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Diagrams 2014: Diagrammatic Representation and Inference pp 161-175 | Cite as

Recognising, Knowing and Naming: Can Object Picture Processing Models Accommodate Non-Picture Visuals?

  • Richard Cox
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8578)


This paper provides an overview of information processing accounts of pictures of objects and of non-picture visuals (NPVs) such as graphs and diagrams, including theories of graph comprehension. Compared to the study of objects, there appear to be rather few information processing studies of NPVs. An NPV corpus was developed and items were used as visual stimuli in four cognitive tasks. The tasks assessed perceptual level processing (NPV recognition), semantic knowledge and lexical production (naming). The results are discussed in relation to several questions: How well do models of object picture processing accommodate the findings from this study of NPV processing? To what extent can NPVs be considered to be another class of object pictures? Are well-established phenomena in the visual object domain such as frequency and age of acquisition effects observed for NPVs? How do patterns of performance on the perceptual, semantic and naming tasks differ across NPV item sub-classes? The results show that performance patterns across a range of cognitive tasks utilizing NPV stimuli are - to some degree - similar to those seen in object picture processing. Age of acquisition effects were also observed. It is concluded that the use of experimental paradigms from studies of object picture processing are useful for understanding how people understand and use non-pictorial graphical representations such as diagrams.


information processing cognitive processing diagrams external representations graph comprehension object recognition picture naming age of acquisition 


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  1. 1.
    Humphreys, G.W., Riddoch, M.J.: Visual object processing: A cognitive neuropsychological approach. Lawrence Erlbaum Associates, Hillsdale (1987)Google Scholar
  2. 2.
    Shah, P., Freedman, E.G., Vekiri, I.: The comprehension of quantitative information in graphical displays. In: Shah, P., Miyake, A. (eds.) The Cambridge Handbook of Visuospatial Thinking, pp. 426–476. Cambridge University Press (2005)Google Scholar
  3. 3.
    Pinker, S.: A theory of graph comprehension. In: Freedle, R. (ed.) Artificial Intelligence and the Future of Testing, pp. 73–126. Lawrence Erlbaum Associates, Hillsdale (1990)Google Scholar
  4. 4.
    Cripwell, K.R.: Non-picture visuals for communication in health learning manuals. Health Education Research 4(3), 297–304 (1989)CrossRefGoogle Scholar
  5. 5.
    Baddeley, A.: Working memory, thought, and action. Oxford University Press (2007)Google Scholar
  6. 6.
    Snodgrass, J.G., Vanderwart, M.: A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology: Human Learning and Memory 6, 174–215 (1980)Google Scholar
  7. 7.
    Johnston, R.A., Dent, K., Humphreys, G., Barry, C.: British-English norms and naming times for a set of 539 pictures: The role of age of acquisition. Behavior Research Methods 42(2), 461–469 (2010)CrossRefGoogle Scholar
  8. 8.
    Morrison, C., Hirsh, K.W., Duggan, G.B.: Age of acquisition, ageing, and verb production: Normative and experimental data. The Quarterly Journal of Experimental Psychology 56(4), 705–730 (2003)CrossRefGoogle Scholar
  9. 9.
    Johnston, R.A., Barry, C.: Age of acquisition and lexical processing. Visual Cognition 13(7/8), 789–845 (2006)CrossRefGoogle Scholar
  10. 10.
    Garcia Garcia, G., Cox, R.: Diagrams in the UK national school curriculum. In: Stapleton, G., Howse, J., Lee, J. (eds.) Diagrams 2008. LNCS (LNAI), vol. 5223, pp. 360–363. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  11. 11.
    Cleveland, W.S., McGill, R.: Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association 79(387), 531–554 (1984)CrossRefGoogle Scholar
  12. 12.
    Canham, M., Hegarty, M.: Effects of knowledge and display design on comprehension of complex graphics. Learning & Instruction 20(2), 155–166 (2010)CrossRefGoogle Scholar
  13. 13.
    Shah, P., Freedman, E.G.: Bar and line graph comprehension: An interaction of top-down and bottom-up processes. Topics in Cognitive Science, 1–19 (2009)Google Scholar
  14. 14.
    Shah, P., Hoeffner, J.: Review of graph comprehension research: Implications for instruction. Educational Psychology Review 14(1), 47–69 (2002)CrossRefGoogle Scholar
  15. 15.
    Lohse, J.: A cognitive model for the perception and understanding of graphs. Human-Computer Interaction 8, 353–388 (1993)CrossRefGoogle Scholar
  16. 16.
    Trafton, J.G., Trickett, S.B.: A new model of graph and visualization usage. In: Moore, J.D., Stenning, K. (eds.) Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 1048–1053. Lawrence Erlbaum Associates, Mahweh (2001)Google Scholar
  17. 17.
    Novick, L.R., Hurley, S.M.: To matrix, network or hierarchy: That is the question. Cognitive Psychology 42, 158–216 (2001)CrossRefGoogle Scholar
  18. 18.
    Tversky, B.: Spatial schemas in depictions. In: Gattis, M. (ed.) Spatial Schemas in Abstract Thought, pp. 79–111. MIT Press (2001)Google Scholar
  19. 19.
    Hollands, J.G., Spence, I.: The discrimination of graphical elements. Applied Cognitive Psychology 15, 413–431 (2001)CrossRefGoogle Scholar
  20. 20.
    Trickett, S.B., Trafton, J.G.: Toward a comprehensive model of graph comprehension: Making the case for spatial cognition. In: Barker-Plummer, D., Cox, R., Swoboda, N. (eds.) Diagrams 2006. LNCS (LNAI), vol. 4045, pp. 286–300. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    Tabachneck-Schijf, H.J.M., Leonardo, A.M., Simon, H.A.: CaMeRa: A computational model of multiple representations. Cognitive Science 21(3), 305–350 (1998)CrossRefGoogle Scholar
  22. 22.
    Leinhardt, G., Zaslavsky, O., Stein, M.K.: Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research 60(1), 1–64 (1990)CrossRefGoogle Scholar
  23. 23.
    Garcia Garcia, G., Cox, R.: “Graph-as-picture” misconceptions in young students. In: Goel, A.K., Jamnik, M., Narayanan, N.H. (eds.) Diagrams 2010. LNCS (LNAI), vol. 6170, pp. 310–312. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  24. 24.
    Cox, R., Romero, P., du Boulay, B., Lutz, R.: A cognitive processing perspective on student programmers’ ‘Graphicacy’. In: Blackwell, A.F., Marriott, K., Shimojima, A. (eds.) Diagrams 2004. LNCS (LNAI), vol. 2980, pp. 344–346. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  25. 25.
    Grawemeyer, B., Cox, R.: The effects of users’ background diagram knowledge and task characteristics upon information display selection. In: Stapleton, G., Howse, J., Lee, J. (eds.) Diagrams 2008. LNCS (LNAI), vol. 5223, pp. 321–334. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  26. 26.
    Lohse, G.L., Biolsi, K., Walker, N., Rueter, H.: A classification of visual representations. Communications of the ACM 37(12), 36–49 (1994)CrossRefGoogle Scholar
  27. 27.
    Cox, R.: Representation construction, externalised cognition and individual differences. Learning and Instruction 9, 343–363 (1999)CrossRefGoogle Scholar
  28. 28.
    Cox, R., Grawemeyer, B.: The mental organisation of external representations. In: Schmalhofer, F., Young, R., Katz, G. (eds.) Proceedings of the 1st European Cognitive Science Conference (EuroCogSci 2003), Lawrence Erlbaum Associates, Osnabrück (2003)Google Scholar
  29. 29.
    Twyman, M.: A schema for the study of graphical language. In: Kolers, P.A., Wrolstad, M.E., Bouma, H. (eds.) Processing of Visible Language, vol. 1, pp. 117–150. Plenum Press, New York (1979)CrossRefGoogle Scholar
  30. 30.
    Harris, R.L.: Information graphics: A comprehensive illustrated reference. OUP, Oxford (1999)zbMATHGoogle Scholar
  31. 31.
    Lockwood, A.: A visual survey of graphs, maps, charts and diagrams for the graphic designer. Studio Vista, London (1969)Google Scholar
  32. 32.
    Magnié, M.N., Besson, M., Poncet, M., Dolisi, C.: The Snodgrass and Vanderwart Set Revisited: Norms for Object Manipulability and for Pictorial Ambiguity of Objects, Chimeric Objects, and Non-objects. Journal of Clinical & Experimental Neuropsychology 25(4), 521–560 (2003)CrossRefGoogle Scholar
  33. 33.
    Cheng, P.C.-H.: Functional roles for the cognitive analysis of diagrams in problem solving. In: Cottrell, G.W. (ed.) Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society, pp. 207–212. Lawrence Erlbaum Associates, Mahweh (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Richard Cox
    • 1
  1. 1.Monash Adaptive Visualisation Lab (MArVL)Monash UniversityCaulfieldAustralia

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