Visual-Spatial Learning and Training in Collaborative Design in Virtual Environments

  • Maria Kozhevnikov
  • Andre Garcia
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 48)


This chapter reviews different types of immersive virtual environments (IVE) and discusses the major advantages that these environments can offer in the domain of visual-spatial learning, assessment, and training. Overall, our review indicates that immersion might be one of the most important aspects to be considered in the design of learning and training environments for visual-spatial cognition. Furthermore, we suggest that only immersive virtual environments can provide a unique tool for assessing and training visual-spatial performance that require either the reliance on non-visual cues (motor, vestibular, or proprioceptive) or the use of egocentric frames of references.


Virtual Reality Virtual Environment Mental Rotation Path Integration Collaborative Design 
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.


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  1. Aoki, H., Oman, C., Buckland, D., Natapoff, A.: Desktop-VR system for preflight 3D navigation training. Acta Astronautica 63, 841–847 (2008)CrossRefGoogle Scholar
  2. Bigel, M., Ellard, C.: The contribution of nonvisual information to simple place navigation and distance estimation: An examination of path integration. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 54(3), 172–185 (2000)CrossRefGoogle Scholar
  3. Blade, R.A., Padgett, M.L.: Virtual environments standards and terminology. In: Stanney, K. (ed.) Handbook of Virtual Environments: Design, Implementation, and Applications, pp. 15–27. Lawrence Erlbaum Associates Publishers, Mahwah (2002)Google Scholar
  4. Blajenkova, O., Motes, M., Kozhevnikov, M.: Individual differences in the representations of novel environments. Journal of Environmental Psychology 25(1), 97–109 (2005)CrossRefGoogle Scholar
  5. Chance, S., Gaunet, F., Beall, A., Loomis, J.: Locomotion mode affects the updating of objects encountered during travel: The contribution of vestibular and proprioceptive inputs to path integration. Presence 7(2), 168–178 (1998)CrossRefGoogle Scholar
  6. Cockayne, W., Darken, R.: The application of human ability requirements to virtual environment interface design and evaluation. In: The handbook of task analysis for human-computer interaction, pp. 401–421 (2004)Google Scholar
  7. Colt, H.G., Crawford, S.W., Gaulbraith, O.: Virtual reality bronchoscopy simulation. Chest 120, 1333–1339 (2001)CrossRefGoogle Scholar
  8. Darken, R., Peterson, B.: Spatial orientation, wayfinding, and representation. In: Stanney, K. (ed.) Handbook of Virtual Environments: Design, Implementation, and Applications, pp. 493–518. Lawrence Erlbaum Associates Publishers, Mahwah (2002)Google Scholar
  9. Darken, R., Sibert, J.: Navigating large virtual spaces. International Journal of Human-Computer Interaction 8(1), 49–71 (1996)CrossRefGoogle Scholar
  10. Easton, R., Sholl, M.: Object-array structure, frames of reference, and retrieval of spatial knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition 21(2), 483–500 (1995)CrossRefGoogle Scholar
  11. Gillingham, K.K., Wolfe, J.W.: Spatial Orientation in Flight (Technical Report USAFSAM-TR-85-31), Brooks Air Force Base, TX: USAF School of Aerospace Medicine, Aerospace Medical Division (1986)Google Scholar
  12. Haskell, I., Wickens, C.: Two- and three-dimensional displays for aviation: A theoretical and empirical comparison. International Journal of Aviation Psychology 3(2), 87–109 (1993)CrossRefGoogle Scholar
  13. Homan, W.J.: Virtual reality: Real promises and false expectations. EMI: Educational Media International 31(4), 224–227 (1994)CrossRefGoogle Scholar
  14. Jodlowski, M.T., Doane, S.M., Brou, R.J.: Adaptive expertise during simulated flight. In: Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting, HFES, Denver, Colorado (October 2003)Google Scholar
  15. Kemeny, A., Panerai, F.: Evaluating perception in driving simulation experiments. Trends in Cognitive Sciences 7(1), 31–37 (2003)CrossRefGoogle Scholar
  16. Kidd, D.G., Monk, C.A.: The effects of dual-task inference and response strategy on stop or go decisions to yellow light changes. In: Proceedings of the 5th International Symposium on Human Factors in Driving Assessment, Training, and Vehicle Design, Big Sky, Montana (June 2009)Google Scholar
  17. Klatzky, R., Loomis, J., Beall, A., Chance, S., Golledge, R.: Spatial updating of self-position and orientation during real, imagined, and virtual locomotion. Psychological Science 9(4), 293–298 (1998)CrossRefGoogle Scholar
  18. Kozhevnikov, M.: The role of immersive 3-D environments in mental rotation. Paper was be presented at the Psychonomic Society 50th Annaul Meetihg, Boston, November 12-22 (2009)Google Scholar
  19. Kozhevnikov, M., Blazhenkova, O., Royan, J., Gorbunov, A.: The role of immersivity in three-dimensional mental rotation. In: Paper was presented at third International Conference on Design Computing and Cognition DCC 2008, Atlanta, GA (2008)Google Scholar
  20. Kozhevnikov, M: Individual difference in allocentric and agocentric spatial ability, Technical report, Office on Naval Research, N000140611072 (2007)Google Scholar
  21. Kozhevnikov, M., Motes, M., Rasch, B., Blajenkova, O.: Perspective-taking vs. mental rotation transformations and how they predict spatial navigation performance. Applied Cognitive Psychology 20, 397–417 (2006)CrossRefGoogle Scholar
  22. Loomis, J., Beall, A.: Visually controlled locomotion: Its dependence on optic flow, three-dimensional space perception, and cognition. Ecological Psychology 10(3), 271–285 (1998)CrossRefGoogle Scholar
  23. Loomis, J., Blascovich, J., Beall, A.: Immersive virtual environment technology as a basic research tool in psychology. Behavior Research Methods, Instruments & Computers 31(4), 557–564 (1999)CrossRefGoogle Scholar
  24. Loomis, J., Klatzky, R., Golledge, R., Philbeck, J.: Human Navigation by Path Integration. In: Wayfinding Behavior: Cognitive Mapping and Other Spatial Processes, Johns Hopkins University Press, Baltimore (1998)Google Scholar
  25. Macuga, K.L., Beall, A.C., Kelly, J.W., Smith, R.S., Loomis, J.M.: Changing lanes: inertial cues and explicit path information facilitate steering performance when visual feedback is removed. Experimental Brain Research 178, 141–150 (2007)CrossRefGoogle Scholar
  26. Pausch, R., Proffitt, D., Williams, G.: Quantifying immersion in virtual reality. In: SIGGRAPH (August 1997)Google Scholar
  27. Péruch, P., Gaunet, F.: Virtual environments as a promising tool for investigating human spatial cognition. Cahiers de Psychologie Cognitive/Current Psychology of Cognition 17(4), 881–899 (1998)Google Scholar
  28. Richardson, A., Montello, D., Hegarty, M.: Spatial knowledge acquisition from maps and from navigation in real and virtual environments. Memory & Cognition 27(4), 741–750 (1999)CrossRefGoogle Scholar
  29. Rieser, J.: Access to knowledge of spatial structure at novel points of observation. Journal of Experimental Psychology: Learning, Memory, and Cognition 15(6), 1157–1165 (1989)CrossRefGoogle Scholar
  30. Rizzo, A., Schultheis, M.: Expanding the boundaries of psychology: The application of virtual reality. Psychological Inquiry 13(2), 134–140 (2002)Google Scholar
  31. Salas, E., Oser, R., Cannon-Bowers, J., Daskarolis-Kring, E.: Team training in virtual environments: An event-based approach. In: Stanney, K. (ed.) Handbook of Virtual Environments: Design, Implementation, and Applications, pp. 873–892. Lawrence Erlbaum Associates Publishers, Mahwah (2002)Google Scholar
  32. Van Orden, K., Broyles, J.: Visuospatial task performance as a function of two- and three-dimensional display presentation techniques. Displays 21(1), 17–24 (2000)CrossRefGoogle Scholar
  33. Verner, L., Oleynikov, D., Holtmann, S., Haider, H., Zhukov, L.: Measurements of the level of surgical expertise using flight path analysis from da Vinci Robotic Surgical System. Medicine Meets Virtual Reality 11, 373–378 (2003)Google Scholar
  34. Wiederhold, B., Rizzo, A.: Virtual reality and applied psychophysiology. Applied Psychophysiology and Biofeedback 30(3), 183–185 (2005)CrossRefGoogle Scholar

Copyright information

© Springer Netherlands 2011

Authors and Affiliations

  • Maria Kozhevnikov
    • 1
  • Andre Garcia
    • 2
  1. 1.Harvard Medical School and National University of SingaporeSingapore
  2. 2.George Mason UniversityUSA

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