Learning from Animations: From 2D to 3D?

  • Stephan Schwan
  • Frank Papenmeier


This chapter considers the role of three-dimensional animations in learning. ‘Going three-dimensional’ does not simply add a third dimension to conventional animations, but rather it can provide new types of animations that show static objects or scenes from changing viewpoints, improve perception of depth through stereoscopic projection, and offer additional types of interactivity beyond control of pacing. From a psychological perspective, these possibilities have implications for learning and understanding. In particular, the provision of a third dimension may be beneficial for building up appropriate mental representations, particularly when extension in space is relevant for comprehension. Three-dimensional animations also allow for a precise definition of viewpoint trajectories that may guide the viewers’ attention to relevant parts of objects or events. The chapter gives an overview of these issues, describes relevant empirical findings, and gives a balanced account of the benefits and drawbacks of using three-dimensional animations for learning and knowledge acquisition.


Spatial Ability Camera Movement Virtual Camera Canonical View Stereoscopic Viewing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bennett, D. J., & Vuong, Q. C. (2006). A stereo advantage in generalizing over changes in viewpoint on object recognition tasks. Perception & Psychophysics, 68, 1082–1093.CrossRefGoogle Scholar
  2. Berney, S., & Bétrancourt, M. (2017). Learning three-dimensional anatomical structures with animation: Effects of orientation references and learners’ spatial ability. In R. Lowe & R. Ploetzner (Eds.), Learning from dynamic visualization — Innovations in research and application. Berlin: Springer (this volume).Google Scholar
  3. Bivall, P., Ainsworth, S., & Tibell, L. A. E. (2011). Do haptic representations help complex molecular learning? Science Education, 95, 700–719.CrossRefGoogle Scholar
  4. Blanz, V., Tarr, M. J., & Bülthoff, H. H. (1999). What object attributes determine canonical views? Perception, 28, 575–599.CrossRefGoogle Scholar
  5. Bordwell, D., & Thompson, K. (1979). Film art: An introduction. New York: McGraw Hill.Google Scholar
  6. Boucheix, J.-M., Lowe, R. K., Putri, D. K., & Groff, J. (2013). Cueing animations: Dynamic signaling aids information extraction and comprehension. Learning and Instruction, 25, 71–84.CrossRefGoogle Scholar
  7. Burke, D. (2005). Combining disparate views of objects: Viewpoint costs are reduced by stereopsis. Visual Cognition, 12, 705–719.CrossRefGoogle Scholar
  8. Carrier, L. M., Rab, S. S., Rosen, L. D., Vasquez, L., & Cheever, N. A. (2012). Pathways for learning from 3D technology. International Journal of Environmental & Science Education, 7, 53–69.Google Scholar
  9. Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41, 10–32.CrossRefGoogle Scholar
  10. De Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2007). Attention guidance in learning from complex animation: Seeing is understanding? Learning and Instruction, 20, 111–122.CrossRefGoogle Scholar
  11. De Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21, 113–140.CrossRefGoogle Scholar
  12. Diwadkar, V. A., & McNamara, T. P. (1997). Viewpoint dependence in scene recognition. Psychological Science, 8, 302–307.CrossRefGoogle Scholar
  13. Eriksson, U., Linder, C., Airey, J., & Redfors, A. (2014). Who needs 3D when the universe is flat? Science Education, 98, 412–442.CrossRefGoogle Scholar
  14. Fischer, S., Lowe, R. K., & Schwan, S. (2008). Effects of presentation speed of a dynamic visualization on the understanding of a mechanical system. Applied Cognitive Psychology, 22, 1126–1141.CrossRefGoogle Scholar
  15. Garg, A. X., Norman, G. R., Eva, K. W., Spero, L., & Sharan, S. (2002). Is there any real virtue of virtual reality? The minor role of multiple orientations in learning anatomy from computers. Academic Medicine, 77, S97–S99.CrossRefGoogle Scholar
  16. Garg, A., Norman, G. R., Spero, L., & Maheswari, P. (1999). Do virtual computer models hinder anatomy learning? Academic Medicine, 74, S87–S89.CrossRefGoogle Scholar
  17. Garsoffky, B., Huff, S., & Schwan, S. (2007). Changing viewpoints during dynamic events. Perception, 36, 366–374.CrossRefGoogle Scholar
  18. Garsoffky, B., Schwan, S., & Hesse, F. W. (2002). Viewpoint dependency in the recognition of dynamic scenes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 1035–1050.Google Scholar
  19. Garsoffky, B., Schwan, S., & Huff, M. (2009). Canonical views of dynamic scenes. Journal of Experimental Psychology: Human Perception and Performance, 35, 17–27.Google Scholar
  20. Glaser, M., Lengyel, D., Toulouse, C., & Schwan, S. (in press). Designing computer-based learning contents: Influence of digital zoom on attention. Education Technology Research and Development.Google Scholar
  21. Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21, 713–729.CrossRefGoogle Scholar
  22. Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17, 722–738.CrossRefGoogle Scholar
  23. Huff, M., Jahn, G., & Schwan, S. (2009). Tracking multiple objects across abrupt viewpoint changes. Visual Cognition, 17, 297–306.CrossRefGoogle Scholar
  24. Huk, T. (2006). Who benefits from learning with 3D models? The case of spatial ability. Journal of Computer Assisted Learning, 22, 392–404.Google Scholar
  25. Huk, T., Steinke, M., & Floto, C. (2010). The educational value of visual cues and 3D-representational format in a computer animation under restricted and realistic conditions. Instructional Science, 38, 455–469.CrossRefGoogle Scholar
  26. Imhof, B., Scheiter, K., Edelmann, J., & Gerjets, P. (2012). How temporal and spatial aspects of presenting visualizations affect learning about locomotion patterns. Learning and Instruction, 22, 193–205.Google Scholar
  27. Jahn, G., Papenmeier, F., Meyerhoff, H. S., & Huff, M. (2012). Spatial reference in multiple object tracking. Experimental Psychology, 59, 163–173.CrossRefGoogle Scholar
  28. Jenkinson, J. (2017). The role of craft-based knowledge in the design of dynamic visualizations. In R. Lowe & R. Ploetzner (Eds.), Learning from dynamic visualization — Innovations in research and application. Berlin: Springer (this volume).Google Scholar
  29. Johnston, O., & Thomas, F. (1981). Disney animation: The illusion of life. New York: Walt Disney Productions.Google Scholar
  30. Kheener, M., Hegarty, M., Cohen, C., Khooshabeh, P., & Montello, D. R. (2008). Spatial reasoning with external visualizations: What matters is what you see, not whether you interact. Cognitive Science, 32, 1099–1132.CrossRefGoogle Scholar
  31. Khooshabeh, P., & Hegarty, M. (2010). Inferring cross-section: When internal visualizations are more important than properties of external visualizations. Human-Computer Interaction, 25, 119–147.CrossRefGoogle Scholar
  32. Lambooji, M., Fortuin, M., Heynderickx, I., & Ijsselsteijn, W. (2009). Visual discomfort and visual fatigue of stereoscopic displays: A review. Journal of Imaging Science and Technology, 53, 1–14.Google Scholar
  33. Lee, Y. L., & Saunders, J. A. (2011). Stereo improves 3D shape discrimination even when rich monocular shape cues are available. Journal of Vision, 11, 1–12.Google Scholar
  34. Liu, G., Austen, E. L., Booth, K. S., Fisher, B. D., Argue, R., Rempel, M. I., et al. (2005). Multiple-object tracking is based on scene, not retinal, coordinates. Journal of Experimental Psychology: Human Perception and Performance, 31, 235–247.Google Scholar
  35. Lowe, R., & Boucheix, J. M. (2008). Learning from animated diagrams: How are mental models built? In G. Stapleton, J. Howse, & J. Lee (Eds.), Diagrammatic representation and inference (pp. 266–281). Berlin: Springer.CrossRefGoogle Scholar
  36. Lowe, R., & Boucheix, J.-M. (2017). A composition approach to design of educational animations. In R. Lowe & R. Ploetzner (Eds.), Learning from dynamic visualization — Innovations in research and application. Berlin: Springer (this volume).Google Scholar
  37. Lowe, R., & Schnotz, W. (2014). Animation principles in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 513–546). Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  38. Lowe, R., Schnotz, W., & Rasch, T. (2011). Aligning affordances of graphics with learning task requirements. Applied Cognitive Psychology, 25, 452–459.CrossRefGoogle Scholar
  39. Luursema, J. M., Verwey, W. B., Kommers, P. A. M., & Annema, J. H. (2008). The role of stereopsis in virtual anatomical learning. Interacting with Computers, 20, 455–460.CrossRefGoogle Scholar
  40. Magner, U. I. E., Schwonke, R., Aleven, V., Popescu, O., & Renkl, A. (2014). Triggering situational interest by decorative illustrations both fosters and hinders learning in computer-based learning environments. Learning and Instruction, 29, 141–152.CrossRefGoogle Scholar
  41. Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93, 390–397.CrossRefGoogle Scholar
  42. McClean, S. T. (2007). Digital storytelling. Cambridge, MA: MIT Press.Google Scholar
  43. McGill, G. (2017). Designing instructional science visualizations in the trenches: Where research meets production reality. In R. Lowe & R. Ploetzner (Eds.), Learning from dynamic visualization — Innovations in research and application. Berlin: Springer (this volume).Google Scholar
  44. McIntire, J. P., Havig, P. R., & Geiselman, E. E. (2014). Stereoscopic 3D displays and human performance: A comprehensive review. Displays, 35, 18–28.CrossRefGoogle Scholar
  45. Meesters, L. M. J., Ijsselsteijn, W. A., & Seuntiens, P. J. H. (2004). A survey of perceptual evaluations and requirments of three-dimensional TV. IEEE Transactions on Circuits and Systems for Video Technology, 14, 381–391.CrossRefGoogle Scholar
  46. Mendiburu, B. (2009). 3D movie making. London: Routledge.Google Scholar
  47. Meyer, K., Rasch, T., & Schnotz, W. (2010). Effects of animation’s speed of presentation on perceptual processing and learning. Learning and Instruction, 20, 136–145.CrossRefGoogle Scholar
  48. Meyerhoff, H. S., Huff, M., Papenmeier, F., Jahn, G., & Schwan, S. (2011). Continuous visual cues trigger automatic spatial target updating in dynamic scenes. Cognition, 121, 73–82.CrossRefGoogle Scholar
  49. Mital, P. K., Smith, T. J., Hill, R. L., & Henderson, J. M. (2011). Clustering of gaze during dynamic scene viewing is predicted by motion. Cognitive Computation, 3, 5–24.CrossRefGoogle Scholar
  50. Narayanan, N. H., & Hegarty, M. (2002). Multimedia design for communication of dynamic information. International Journal of Human-Computer Studies, 57, 279–315.CrossRefGoogle Scholar
  51. Nguyen, N., Nelson, A. J., & Wilson, T. D. (2012). Computer visualizations: Factors that influence spatial anatomy comprehension. Anatomical Sciences Education, 5, 98–108.CrossRefGoogle Scholar
  52. Palmer, S., Rosch, E., & Chase, P. (1981). Canonical perspective and the perception of objects. In J. Long & A. Baddeley (Eds.), Attention and performance IX (pp. 135–151). Hillsdale: Erlbaum.Google Scholar
  53. Papenmeier, F., Huff, M., & Schwan, S. (2012). Representation of dynamic spatial configurations in visual short-term memory. Attention, Perception, & Psychophysics, 74, 397–415.CrossRefGoogle Scholar
  54. Papenmeier, F., & Schwan, S. (2016). If you watch it move, you’ll recognize it in 3D: Transfer of depth cues between encoding and retrieval. Acta Psychologica, 164, 90–95.CrossRefGoogle Scholar
  55. Ploetzner, R., & Lowe, R. (2012). A systematic characterization of expository animations. Computers in Human Behavior, 28, 781–794.CrossRefGoogle Scholar
  56. Preece, D., Williams, S. B., Lam, R., & Weller, R. (2013). “Let’s get physical”: Advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy. Anatomical Sciences Education, 6, 216–224.CrossRefGoogle Scholar
  57. Rey, G. D. (2012). A review of research and a meta-analysis of the seductive detail effect. Educational Research Review, 7, 216–237.CrossRefGoogle Scholar
  58. Schwan, S. (2013). The art of simplifying events. In A. P. Shimamura (Ed.), Psychocinematics: Exploring cognition at the movies (pp. 214–226). New York: Oxford University Press.CrossRefGoogle Scholar
  59. Schwan, S., Lewalter, D., & Grajal, A. (2014). Understanding and engagement in places of science experience: Science museums, science centers, zoos and aquariums. Educational Psychologist, 49, 70–85.CrossRefGoogle Scholar
  60. Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and Instruction, 14, 293–305.CrossRefGoogle Scholar
  61. Smith, T. J., Levin, D., & Cutting, J. E. (2012). A window on reality: Perceiving edited moving images. Current Directions in Psychological Science, 21, 107113.CrossRefGoogle Scholar
  62. Soemer, A., & Schwan, S. (2012). Visual mnemonics for language learning: Static pictures vs. animated morphs. Journal of Educational Psychology, 104, 565–579.CrossRefGoogle Scholar
  63. St. John, M., Cowen, M. B., Smallman, H. S., & Oonk, H. M. (2001). The use of 2D and 3D displays for shape-understanding versus relative-position tasks. Human Factors, 43, 79–98.CrossRefGoogle Scholar
  64. Stull, A. T., Hegarty, M., & Mayer, R. E. (2009). Getting a handle on learning anatomy with interactive three-dimensional graphics. Journal of Educational Psychology, 101, 803–816.CrossRefGoogle Scholar
  65. Tarr, M. J. (1995). Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonomic Bulletin & Review, 2, 55–82.CrossRefGoogle Scholar
  66. Trindade, J., Fiolhais, C., & Almeida, L. (2002). Science learning in virtual environments: a descriptive study. British Journal of Educational Technology, 33, 471–488.CrossRefGoogle Scholar
  67. Tversky, B., Morrison, J. B., & Bétrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human-Computer Studies, 57, 247–262.CrossRefGoogle Scholar
  68. Ukai, K., & Howarth, P. A. (2008). Visual fatigue caused by viewing stereoscopic motion images: Background, theories, and observations. Displays, 29, 106–116.CrossRefGoogle Scholar
  69. Valsecchi, M., & Gegenfurtner, K. R. (2012). On the contribution of binocular disparity to the long-term memory for natural scenes. PlosOne, 7(11), e49947.Google Scholar
  70. Van Beurden, M. H. P. H., IJsselsteijn, W. A., & Juola, J. F. (2012). Effectiveness of stereoscopic displays in medicine: A review. 3D Research, 3, 1–13.Google Scholar
  71. Vishwanath, D., & Hibbard, P. B. (2013). Seeing in 3-D with just one eye: Stereopsis without binocular vision. Psychological Science, 24, 1673–1685.CrossRefGoogle Scholar
  72. Wouters, P., Tabbers, H. K., & Paas, F. (2007). Interactivity in video-based models. Educational Psychology Review, 19, 327–342.CrossRefGoogle Scholar
  73. Yuan, H., Calic, J., & Kondoz, A. (2012). Analysis of user requirements in interactive 3D video systems. Advances in Human-Computer Interaction, 2012, 1–11. ID 343197.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Leibniz-Institut für WissensmedienTubingenGermany
  2. 2.University of TübingenTubingenGermany

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