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Learning from Animated Diagrams: How Are Mental Models Built?

  • Richard Lowe
  • Jean-Michel Boucheix
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5223)

Abstract

Current approaches to the design of educational animations too often appear to be largely founded upon intuition rather than research-based principles. Animated diagrams designed to be behaviourally realistic run the risk of learners overlooking vital high relevance information that has low intrinsic perceptual salience. The information that learners extract from such representations is a poor basis upon which to build high quality dynamic mental models. For animated diagrams to be effective as tools for learning, their design should be based upon explicit and principled modeling of the way learners process such depictions. This paper synthesizes recent research to propose a theoretical framework for learners’ perceptual and conceptual processing of animated diagrams. A five-stage model is presented that characterizes the role of different levels of processing in building dynamic mental models of the depicted content.

Keywords

Animated diagrams theoretical framework perceptual and cognitive processing mental model construction complex dynamic content 

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References

  1. 1.
    Mayer, R.E.: A Cognitive Theory of Multimedia Learning. In: Mayer, R.E. (ed.) Cambridge Handbook of Multimedia Learning. Cambridge University Press, New York (2005)Google Scholar
  2. 2.
    Mayer, R.E., Sims, V.K.: For Whom is a Picture Worth a Thousand Words? Extensions of Dual-coding Theory of Multimedia Learning. Journal of Educational Psychology 86, 389–401 (1994)CrossRefGoogle Scholar
  3. 3.
    Narayanan, N.H., Hegarty, M.: On designing Comprehensible Interactive Hypermedia Manuals. International Journal of Human-Computer Studies 48, 267–301 (1998)CrossRefGoogle Scholar
  4. 4.
    Schnotz, W.: An Integrated Model of Text and Picture Comprehension. In: Mayer, R.E. (ed.) Cambridge Handbook of Multimedia Learning, pp. 49–70. Cambridge University Press, New York (2005)Google Scholar
  5. 5.
    Lowe, R.K.: Extracting Information From an Animation During Complex Visual Learning. European Journal of Psychology of Education 14, 225–244 (1999)CrossRefGoogle Scholar
  6. 6.
    Lowe, R.K.: Animation and learning: Selective Processing of Information in Dynamic Graphics. Learning and Instruction 13, 157–176 (2003)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Stenning, K.: Distinguishing Semantic from Processing Explanations of Usability of Representations: Applying Expressiveness Analysis to Animations. In: Lee, J. (ed.) Intelligence and Multimodality in Multimedia Interfaces: Research and Applications. AAAI Press, Menlo Park (1998)Google Scholar
  8. 8.
    Lowe, R.K.: Components of Expertise in the Perception and Interpretation of Meteorological Charts. In: Hoffman, R.R., Markman, A.B. (eds.) Interpreting Remote Sensing Imagery, pp. 185–206. Lewis, Boca Raton (2001)Google Scholar
  9. 9.
    Lowe, R.K.: Multimedia Learning of Meteorology. In: Mayer, R.E. (ed.) The Cambridge Handbook of Multimedia Learning, pp. 429–446. Cambridge University Press, New York (2005)Google Scholar
  10. 10.
    Boucheix, J.-M., Lowe, R.K., Soirat, A.: On-line Processing of a Complex Technical Animation: Eye Tracking Investigation During Verbal Description. Paper presented at the Text and Graphics Comprehension conference, University of Nottingham, UK (2006)Google Scholar
  11. 11.
    Lowe, R.K., Schnotz, W.: Animations and Temporal Manipulations: Supporting Comprehension of Complex Dynamic Information. In: Paper presented at the 12th European Conference for Research on Learning and Instruction, Budapest, Hungary (2007)Google Scholar
  12. 12.
    Lowe, R.K.: Learning with Animation: Lessons from Static Graphics. In: Paper presented at the 12th European Conference for Research on Learning and Instruction, Budapest, Hungary (2007)Google Scholar
  13. 13.
    Johnson-Laird, P.N.: Mental Models: Towards a Cogntive Science of Language, Inference and Consciousness. Cambridge University Press, Cambridge (1983)Google Scholar
  14. 14.
    Lowe, R.K.: Animated Documentation: A Way of Handling Complex Procedural Tasks? In: Alamargot, D., Terrier, P., Cellier, J.-M. (eds.) Written Documents in the Workplace, pp. 231–242. Elsevier, Amsterdam (2007)Google Scholar
  15. 15.
    Zacks, J.M., Tversky, B.: Event Structure in Perception and Conception. Psychological Bulletin 27, 3–21 (2001)CrossRefGoogle Scholar
  16. 16.
    Zacks, J.M., Speer, N.K., Swallow, K.M., Braver, T.S., Reynolds, J.R.: Event Perception: A Mind/Brain Perspective. Psychological Bulletin 127, 273–293 (2007)CrossRefGoogle Scholar
  17. 17.
    Wolfe, J.M., Horowitz, T.S.: What Attributes Guide the Deployment of Visual Attention and How Do They Do It? Nature Reviews Neuroscience 5, 1–7 (2004)CrossRefGoogle Scholar
  18. 18.
    Lowe, R.K., Boucheix, J.-M.: Eye Tracking as a Basis for Improving Animation Design. In: Paper presented at the 12th European Conference for Research on Learning and Instruction, Budapest, Hungary (2007)Google Scholar
  19. 19.
    Alvarez, G.A., Franconeri, S.L.: How Many Objects Can You Track?: Evidence for a Resource-limited Attentive Tracking Mechanism. Journal of Vision 7, 1–10 (2007)Google Scholar
  20. 20.
    Wolfe, J.M., Place, S.S., Horowitz, T.S.: Multiple Object Juggling: Changing What is Tracked During Extended Multiple Object Tracking. Psychonomic Bulletin & Review 14, 344–349 (2007)Google Scholar
  21. 21.
    Wertheimer, M.: Laws of Organization in Perceptual Forms. In: Ellis, W. (ed.) A Source Book of Gestalt Psychology, pp. 71–88. Routledge, London (1938)CrossRefGoogle Scholar
  22. 22.
    Lee, P., Klippel, A., Tappe, H.: The Effect of Motion in Graphical User Interfaces. In: Butz, A., Krüger, A., Olivier, P. (eds.) SG 2003. LNCS, vol. 2733, pp. 12–21. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  23. 23.
    Agam, Y., Sekuler, R.: Geometric Structure and Chunking in Reproduction of Motion Sequences. Journal of Vision 8, 1–12 (2008)CrossRefGoogle Scholar
  24. 24.
    Michotte, A.: The Perception of Causality. Methuen, London (1963)Google Scholar
  25. 25.
    Kriz, S., Hegarty, M.: Top-down and Bottom-up Influences on Learning from Animations. International Journal of Man-Machine Studies 65, 911–930 (2007)Google Scholar
  26. 26.
    Lowe, R.K.: Interrogation of a Dynamic Visualisation During Learning. Learning & Instruction 14, 257–274 (2004)CrossRefMathSciNetGoogle Scholar
  27. 27.
    Lowe, R.K.: Learning from animation: Where to Look, When to Look. In: Lowe, R.K., Schnotz, W. (eds.) Learning with Animation: Research Implications for Design, pp. 49–68. Cambridge University Press, New York (2008)Google Scholar
  28. 28.
    Ayres, P., Paas, F.: Can the Cognitive Load Approach Make Instructional Animations More Effective? Applied Cognitive Psychology 21, 811–820 (2007)CrossRefGoogle Scholar
  29. 29.
    Burns, C.M.: Navigation Strategies with Ecological Displays. International Journal of Human-Computer Studies 52, 111–129 (2000)CrossRefGoogle Scholar
  30. 30.
    Norman, D.A.: The Design of Everyday Things. Doubleday, New York (1991)Google Scholar
  31. 31.
    Naikar, N., Hopcroft, R., Moylan, A.: Work Domain Analysis: Theoretical Concepts and Methodology. Australian Government Department of Defence, Victoria (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Richard Lowe
    • 1
  • Jean-Michel Boucheix
    • 2
  1. 1.Curtin UniversityAustralia
  2. 2.University of BurgundyFrance

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