Cognitive Processing

, Volume 14, Issue 3, pp 255–272 | Cite as

Cognitive tools shape thought: diagrams in design

  • Jeffrey V. Nickerson
  • James E. Corter
  • Barbara Tversky
  • Yun-Jin Rho
  • Doris Zahner
  • Lixiu Yu
Research Report


Thinking often entails interacting with cognitive tools. In many cases, notably design, the predominant tool is the page. The page allows externalizing, organizing, and reorganizing thought. Yet, the page has its own properties that by expressing thought affect it: path, proximity, place, and permanence. The effects of these properties were evident in designs of information systems created by students Paths were interpreted as routes through components. Proximity was used to group subsystems. Horizontal position on the page was used to express temporal sequence and vertical position to reflect real-world spatial position. The permanence of designs on the page guided but also constrained generation of alternative designs. Cognitive tools both reflect and affect thought.


Diagrammatic reasoning Design Creativity Cognitive tool Affordance Spatial thinking Information systems design 



This work has been supported by awards IIS-0725223, HHC-0905417, IIS-0855995, and IIS-0968561 from the National Science Foundation, and by the Stanford Regional Visualization and Analysis Center.


  1. Akin Ö (2001) Variants in design cognition. In: Eastman C, McCracken M, Newstetter W (eds) Design knowing and learning: cognition in design education. Elsevier, Amsterdam, pp 105–124CrossRefGoogle Scholar
  2. Avital M, Lyytinen K, Boland R, Butler B, Dougherty D, Fineout M, Jansen W, Levina N, Rifkin W, Venable J (2006) Design with a positive lens: an affirmative approach to designing information and organizations. Commun Assoc Inf Syst 18:519–545Google Scholar
  3. Banks WP, Flora J (1977) Semantic and perceptual processes in symbolic comparisons. J Exp Psychol Hum Percept Perform 3(2):278PubMedCrossRefGoogle Scholar
  4. Barthélemy M (2011) Spatial networks. Phys Rep 499(1):1–101CrossRefGoogle Scholar
  5. Booch G, Rumbaugh J, Jacobson I (2005) The unified modeling language user guide, 2nd edn. Addison-Wesley, Upper Saddle River, NJGoogle Scholar
  6. Boroditsky L (2000) Metaphoric structuring: understanding time through spatial metaphors. Cognition 75(1):1–28PubMedCrossRefGoogle Scholar
  7. Carroll JM (2000) Making use: scenario-based design of human computer interactions. MIT Press, Cambridge, MAGoogle Scholar
  8. Casasanto D, Henetz T (2012) Handedness shapes children’s abstract concepts. Cogn Sci 36:359–372PubMedCrossRefGoogle Scholar
  9. Chatterjee A (2001) Language and space: some interactions. Trends Cogn Sci 5:55–61PubMedCrossRefGoogle Scholar
  10. Clark HH (1973) Space, time, semantics, and the child. In: Moore TE (ed) Cognitive development and the acquisition of language. Academic Press, NY, pp 27–63Google Scholar
  11. Cooper WE, Ross JR (1975) World order. In: Grossman RE, San LJ, Vances TJ (eds) Papers from the parasession on functionalism. Chicago Linguistic Society, Chicago, pp 63–111Google Scholar
  12. Donald M (1991) Origins of the modern mind. Harvard University Press, CambridgeGoogle Scholar
  13. Dontcheva M, Gerber E, Lewis S (2011) Crowdsourcing and creativity. CHI 2011: Crowdsourcing WorkshopGoogle Scholar
  14. Dow S, Kulkarni A, Bunge B, Nguyen T, Klemmer S, Hartmann B (2011) Shepherding the crowd: managing and providing feedback to crowd workers. In: Proceedings of the 2011 annual conference on human factors in computing systems (CHI)Google Scholar
  15. Egan DE, Schwartz BJ (1979) Chunking in recall of symbolic drawings. Mem Cogn 7:149–158CrossRefGoogle Scholar
  16. Emmorey K (2001) Language, cognition, and the brain: insights from sign language research. Erlbaum, Mahwah, NJGoogle Scholar
  17. Fish J, Scrivener S (1990) Amplifying the mind’s eye: sketching and visual cognition. Leonardo 23(1):117–126CrossRefGoogle Scholar
  18. Floyd RW (1962) Algorithm 97: shortest path. Commun ACM 5(6):345CrossRefGoogle Scholar
  19. Gick ML, Holyoak KJ (1980) Analogical problem solving. Cogn Psychol 12(3):306–355CrossRefGoogle Scholar
  20. Gick ML, Holyoak KJ (1983) Schema induction and analogical transfer. Cogn Psychol 15(1):1–38CrossRefGoogle Scholar
  21. Golden BL, Ball M (1978) Shortest paths with euclidean distances: an explanatory model. Networks 8(4):297–314CrossRefGoogle Scholar
  22. Goldin-Meadow S (2003) Hearing gesture: how our hands help us think. Belknap Press, Cambridge, MAGoogle Scholar
  23. Goldschmidt G (1991) The dialectics of sketching. Creat Res J 4(2):123–143CrossRefGoogle Scholar
  24. Goldschmidt G (1994) On visual design thinking: the vis kids of architecture. Des Stud 15(2):158–174CrossRefGoogle Scholar
  25. Hevner AR, March ST, Park J, Ram S (2004) Design science in information systems research. MIS Q 28(1):75–105Google Scholar
  26. Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice Hall, Upper Saddle River, NJGoogle Scholar
  27. Jansson DG, Smith SM (1991) Design fixation. Des Stud 12:3–11CrossRefGoogle Scholar
  28. Kaminiski JA, Sloutsky VM, Heckler AF, Sun R, Miyake N (2006) Effects of concreteness on representation: an explanation for differential transfer. In: Proceedings of the 28th annual conference of the Cognitive Science Society. Lawrence Erlbaum Associates, Hillsdale, NJ, pp 1581–1586Google Scholar
  29. Kirsh D (2010) Explaining artifact evolution. In: Malafouris L and Renfrew C (eds) The cognitive life of things: recasting the boundaries of the mind. McDonald Institute for Archaeological Research, Cambridge pp 121–144Google Scholar
  30. Kranjec A, Lehet M, Bromberger B, Chatterjee A (2010) A sinister bias for calling fouls in soccer. PLoS One 5(7). doi: 10.1371/journal.pone.0011667
  31. Kruskal JB (1964) Nonmetric multidimensional scaling: a numerical method. Psychometrika 29:115–129CrossRefGoogle Scholar
  32. Lackoff G, Johnson M (1980) Metaphors we live by. University of Chicago Press, ChicagoGoogle Scholar
  33. Landy D, Goldstone RL (2007) The alignment of order and space in arithmetic computation. In: Proceedings of the twenty-eighth annual conference of the Cognitive Science Society. Lawrence Erlbaum Associates, Hillsdale, NJ, pp 382–387Google Scholar
  34. Liddell S (2003) Sources of meaning in ASL classifier predicates. In: Emmorey K (ed) Perspectives on classifier constructions in sign language. Lawrence Erlbaum, Mahwah, NJ, pp 199–220Google Scholar
  35. Maass A, Russo A (2003) Directional bias in the mental representation of spatial events: nature or culture? Psychol Sci 14:296–301PubMedCrossRefGoogle Scholar
  36. Maass A, Pagani D, Berta E (2007) How beautiful is the goal and how violent is the fistfight? Spatial bias in the interpretation of human behavior. Soc Cogn 25:833–852CrossRefGoogle Scholar
  37. Maher ML (2010) Design creativity research: from the individual to the crowd. In: Taura T, Nagai Y (eds) Design creativity 2010. Springer, London, pp 41–47Google Scholar
  38. March S, Hevner A, Ram S (2000) Research commentary: an agenda for information technology research in heterogeneous and distributed environments. Inf Syst Res 11(4):327–341CrossRefGoogle Scholar
  39. Mayer RE (2001) Multimedia learning. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  40. Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97PubMedCrossRefGoogle Scholar
  41. Moyer R (1973) Comparing objects in memory: evidence suggesting an internal psychophysics. Percept Psychophys 13:180–184CrossRefGoogle Scholar
  42. Nickerson JV (2006) Teaching the integration of information systems technologies. IEEE Trans Educ 49:271–277CrossRefGoogle Scholar
  43. Nickerson JV, Sakamoto Y (2010) Crowdsourcing creativity: combining ideas in networks. Workshop on Information in NetworksGoogle Scholar
  44. Norman DA (1993) Things that make us smart. Addison-Wesley, Reading, MAGoogle Scholar
  45. Novick LR (1990) Representational transfer in problem solving. Psychol Sci 1(2):128CrossRefGoogle Scholar
  46. Oberlander J (1996) Grice for graphics: pragmatic implicature in network diagrams. Inf Des J 8(6):163–179Google Scholar
  47. Oppenheimer DM, Trail TE (2010) Why leaning to the left makes you lean to the left: effect of spatial orientation on political attitudes. Soc Cogn 28:651–661CrossRefGoogle Scholar
  48. Pemmaraju S, Skienna S (2003) Computational discrete mathematics: combinatorics and graph theory with mathematica. Cambridge University Press, New YorkCrossRefGoogle Scholar
  49. Peterson LL, Davie BS (2011) Computer networks: a systems approach. Morgan Kaufmann, Los Altos, CAGoogle Scholar
  50. Petre M, Green TRG (1993) Learning to read graphics: some evidence that ‘seeing’ an information display is an acquired skill. J Vis Lang Comput 4:55–70CrossRefGoogle Scholar
  51. Redmiles D, Nakakoji K (2004) Supporting reflective practitioners. In: Proceedings of the 26th international conference on software engineering (ICSE’04), pp 688–690Google Scholar
  52. Rosch E (1978) Principles of categorization. In: Rosch E, Lloyd BB (eds) Cognition and categorization. Lawrence Erlbaum Associates, Hillsdale, NJ, pp 27–48Google Scholar
  53. Rumelhart D (1980) On evaluating story grammars. Cogn Sci 4:313–316CrossRefGoogle Scholar
  54. Sanfeliu A, Fu KS (1983) A distance measure between attributed relational graphs for pattern recognition. IEEE Trans Syst Man Cybern 13(3):353–362CrossRefGoogle Scholar
  55. Schön DA (1983) The reflective practitioner: how professionals think in action. Basic Books, Jackson, TNGoogle Scholar
  56. Schrepfer M, Wolf J, Mendling J, Reijers HA (2009) The impact of secondary notation on process model understanding. Lecture Notes in Business Information Processing, 39, part 5. Springer, pp 161–175Google Scholar
  57. Schubert T (2005) Your highness: vertical positions as perceptual symbols of power. J Pers Soc Psychol 89(1):1–21PubMedCrossRefGoogle Scholar
  58. Schubert TW, Waldzus S, Seibt B (2008) The embodiment of power and communalism in space and bodily contact. In: Semin GR, Smith ER (eds) Embodied grounding: social, cognitive, affective, and neuroscientific approaches. Cambridge University Press, New York, pp 160–183CrossRefGoogle Scholar
  59. Simon HA (1969) The sciences of the artificial. MIT Press, Cambridge, MAGoogle Scholar
  60. Smith SM, Blankenship E (1991) Incubation and the persistence of fixation in problem solving. Am J Psychol 104:61–87PubMedCrossRefGoogle Scholar
  61. Sokal RR, Rohlf FJ (1962) The comparison of dendrograms by objective methods. Taxon 11:33–40CrossRefGoogle Scholar
  62. Suwa M, Tversky B (1997) What do architects and students perceive in their design sketches? A protocol analysis. Des Stud 18:385–403CrossRefGoogle Scholar
  63. Suwa M, Tversky B (2001) Constructive perception in design. In: Gero JS, Maher ML (eds) Computational and cognitive models of creative design. University of Sydney, Sydney, pp 227–239Google Scholar
  64. Suwa M, Tversky B (2003) Constructive perception: a skill for coordinating perception and conception. In: Alterman R, Kirsh D (eds) Proceedings of the 25 annual meeting of the Cognitive Science Society. Cognitive Science Society, Boston, pp 1140–1145Google Scholar
  65. Suwa M, Tversky B, Gero J, Purcell T (2001) Seeing into sketches: regrouping parts encourages new interpretations. In: Gero JS, Tversky B, Purcell T (eds) Visual and spatial reasoning in design Sydney. Key Centre of Design Computing and Cognition, Australia, pp 207–219Google Scholar
  66. Talmy L (2000) Toward a cognitive semantics. MIT Press, Cambridge, MAGoogle Scholar
  67. Talmy L (2003) The representation of spatial structure in spoken and signed language. In: Emmorey K (ed) Perspectives on classifier constructions in sign language. Lawrence Erlbaum, Mahwah, NJ, pp 311–332Google Scholar
  68. Talmy L (2005) The fundamental system of spatial schemas in language. In: Hampe B, Grady JE (eds) From perception to meaning: Image schemas in cognitive linguistics, Cognitive Linguistics Research 29. Mouton de Gruyter, Berlin/New York, pp 199–234CrossRefGoogle Scholar
  69. Taylor HA, Tversky B (1992) Descriptions and depictions of environments. Mem Cogn 20:483–496CrossRefGoogle Scholar
  70. Tversky B (1995) Cognitive origins of graphic conventions. In: Marchese FT (ed) Understanding images. Springer, New York, pp 29–53CrossRefGoogle Scholar
  71. Tversky B (2001) Spatial schemas in depictions. In: Gattis M (ed) Spatial schemas and abstract thought. MIT Press, Cambridge, MA, pp 79–111Google Scholar
  72. Tversky B (2011a) Spatial thought, social thought. In: Schubert T, Maass A (eds) Spatial dimensions of social thought. Mouton de Gruyter, Berlin, pp 17–38Google Scholar
  73. Tversky B (2011b) Visualizations of thought. Top Cogn Sci 3:499–535CrossRefGoogle Scholar
  74. Tversky B, Suwa M (2009) Thinking with sketches. In: Markman AB, Wood KL (eds) Tools for innovation. Oxford University Press, Oxford, pp 75–84CrossRefGoogle Scholar
  75. Tversky B, Kugelmass S, Winter A (1991) Cross-cultural and developmental trends in graphic productions. Cogn Psychol 23:515–557CrossRefGoogle Scholar
  76. Tversky B, Zacks J, Lee PU, Heiser J (2000) Lines, blobs, crosses, and arrows: diagrammatic communication with schematic figures. In: Anderson M, Cheng P, Haarslev V (eds) Theory and application of diagrams. Springer, Berlin, pp 221–230CrossRefGoogle Scholar
  77. Tversky B, Heiser J, Lee P, Daniel MP (2009) Explanations in gesture, diagram, and word. In: Coventry KR, Tenbrink T, Bateman J (eds) Spatial language and dialogue. Oxford University Press, Oxford, pp 119–131CrossRefGoogle Scholar
  78. Wand Y, Weber R (1993) On the ontological expressiveness of information systems analysis and design grammars. Inf Syst J 3(4):217–237CrossRefGoogle Scholar
  79. Winograd T (1996) Bringing design to software. Addison-Wesley, BostonGoogle Scholar
  80. Yu L, Nickerson JV (2011) Cooks or cobblers? Crowd creativity through combination. In: Proceedings of the 2011 annual conference on human factors in computing systems (CHI)Google Scholar
  81. Yu L, Nickerson JV (2013) An Internet scale idea generation system. ACM Trans Interact Intell Syst 3(1). Art 2Google Scholar
  82. Zacks J, Tversky B (2001) Event structure in perception and conception. Psychol Bull 127(1):3–21PubMedCrossRefGoogle Scholar

Copyright information

© Marta Olivetti Belardinelli and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jeffrey V. Nickerson
    • 1
  • James E. Corter
    • 2
  • Barbara Tversky
    • 2
  • Yun-Jin Rho
    • 2
    • 4
  • Doris Zahner
    • 1
    • 3
  • Lixiu Yu
    • 1
    • 5
  1. 1.Center for Decision TechnologiesStevens Institute of TechnologyHobokenUSA
  2. 2.Department of Human Development, Teachers CollegeColumbia UniversityNew YorkUSA
  3. 3.Council for Aid to EducationNew YorkUSA
  4. 4.Pearson EducationBostonUSA
  5. 5.Human-Computer Interaction Institute, Carnegie Mellon UniversityPittsburghUSA

Personalised recommendations