Elucidating the Mechanism of Spontaneous Diagram Use in Explanations: How Cognitive Processing of Text and Diagrammatic Representations Are Influenced by Individual and Task-Related Factors

  • Emmanuel Manalo
  • Yuri Uesaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7352)


Although diagrams are considered effective tools for communication, students have been reported as lacking sufficient spontaneity in using diagrams when explaining what they have learned. This study examined the possible mechanism that relates text to diagram production in the process of providing written explanations. It puts forward the hypothesis that the production of text and diagrammatic representations shares the same cognitive processing resources, the allocation of which is influenced by individual factors like language ability and task-related factors like imageability of what needs to be explained. This hypothesis was tested on Japanese university students who were administered a passage (two versions varying in imageability) to read and subsequently explain in English or Japanese. A significant correlation was found between diagram use and English language competence (measured by TOEIC scores) - but only among students asked to explain the passage with lower imageability, and in English, providing support for the hypothesis.


spontaneous diagram use text and diagrammatic representations explanation cognitive processing resources communication 


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  1. 1.
    Larkin, J.H., Simon, H.A.: Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science 11, 65–99 (1987)CrossRefGoogle Scholar
  2. 2.
    Ainsworth, S., Prain, V., Tytler, R.: Drawing to Learn in Science. Science 333, 1096–1097 (2011)CrossRefGoogle Scholar
  3. 3.
    Manalo, E., Uesaka, Y.: Drawing Attention to Diagram Use. Science 334, 761 (2011)CrossRefGoogle Scholar
  4. 4.
    Grawemeyer, B., Cox, R.: The Effect of Knowledge-of-External-Representations Upon Performance and Representational Choice in a Database Query Task. In: Blackwell, A., Marriott, K., Shimojima, A. (eds.) Diagrams 2004. LNCS (LNAI), vol. 2980, pp. 351–354. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Uesaka, Y., Manalo, E.: Active Comparison as a Means of Promoting the Development of Abstract Conditional Knowledge and Appropriate Choice of Diagrams in Math Word Problem Solving. In: Barker-Plummer, D., Cox, R., Swoboda, N. (eds.) Diagrams 2006. LNCS (LNAI), vol. 4045, pp. 181–195. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Bowen, G.M., Roth, W.-M.: Why Students Not Learn to Interpret Scientific Inscriptions. Research in Science Education 32, 303–327 (2002)CrossRefGoogle Scholar
  7. 7.
    Dufour-Janvier, B., Bednarz, N., Belanger, M.: Pedagogical Considerations Concerning the Problem of Representation. In: Janvier, C. (ed.) Problems of Representation in the Teaching and Learning of Mathematics, pp. 110–120. Erlbaum, Hillsdale (1987)Google Scholar
  8. 8.
    Kozhevnikov, M., Motes, M.A., Hegarty, M.: Spatial Visualization in Physics Problem Solving. Cognitive Science 31, 549–579 (2007)CrossRefGoogle Scholar
  9. 9.
    Mokros, J.R., Tinker, R.F.: The Impact of Microcomputer-Based Labs on Children’s Ability to Interpret Graphs. Journal of Research in Science Teaching 24, 369–383 (1987)CrossRefGoogle Scholar
  10. 10.
    Ichikawa, S.: Suugakuteki na Kangaekata wo Megutte no Soudan to Sidou [Case Report of Cognitive Counseling in Mathematical Thinking]. In: Ichikawa, S. (ed.) Gakusyuu wo Sasaeru Nintikaunsering: Shinrigaku to Kyouiku no Aratana Setten [Cognitive Counseling that Supports Learning: A New Approach Bridging Psychology and Education], pp. 36–61. Brain Press, Tokyo (1993)Google Scholar
  11. 11.
    Manalo, E., Uesaka, Y.: Quantity and Quality of Diagrams Used in Math Word Problem Solving: A Comparison Between New Zealand and Japanese Students. Refereed Papers of the NZARE (New Zealand Association for Research in Education) National Conference 2006. NZARE, Wellington. ERIC Document Reproduction Service No. ED518280 (2006)Google Scholar
  12. 12.
    Uesaka, Y., Manalo, E., Ichikawa, S.: What Kinds of Perceptions and Daily Learning Behaviors Promote Students’ Use of Diagrams in Mathematics Problem Solving? Learning and Instruction 17, 322–335 (2007)CrossRefGoogle Scholar
  13. 13.
    Uesaka, Y., Manalo, E., Ichikawa, S.: The Effects of Perception of Efficacy and Diagram Construction Skills on Students’ Spontaneous Use of Diagrams When Solving Math Word Problems. In: Goel, A.K., Jamnik, M., Narayanan, N.H. (eds.) Diagrams 2010. LNCS (LNAI), vol. 6170, pp. 197–211. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  14. 14.
    Manalo, E., Uesaka, Y., Pérez-Kriz, S., Kato, M., Fukaya, T.: Science and Engineering Students’ Use of Diagrams During Note Taking Versus Explanation. Educational Studies (2012), doi:10.1080/03055698.2012.680577Google Scholar
  15. 15.
    Mayer, R.E.: Multimedia Learning. Cambridge University Press, New York (2001)CrossRefGoogle Scholar
  16. 16.
    Mayer, R.E., Anderson, R.B.: Animations Need Narrations: An Experimental Test of a Dual-Coding Hypothesis. Journal of Educational Psychology 83, 484–490 (1991)CrossRefGoogle Scholar
  17. 17.
    Mayer, R.E., Moreno, R.: A Split-Attention Effect in Multimedia Learning: Evidence for Dual Processing Systems in Working Memory. Journal of Educational Psychology 90, 312–320 (1998)CrossRefGoogle Scholar
  18. 18.
    Mayer, R.E., Sims, V.K.: For Whom is a Picture Worth a Thousand Words? Extensions of a Dual-Coding Theory of Multimedia Learning. Journal of Educational Psychology 84, 389–460 (1994)CrossRefGoogle Scholar
  19. 19.
    Mayer, R.E., Moreno, R.: Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist 38, 43–52 (2003)CrossRefGoogle Scholar
  20. 20.
    Baddeley, A.D.: Working Memory. Oxford University Press, Oxford (1986)Google Scholar
  21. 21.
    Baddeley, A.D.: Human Memory. Allyn & Bacon, Boston (1998)Google Scholar
  22. 22.
    Cornoldi, C., Gobbo, C., Mazzoni, G.: On Metamemory-Memory Relationship: Strategy Availability and Training. International Journal of Behavioral Development 14, 101–121 (1991)Google Scholar
  23. 23.
    Baddeley, A.D.: Personal communication, February 24 (2012)Google Scholar
  24. 24.
    Baddeley, A.D.: The Episodic Buffer: A New Component of Working Memory? Trends in Cognitive Sciences 4, 417–423 (2000)CrossRefGoogle Scholar
  25. 25.
    Chandler, P., Sweller, J.: Cognitive Load Theory and the Format of Instruction. Cognition and Instruction 8, 293–332 (1991)CrossRefGoogle Scholar
  26. 26.
    Sweller, J.: Instructional Design in Technical Areas. ACER Press, Camberwell (1999)Google Scholar
  27. 27.
    Uesaka, Y., Manalo, E.: Task-related Factors that Influence the Spontaneous Use of Diagrams in Math Word Problems. Applied Cognitive Psychology (2011), doi:10.1002/acp.1816Google Scholar
  28. 28.
  29. 29.
    Chi, M.T.H., Siler, S.A., Jeong, H., Yamauchi, T., Hausmann, R.G.: Learning from Human Tutoring. Cognitive Science 25, 471–533 (2001)CrossRefGoogle Scholar
  30. 30.
    TOEIC-ETS Home, http://www.ets.org/toeic
  31. 31.
    Ackerman, P.L.: Individual Differences in Information Processing: An Investigation of Intellectual Abilities and Task Performance During Practice. Intelligence 10, 101–139 (1986)CrossRefGoogle Scholar
  32. 32.
    Neisser, U., Boodoo, G., Bouchard, T.J., Halpern, D.E., Loehlin, J.C., Perloff, R., Sternberg, R.J., Urbina, S.: Intelligence: Knowns and Unknowns. American Psychologist 51, 77–101 (1996)CrossRefGoogle Scholar
  33. 33.
    Navon, D., Gopher, D.: On the Economy of the Human-Processing System. Psychological Review 86, 214–255 (1979)CrossRefGoogle Scholar
  34. 34.
    Norman, D.A., Bobrow, D.J.: On Data-Limited and Resource-Limited Processes. Cognitive Psychology 7, 44–64 (1975)CrossRefGoogle Scholar
  35. 35.
    Allport, G.W.: The Nature of Prejudice. Addison Wesley, New York (1954)Google Scholar
  36. 36.
    Kool, W., McGuire, J.T., Rosen, Z.B., Botvinick, M.M.: Decision Making and the Avoidance of Cognitive Demand. Journal of Experimental Psychology: General 139, 665–682 (2010)CrossRefGoogle Scholar
  37. 37.
    Mathews, N., Hunt, E., MacLeod, C.M.: Strategy Choice and Strategy Training in Sentence-Picture Verification. Journal of Verbal Learning and Verbal Behavior 19, 531–548 (1980)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Emmanuel Manalo
    • 1
  • Yuri Uesaka
    • 2
  1. 1.Faculty of Science and EngineeringWaseda UniversityTokyoJapan
  2. 2.Graduate School of EducationThe University of TokyoJapan

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