a theoretical framework for analogy. Cognitive Science, 7(1), 155–170.Google Scholar
Gentner, D. & Markman, A.B. (1997). Structural alignment in analogy and similarity. American Psychologist, 52(1), 45–56.Google Scholar
Gentner, D., Rattermann, M.J., & Forbus, K.D. (1993). The roles of similarity in transfer: separating retrievability from inferential soundness. Cognitive Psychology, 25(3), 524–575.Google Scholar
Gero, J.S. (2002). Towards a theory of designing as situated acts. Int. Conf. Sciences of Design, Lyon, France.
Gero, J.S. & Kannengiesser, U. (2004). The situated function–behaviour–structure framework. Design Studies, 25(3), 373–391.Google Scholar
Gobet, F. & Simon, H.A. (1998). Expert chess memory: revisiting the chunking hypothesis. Memory, 6(2), 225–255.Google Scholar
Goldmeier, E. (1936/1972). Similarity in visually perceived forms. Psychological Issues, 8, monograph 29.Google Scholar
Goldschmidt, G. (1991). The dialectics of sketching. Creativity Research Journal, 4(1), 123–143.Google Scholar
Goldschmidt, G. (1998). Creative architectural design: reference versus precedence. Journal of Architectural and Planning Research, 15(2), 258–270.Google Scholar
Goldstone, R.L. (1994a). Influences of categorization on perceptual discrimination. Journal of Experimental Psychology: General, 123(1), 178–200.Google Scholar
Goldstone, R.L. (1994b). Similarity, interactive activation, and mapping. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(1), 3–28.Google Scholar
Goldstone, R.L. (1996). Alignment-based nonmonotonicities in similarity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(6), 988–1001.Google Scholar
Goldstone, R.L. (1998). Perceptual learning. Annual Review of Psychology, 49, 585–612.Google Scholar
Goldstone, R.L. (2000). Unitization during category learning. Journal of Experimental Psychology: Human Perception and Performance, 26(1), 86–112.Google Scholar
Goldstone, R.L. (2003). Learning to perceive while perceiving to learn. In Perceptual Organization in Vision: Behavioral and Neural Perspectives (Kimchi, R., Behrmann, M. & Olson, C., Eds.), pp. 233–278. Mahwah, NJ: Erlbaum.
Goldstone, R.L., Lippa, Y., & Shiffrin, R.M. (2001). Altering object representations through category learning. Cognition, 78(1), 27–43.Google Scholar
Goldstone, R.L. & Medin, D.L. (1994). The time course of comparison. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(1), 29–50.Google Scholar
Goldstone, R.L., Medin, D.L., & Gentner, D. (1991). Relational similarity and the non-independence of features in similarity judgments. Cognitive Psychology, 23(2), 222–264.Google Scholar
Goldstone, R.L., Medin, D.L., & Halberstadt, J. (1997). Similarity in context. Memory & Cognition, 25(2), 237–255.Google Scholar
Goldstone, R.L. & Son, J.Y. (2005). Similarity. In Cambridge Handbook of Thinking and Reasoning (Holyoak, K.J. & Morrison, R., Eds.), pp. 3–36. Cambridge: Cambridge University Press.
Goldstone, R.L., Steyvers, M., & Rogosky, B.J. (2003). Conceptual interrelatedness and caricatures. Memory & Cognition, 31(1), 169–180.Google Scholar
Henderson, J.M., Polatsek, A., & Rayner, K. (1989). Covert visual attention and extrafoveal information use during object identification. Perception and Psychophysics, 45(1), 196–208.Google Scholar
Hofstadter, D. & McGraw, G. (1995). Letter Spirit: esthetic perception and creative play in the rich microcosm of the Roman alphabet. In Fluid Concepts and Creative Analogies (Hofstadter & D., The Fluid Analogies Research Group, Eds.), pp. 407–466. New York: Basic Books.
Holyoak, K.J. & Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science, 13(2), 295–355.Google Scholar
Huber, L., Troje, N.F., Loidolt, M., & Aust, U. (2000). Natural categorization through multiple feature learning in pigeons. Quarterly Journal of Experimental Psychology, 53B(3), 343–357.Google Scholar
Johnson-Laird, P.N. (1983). Mental Models. Cambridge, MA: Harvard University Press.
Johnson-Laird, P.N., Girotto, V., & Legrenzi, P. (2004). Reasoning from consistency to consistency. Psychological Review, 111(4), 640–661.Google Scholar
Jupp, J. & Gero, J.S. (2004). Qualitative representation and reasoning in design: a hierarchy of shape and spatial languages. In Visual and Spatial Reasoning in Design III (Gero, J.S., Tversky, B. & Knight, T.W., Eds.), pp. 139–163. Cambridge, MA: MIT Press.
Jupp, J. & Gero, J.S. (2006). Visual style: qualitative and context-dependent categorization. Artificial Intelligence in Engineering Design, Analysis and Manufacturing, 20(3), 247–266.Google Scholar
Kaiser, S.B. (1997). The Social Psychology of Clothing. New York: Fairchild Publications.
Knight, T.W. (1994). Transformations in Design: A Formal Approach to Stylistic Change and Innovation in the Visual Arts. Cambridge: Cambridge University Press.
Koile, K. (2004). An intelligent assistant for conceptual design. In Design Computation and Cognition, DCC'04 (Gero, J.S., Ed.), pp. 3–22. Cambridge, MA: Kluwer Academic.
Koile, K. (2006). Formalizing abstract characteristics of style. Artificial Intelligence in Engineering Design, Analysis and Manufacturing, 20(3), 267–285.Google Scholar
Koning, H. & Eizenberg, J. (1981). The language of the prairie: Frank Lloyd Wright's Prairie houses. Environment and Planning B: Planning and Design, 8(3), 295–323.Google Scholar
Koriat, A., Goldsmith, M., & Pansky, A. (2000). Towards a psychology of memory accuracy. Annual Review of Psychology, 51(4), 481–537.Google Scholar
Kosslyn, S.M. (1980). Image and Mind. Cambridge, MA: Harvard University Press.
Kosslyn, S.M. (1994). Image and Brain. Cambridge, MA: MIT Press.
Kroes, P. (2002). Design methodology and the nature of technical artifacts. Design Studies, 23(2), 287–302.Google Scholar
Lamberts, K. & Shanks, D.R., Eds. (1997). Knowledge, Concepts, and Categories. Hove: Psychology Press.
Lawson, B.R. (2004). Schemata, gambits and precedent: some factors in design expertise. Design Studies, 25(4), 443–457.Google Scholar
Lesgold, A., Rubinstein, H., Feltovich, P., Glaser, R., Klopfer, D., & Wang, Y. (1988). Expertise in a complex skill: diagnosing x-ray pictures. In The Nature of Expertise (Chi, M.T.H., Glaser, R. & Farr, M.J., Eds.), pp. 311–342. Hillsdale, NJ: Erlbaum.
Loula, F., Kourtzi, Z., & Shiffrar, M. (2000). Surface segmentation cues influence negative priming for novel and familiar shapes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(8), 929–944.Google Scholar
Love, B.C. (2002). Comparing supervised and unsupervised category learning. Psychonomic Bulletin and Review, 9(7), 829–835.Google Scholar
Love, B.C. (2003). The multifaceted nature of unsupervised category learning. Psychonomic Bulletin and Review, 10(2), 190–197.Google Scholar
Lurie, A. (1981). The Language of Clothes. New York: Random House.
Lynch, E., Coley, J.D., & Medin, D.L. (2000). Tall is typical: central tendency, ideal dimensions and graded category structure among tree experts and novices. Memory & Cognition, 28(1), 41–50.Google Scholar
Maddox, W.T. & Ashby, F.G. (2004). Dissociating explicit and procedural-learning based systems of perceptual category learning. Behavioural Processes, 66(2), 309–332.Google Scholar
Markman, A.B. & Gentner, D. (1993). Structural alignment during similarity comparisons. Cognitive Psychology, 25(4), 431–467.Google Scholar
Markman, A.B. & Gentner, D. (1996). Commonalities and differences in similarity comparisons. Memory & Cognition, 24(2), 235–249.Google Scholar
Markman, A.B. & Gentner, D. (1997). The effects of alignability on memory. Psychological Science, 8(3), 363–367.Google Scholar
Markman, A.B. & Gentner, D. (2005). Nonintentional similarity processing. In The New Unconscious (Hassin, T., Bargh, J. & Uleman, J., Eds.), pp. 107–137. New York: Oxford University Press.
McCormack, J.P., Cagan, J., & Vogel, C.M. (2004). Speaking the Buick language: capturing, understanding and exploring brand identity with shape grammars. Design Studies, 25(1), 1–29.Google Scholar
McCracken, G. (1988). Culture and Consumption: New Approaches to the Symbolic Character of Consumer Goods and Activities. Bloomington, IN: Indiana University Press.
McGraw, G. (1995). Letter Spirit (part one): emergent high-level perception of letters using fluid concepts. PhD Thesis. Indiana University.
McGraw, G., Rehling, J., & Goldstone, R.L. (1994). Letter perception: toward a conceptual approach. Proc. 16th Annual Conf. Cognitive Science Society, pp. 613–618, Georgia Institute of Technology, Atlanta.
McMahon, J.A. (2003). Perceptual constraints and perceptual schemata: the possibility of perceptual style. Journal of Aesthetics and Art Criticism, 61(2), 259–272.Google Scholar
McNeill, T., Gero, J.S., & Warren, J. (1999). Understanding conceptual electronic design using protocol analysis. Research in Engineering Design, 10(1), 129–140.Google Scholar
Medin, D.L., Goldstone, R.L., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100(2), 254–278.Google Scholar
Medin, D.L., Lynch, E.B., & Solomon, K.O. (2000). Are there kinds of concepts? Annual Review of Psychology, 51(1), 121–147.Google Scholar
Melara, R.D. & Marks, L.E. (1990). Dimensional interactions in language processing: investigating directions and levels of crosstalk. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(3), 539–554.Google Scholar
Myles-Worsley, M., Johnson, & W.A., Simons M.A. (1988). The influence of expertise on X-ray image processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(3), 553–557.Google Scholar
Norman, D.A. (1988). The Psychology of Everyday Things. New York: Basic Books.
Oxman, R.E. (1990). Prior knowledge in design: a dynamic knowledge-based model of design and creativity. Design Studies, 11(1), 17–28.Google Scholar
Palmeri, T.J. & Gauthier, I. (2004). Visual object understanding. Nature Reviews Neuroscience, 5(2), 291–304.Google Scholar
Palmeri, T.J., Wong, A.C.-N., & Gauthier, I. (2004). Computational approaches to the development of perceptual expertise. Trends in Cognitive Sciences, 8(3), 378–386.Google Scholar
Prentice, W.C.H. (1954). Visual recognition of verbally labeled figures. American Journal of Psychology, 67(2), 315–320.Google Scholar
Pugliese, M. & Cagan, J. (2001). Capturing a rebel: modeling the Harley-Davidson brand through a motorcycle shape grammar. Research in Engineering Design, 13(1), 139–156.Google Scholar
Rehder, B. & Hastie, R. (2004). Category coherence and category-based property induction. Cognition, 91(1), 113–153.Google Scholar
Rehling, J. (2000). Letter Spirit (part two): modeling creativity in a visual domain. PhD Thesis. Indiana University.
Rehling, J. & Hofstadter, D. (2004). Letter Spirit: a model of visual creativity. In Proc. 6th Int. Conf. Cognitive Modeling, Pittsburgh, PA.
Saiki, J. & Hummel, J.E. (1996). Attribute conjunctions and the part configuration advantage in object category learning. Journal of Experimental Psychology: Learning, Memory and Cognition, 22(4), 1002–1019.Google Scholar
Schank, R.C. (1982). Dynamic Memory: A Theory of Reminding and Learning in Computers and People. Cambridge: Cambridge University Press.
Schank, R.C. & Abelson, R. (1977). Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Erlbaum.
Schapiro, M. (1961). Style. In Aesthetics Today (Philipson, M. & Grudel, P.J., Eds.), pp. 137–171. New York: New American Library.
Schön, D.A. (1988). Designing: rules, types and worlds. Design Studies, 9(1), 181–190.Google Scholar
Schön, D.A. & Wiggins, G. (1992). Kinds of seeing and their functions in designing. Design Studies, 13(1), 135–156.Google Scholar
Shiffrin, R.M. & Lightfoot, N. (1997). Perceptual learning of alphanumeric-like characters. In The Psychology of Learning and Motivation (Goldstone, R.L., Schyns, P.G. & Medin, D.L., Eds.), Vol. 36, pp. 45–82. San Diego, CA: Academic Press.
Simmel, G. (1904). Fashion. International Quarterly, 10(1), 130–155.Google Scholar
Simon, H.A. (1975). Style in design. In Spatial Synthesis in Computer-Aided Building Design (Eastman, C., Ed.), pp. 287–309. London: Applied Science.
Sloman, S.A., Love, B.C., & Ahn, W. (1998). Feature centrality and conceptual coherence. Cognitive Science, 22(1), 189–228.Google Scholar
Sloman, S.A. & Malt, B.C. (2003). Artifacts are not ascribed essences, nor are they treated as belonging to kinds. Language and Cognitive Processes, 18(4), 563–582.Google Scholar
Smith, E.E., Patalano, A.L., & Jonides, J. (1998). Alternative strategies of categorization. Cognition, 65(1), 167–196.Google Scholar
Smith, E.E. & Sloman, S.A. (1994). Similarity- versus rule-based categorization. Memory and Cognition, 22(3), 377–386.Google Scholar
Smithers, T. (1996). On knowledge level theories of design process. In Artificial Intelligence in Design '96 (Gero, J.S. & Sudweeks, F., Eds.), pp. 561–579. Dordrecht: Kluwer Academic.
Solso, R.L. (1994). Cognition and the Visual Arts. Cambridge, MA: Bradford Books/MIT Press.
Sproles, G.B. & Burns, L.D. (1994). Changing Appearances: Understanding Dress in Contemporary Society. New York: Fairchild Publications.
Stiny, G. & Mitchell, W.J. (1978). The Palladian grammar. Environment and Planning B: Planning and Design, 5(1), 5–18.Google Scholar
Tarr, M.J. (1995). Rotating objects to recognize them: a case study in of the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonomic Bulletin and Review, 2(1), 55–82.Google Scholar
Thagard, P. (1989). Explanatory coherence. Behavioral and Brain Sciences, 12(3), 435–467.Google Scholar
Thagard, P. & Verbeurgt, K. (1998). Coherence as constraint satisfaction. Cognitive Science, 22(1), 1–24.Google Scholar
Treisman, A. (1991). Search, similarity, and integration of features between and within dimensions. Journal of Experimental Psychology: Human Perception and Performance, 17(3), 652–676.Google Scholar
Treisman, A. (1993). The perception of features and objects. In Attention: Selection, Awareness and Control. A Tribute to Donald Broadbent (Baddeley, A.D. & Weiskrantz, L., Eds.), pp. 5–35. Oxford: Clarendon Press.
Treisman, A. & Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 14(1), 107–141.Google Scholar
Tversky, A. (1977). Features of similarity. Psychological Review, 84(2), 327–352.Google Scholar
Tversky, B. (2005). Visuospatial reasoning. In Cambridge Handbook of Thinking and Reasoning (Holyoak, K.J. & Morrison, R., Eds.), pp. 209–240. Cambridge: Cambridge University Press.
Wisniewski, E.J. & Medin, D.L. (1994). On the interaction of theory and data in concept learning. Cognitive Science, 18(2), 221–281.Google Scholar
Wulf, F. (1922). Beitrage zur Psychologie der Gestalt: VI. über die Veränderung von Vorstellungen (Gedächtniss und Gestalt). Psychologische Forschung, 1(2), 333–375.Google Scholar