The Effect of Graphical Format and Instruction on the Interpretation of Three-Variable Bar and Line Graphs

  • Nadia Ali
  • David PeeblesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10871)


We present a study that investigates how graph format and training can affect undergraduate psychology students’ ability to interpret three-variable bar and line graphs. A pre and post-test design was employed to assess 76 students’ conceptual understanding of three-variable graphs prior to and after a training intervention. The study revealed that significant differences in interpretation are produced by graph format prior to training; bar graph users outperform line graph users. Training also resulted in a statistically significant improvement in interpretation of both graph formats with effect sizes confirming the intervention resulted in substantial learning gains in graph interpretation. This resulted in bar graph users outperforming line graph users pre and post training making it the superior format even when training has occurred. The effect of graph format and training differed depending on task demands. Based on the results of this experiment, it is argued that undergraduate students’ interpretations of such three-variable data are more accurate when using the bar form. Findings also demonstrate how a brief tutorial can result in large gains in graph comprehension scores. We provide a test which can be used to assess students understanding of three-variable graphs and the tutorial developed for the study for educators to use.



This research was supported by a grant from the UK Higher Education Academy Psychology Network.


  1. 1.
    Friel, S.N., Curcio, F.R., Bright, G.W.: Making sense of graphs: critical factors influencing comprehension and instructional implications. J. Res. Math. Educ. 32, 124–158 (2001)CrossRefGoogle Scholar
  2. 2.
    National Council of Teachers of Mathematics: Principles and Standards for School Mathematics, vol. 1. National Council of Teachers (2000)Google Scholar
  3. 3.
    Glazer, N.: Challenges with graph interpretation: a review of the literature. Stud. Sci. Educ. 47(2), 183–210 (2011)CrossRefGoogle Scholar
  4. 4.
    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
  5. 5.
    Shah, P., Carpenter, P.A.: Conceptual limitations in comprehending line graphs. J. Exp. Psychol. Gen. 124, 43–62 (1995)CrossRefGoogle Scholar
  6. 6.
    Cleveland, W.S., McGill, R.: An experiment in graphical perception. Int. J. Man-Mach. Stud. 25(5), 491–500 (1986)CrossRefGoogle Scholar
  7. 7.
    Zacks, J., Tversky, B.: Bars and lines: a study of graphic communication. Mem. Cogn. 27(6), 1073–1079 (1999)CrossRefGoogle Scholar
  8. 8.
    Okan, Y., Garcia-Retamero, R., Cokely, E.T., Maldonado, A.: Improving risk understanding across ability levels: encouraging active processing with dynamic icon arrays. J. Exp. Psychol.: Appl. 21(2), 178–194 (2015)Google Scholar
  9. 9.
    Peebles, D., Ali, N.: Expert interpretation of bar and line graphs: the role of graphicacy in reducing the effect of graph format. Front. Psychol. 6, 1673 (2015)CrossRefGoogle Scholar
  10. 10.
    Peebles, D., Cheng, P.C.H.: Modeling the effect of task and graphical representation on response latency in a graph reading task. Hum. Factors 45, 28–45 (2003)CrossRefGoogle Scholar
  11. 11.
    Carswell, C.M., Wickens, C.D.: The perceptual interaction of graphical attributes: configurality, stimulus homogeneity, and object interaction. Percept. Psychophys. 47, 157–168 (1990)CrossRefGoogle Scholar
  12. 12.
    Carswell, C.M., Wickens, C.D.: Mixing and matching lower-level codes for object displays: evidence for two sources of proximity compatibility. Hum. Factors 38(1), 1–22 (1996)CrossRefGoogle Scholar
  13. 13.
    Peebles, D.: The effect of emergent features on judgments of quantity in configural and seperable displays. J. Exp. Psychol.: Appl. 14(2), 85–100 (2008)Google Scholar
  14. 14.
    Dreyfus, T., Eisenberg, T.: On difficulties with diagrams: theoretical issues. In: Booker, G., Cobb, P., de Mendicuti, T.N. (eds.) Proceedings of the 14th Annual Conference of the International Group for the Psychology of Mathematics Education, vol. 1, pp. 27–36 (1990)Google Scholar
  15. 15.
    Ali, N., Peebles, D.: The effect of gestalt laws of perceptual organisation on the comprehension of three-variable bar and line graphs. Hum. Factors 15(1), 183–203 (2013)CrossRefGoogle Scholar
  16. 16.
    Heckler, A.F.: The ubiquitous patterns of incorrect answers to science questions: the role of automatic, bottom-up processes. In: Mestre, J.P., Ross, B.H. (eds.) Psychology of Learning and Motivation: Cognition in Education, vol. 55, pp. 227–268. Academic Press, Cambridge (2011)Google Scholar
  17. 17.
    Kosslyn, S.M.: Graph Design for the Eye and Mind. Oxford University Press, New York (2006)CrossRefGoogle Scholar
  18. 18.
    Field, A.: Discovering Statistics Using SPSS, 4th edn. Sage, London (2009)zbMATHGoogle Scholar
  19. 19.
    Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth ten thousand words. Cogn. Sci. 11, 65–100 (1987)CrossRefGoogle Scholar
  20. 20.
    Peebles, D., Ali, N.: Differences in comprehensibility between three-variable bar and line graphs. In: Taatgen, N., van Rijn, H., Nerbonne, J., Schoemaker, L. (eds.) Proceedings of the Thirty-first Annual Conference of the Cognitive Science Society, Mahwah, NJ, pp. 2938–2943. Cognitive Science Society (2009)Google Scholar
  21. 21.
    Wertheimer, M.: Laws of organization in perceptual forms. In: Ellis, W.D. (ed.) A Source Book of Gestalt Psychology. Routledge & Kegan Paul, London (1938)Google Scholar
  22. 22.
    Shah, P., Mayer, R.E., Hegarty, M.: Graphs as aids to knowledge construction: signaling techniques for guiding the process of graph comprehension. J. Educ. Psychol. 91, 690–702 (1999)CrossRefGoogle Scholar
  23. 23.
    Mautone, P.D., Mayer, R.E.: Cognitive aids for guiding graph comprehension. J. Educ. Psychol. 99(3), 640–652 (2007)CrossRefGoogle Scholar
  24. 24.
    Ali, N., Peebles, D.: The different effects of thinking aloud and writing on graph comprehension. In: Carlson, L., Holscher, C., Shipley, T. (eds.) Proceedings of the Twentieth Annual Conference of the Cognitive Science Society, Mahwah, NJ. Cognitive Science Society (2011)Google Scholar
  25. 25.
    Beattie, V., Jones, M.J.: The use and abuse of graphs in annual reports: theoretical framework and empirical study. Account. Bus. Res. 22(88), 291–303 (1992)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of HuddersfieldHuddersfieldUK

Personalised recommendations