Advertisement

Multisensory Immersion as a Modeling Environment for Learning Complex Scientific Concepts

  • Chris Dede
  • Marilyn C. Salzman
  • R. Bowen Loftin
  • Debra Sprague
Part of the Modeling Dynamic Systems book series (MDS)

Abstract

In every aspect of our knowledge-based society, fluency in understanding complex information spaces is an increasingly crucial skill (Dede and Lewis, 1995). In research and industry, many processes depend on peolple utilizing complicated representations of information (Rieber, 1994). Increasingly, workers must navigate complex information spaces to locate data they need, must find patterns in information for problem solving, and must use sophisticated representations of information to communicate their ideas (Kohn, 1994; Studt, 1995). Further, to make informed decisions about public-policy issues such as global warming and environmental contamination, citizens must comprehend the strenghts and limitations of scientific models based on multivariate interactions. In many academic areas, students’ success now depends on their ability to envision and manipulate abstract multidimensional information spaces (Gordin and Pea, 1995). Fields in which students struggle with mastering these types of representations include mathematics, science, engineering, statistics, and finance.

Keywords

Virtual Reality Field Line Virtual Environment Virtual World Equipotential Surface 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arthur, E.J., Hancock, P.A., & Chrysler, S.T. 1994. Spatial orientation in virtual worlds. In Proceedings of the 37th Annual Meeting of the Human Factors and Ergonomics Society. Santa Monica, CA: Human Factors Society, pp. 328–332.Google Scholar
  2. Bricken, M., & Byrne, C. M. 1993. Summer students in virtual reality. In Wexelblat, A. (ed.), Virtual reality: Applications and exploration. New York: Academic Press, pp. 199–218.Google Scholar
  3. Chi, M.T.H., Feltovich, P.J., & Glaser, R. 1991. Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.CrossRefGoogle Scholar
  4. Clark, A.C. 1973. Technology and the limits of knowledge. In Boorstin, D. (ed.), Technology and the frontiers of knowledge. New York: Doubleday.Google Scholar
  5. Dede, C. 1995. The evolution of constructivist learning environments: Immersion in distributed, virtual worlds. Educational Technology 35(5), 46–52.Google Scholar
  6. Dede, C., and Lewis, M. 1995. Assessment of emerging educational technologies that might assist and enhance school-to-work transitions. Washington, DC: National Technical Information Service.Google Scholar
  7. Dede, C., Salzman, M., & Loftin, B. 1996. ScienceSpace: Virtual realities for learning complex and abstract scientific concepts. In Proceedings of IEEE Virtual Reality Annual International Symposium 1996. New York: IEEE Press, pp. 246 - 253.CrossRefGoogle Scholar
  8. Dede, C., Salzman, M., Loftin, B., & Ash, K. (in preparation). Using virtual reality technology to convey abstract scientific concepts. In Jacobson, M., & Kozma, R. (eds.), Learning the sciences of the 21st century: Reseach, design, and implementation of advanced technological learning environments. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  9. Ellis, S.R., Tharp, G.K., Grunwald, A.J., & Smith, S. 1991. Exocentric judgments in real environments and stereoscopic displays. In Proceedings of the 35th Annual Meeting of the Human Factors Society. Santa Monica, CA: Human Factors Society, pp. 1442–1446.Google Scholar
  10. Erickson, T. 1993. Artificial realities as data visualization environments. In Wexelblat, A. (ed.), Virtual reality: Applications and explorations. New York: Academic Press, pp. 1–22.Google Scholar
  11. Feurzeig, W. 1997. Personal communication to the authors Cambridge, MA: BBN Labs.Google Scholar
  12. Fosnot, C. 1992. Constructing constructivism In Duffy, T.M., & Jonassen, D.H. (eds.), Constructivism and the technology of instruction: A conversation. Hillsdale, NJ: Lawrence Erlbaum, pp. 167–176.Google Scholar
  13. Gordin, D.N., & Pea, R.D. 1995. Prospects for scientific visualization as an educational technology. The Journal of the Learning Sciences, 4(3), 249–279.CrossRefGoogle Scholar
  14. Halloun, I.A., & Hestenes, D. 1985a. Common sense concepts about motion. American Journal of Physics, 53, 1056–1065.CrossRefGoogle Scholar
  15. Halloun, I.A., & Hestenes, D. 1985b. The initial knowledge state of college students. American Journal of Physics 53 1043–1055.CrossRefGoogle Scholar
  16. Heeter, C. 1992. Being there: The subjective experience of presence. Presence: Teleoperators and Virtual environments, 1(1), 262–271.Google Scholar
  17. Kalawsky, R.S. 1993. The science of virtual reality and virtual environments. New York: Addison-Wesley.Google Scholar
  18. Kennedy, R.S., Lane, N.E., Berbaum, K.S., & Lilienthal, M.G. 1993. Simulator sickness questionnaire. An enhanced method for quantifying simulator sickness. The International Journal of Aviation Psychology, 3(3), 203–220.CrossRefGoogle Scholar
  19. Kohn, M. 1994. Is this the end of abstract thought? New Scientist, September 17, 37–39.Google Scholar
  20. Krueger, M. 1991. Artificial reality II. New York: Addison-Wesley.Google Scholar
  21. Loftin, R.B. 1997. Hands across the Atlantic. IEEE Computer Graphics & Applications, 17(2), 78–79.Google Scholar
  22. Malone, T.W., & Lepper, M.R. 1984. Making learning fun: A taxonomy of intrinsic motivations for learning. In Snow, R.E., & Farr, M.J. (eds.), Aptitude, learning and instruction. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  23. McCormick, E.P. 1995. Virtual reality features of frames of reference and display dimensionality with stereopsis: Their effects on scientific visualization. Unpublished master’s thesis, University of Illinois at Urbana-Champaign, Urbana, Illinois.Google Scholar
  24. McDermott, L.C. 1991. Millikan lecture 1990: What we teach and what is learned-closing the gap. American Journal of Physics, 59, 301–315.CrossRefGoogle Scholar
  25. Papert, S. 1988. The conservation of Piaget: The computer as grist for the constructivist mill In Foreman, G., & Pufall, P B (eds.), Constructivism in the computer age. Hillsdale, NJ: Lawrence Erlbaum, pp. 3–13.Google Scholar
  26. Perkins, D. 1991. Technology meets constructivism: Do they make a marriage? Educational Technology 31(5), 18–23.Google Scholar
  27. Piantanida, T., Boman, D.K., & Gille, J. 1993, Human perceptual issues and virtual reality. Virtual Reality Systems, 1(1), 43–52.Google Scholar
  28. Psotka, J. 1996. Immersive training systems: Virtual reality and education and training. Instructional Science 23(5–6), 405–423.Google Scholar
  29. Redish, E. 1993. The implications of cognitive studies for teaching physics. American Journal of Physics, 62(9), 796–803.Google Scholar
  30. Regian, J.W., Shebilske, W., & Monk, J. 1992. A preliminary empirical evaluation of virtual reality as a training tool for visual-spatial tasks. Journal of Communication 42, 136 - 149.CrossRefGoogle Scholar
  31. Reif, F., & Larkin, J. 1991. Cognition in scientific and everyday domains: Comparison and learning implications. Journal of Research in Science Teaching 28, 743 - 760.CrossRefGoogle Scholar
  32. Rieber, L.P. 1994. Visualization as an aid to problem-solving: Examples from history. In Proceedings of Selected Research and Development Presentations at the 1994 National Convention of the Association for Educational Communications and Technology. Washington, DC: AECT, pp. 1018–1023.Google Scholar
  33. Salzman, M.C., Dede, C., & Loftin, R.B. 1995. Learner-centered design of sensorily immersive microworlds using a virtual reality interface. In J. Greer (ed.), Proceedings of the 7th International Conference on Artificial Intelligence and Education. Charlottesville, VA: Association for the Advancement of Computers in Education, pp. 554–564.Google Scholar
  34. Smith, R.B. (1987). Experiences with the alternate reality kit: An example of the tension between literalism and magic. In Proceedings of CHI+ GI 1987. New York: Association for Computing Machinery, pp. 324 - 333.Google Scholar
  35. Stuart, R., & Thomas, J.C. 1991. The implications of education in cyberspace. Multimedia Review 2, 17 - 27.Google Scholar
  36. Studt, T. 1995. Visualization revolution adding new scientific viewpoints. R & D Computers & Software, October 14–16.Google Scholar
  37. Trowbridge, D., & Sherwood, B. 1994. EM Field. Raleigh, NC: Physics Academic Software.Google Scholar
  38. Wenzel, E.M. 1992. Localization in virtual acoustic displays. Presence, 1(1), 80–107.Google Scholar
  39. White, B. 1993. ThinkerTools:Causal models, conceptual change, and science education. Cognition and Instruction,101–100.CrossRefGoogle Scholar
  40. Wickens, C. 1992. Virtual reality and education. IEEE Spectrum, 842–847.Google Scholar
  41. Wickens, C.D., & Baker, P. 1995. Cognitive issues in virtual reality. In Barfield, W., & Furness, T. (eds.), Virtual environments and advanced interface design. New York: Oxford Press.Google Scholar
  42. Witmer, B.B., & Singer, M.J. 1994. Measuring presence in virtual environments(ARI Tech Report No. 1014 ). Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.Google Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Chris Dede
  • Marilyn C. Salzman
  • R. Bowen Loftin
  • Debra Sprague

There are no affiliations available

Personalised recommendations