Bridging strategies for VR-based learning

Conference on Human Factors in Computing Systems - Proceedings

Volumn , Issue , 1999, Pages 536-543

  Moher, Tom ^a   Johnson, Andrew ^a   Ohlsson, Stellan ^a   Gillingham, Mark ^a  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Conceptual change; Learning environments; User models; Virtual reality

Indexed keywords

ALTERNATIVE FRAMEWORK; CONCEPTUAL CHANGE; IMMERSIVE VIRTUAL ENVIRONMENTS; LEARNING ENVIRONMENTS; MODEL MATCHING; MULTIPLE REPRESENTATION; PHYSICAL MODEL; TARGET DOMAIN; USER MODELS;

COMPUTER AIDED INSTRUCTION; HUMAN ENGINEERING; VIRTUAL REALITY; GRAPHICAL USER INTERFACES; LEARNING SYSTEMS; MATHEMATICAL MODELS;

MODELS; HUMAN COMPUTER INTERACTION;

DISTRIBUTED IMMERSIVE VIRTUAL ENVIRONMENTS;

EID: 0032669089     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/302979.303153     Document Type: Conference Paper

References (31)

1. Ainsworth, S., Bibby, P.A., & Wood, D.J. (1997). Information technology and multiple representations: New opportunities-new problems. Journal of Information Technology for Teacher Education, 6, 93- 104.
2. Aronson, E., Blaney, N., Stephan, C., Sikes, J., & Snapp, M. (1978). The Jigsaw Classroom. Beverly Hills, CA: Sage.
3. Angluin, D., & Smith, C. H. (1983). Inductive inference: Theory and methods. Computing Surveys, 15, 237-269.
4. Bereiter, C., (1985). Toward a solution of the learning paradox. Review of Educational Research, 55, 201-226.
5. Bonar, J. & Cunningham, R. (1988). Bridge: Tutoring the programming process. In J. Psotka, L. Massey, and S. Mutter (as.), Intelligent tutoring systems: Lessons learned (pp. 409-434). Hillsdale, NJ: Lawrence Erlbaum.
6. Bruer, J. T. (1994). Schools for thought: A science of learning in the classroom. Cambridge, MA: MIT Press.
7. Calvin, W. H. (1996). The cerebral code. Cambridge, MA: MIT Press.
8. Chi, M. T. H. (1992). Conceptual change within and across ontological categories: Examples from learning and discovery in science. In R. N. Giere, (Ed.), Cognitive models of science (pp. 129-186). Minneapolis, Minnesota: University of Minnesota Press.
9. Clement, J. (1988). Observed methods for generating analogies in scientific problem solving. Cognitive Science, 12, 563-586.
10. Confrey, J. (1990). A review of research on student conceptions in mathematics, science, and programming. In C. B. Cazdan, (Ed.), Review of research in education (Vol. 16, pp. 3-56). Washington, DC: American Educational Research Association.
11. Dede, C., Salzman, M., & Loftin, R. (1996) ScienceSpace: Virtual Realities for Learning Complex and Abstract Scientific Concepts. In Proceedings VRAZS '96 (pp.246-253).
12. DiSessa, A. A. (1988). Knowledge in pieces. In G. Forman & P. Pufall, (Eds.), Constructivism in the computer age (pp. 49-70). Hillsdale, NJ: Erlbaum.
13. DiSessa, A. A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10, 105-225.
14. Ericsson, K. A., Krampe, R. Th., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363-406.
15. Gentner, D., Rattermann, M., Forbus, K. (1993). The role of similarity in transfer. Cognitive Psychology, 25, 524-575.
16. Gick, M., & Holyoak, J. (1987). The cognitive basis for knowledge transfer. In S. Cormier and J.Hagman (Eds.), Transfer of learning (pp. 9-46). San Diego, CA: Academic Press.
17. Hewson, P. W., & Hewson, M. G. A. (1984). The role of conceptual conflict in conceptual change and the design of science instruction. Instructional Science, 13, 1-13.
18. Holyoak, K. J., & Thagard, P. (1995). Mental leaps. Cambridge, MA: Cambridge University Press.
19. Karmiloff-Smith, A. (1992). Beyond modularity: A developmental perspective on cognitive science. Cambridge, MA: MIT Press.
20. McCloseky, (1983). Intuitive theories of motion. In D. Gentner & A. L. Stevens, (Eds.), Mental models (pp. 299-323). Hillsdale, NJ: Erlbaum.
21. Nussbaum, J. (1985). The Earth as a cosmic body. In R. Driver, E. Guesne, & A. Tiberghien (Eds.), Children's ideas in science (pp. 170-192). Milton Keynes, UK: Open University Press.
22. Ohlsson, S. (1995a). Learning to do and learning to understand: A lesson and a challenge for cognitive modeling. In P. Reimann and H. Spada, (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science. Oxford, UK: Elsevier.
23. Piaget, J. (1985). The equilibration of cognitive structures. Chicago, IL: The University of Chicago Press.
24. Reber, A. (1993). Implicit learning and tacit knowledge. New York: Oxford University Press.
25. Resnick, L. B., & Omanson, S. (1987). Learning to understand arithmetic. In R. Glaser, (Ed.), Advances in instructional psychology (Vol. 3, pp. 41-95). Hillsdale, NJ: Erlbaum.
26. Salzman, M., Dede, C., Loftin, R.; & Chen, J. A. (1998)A model for understanding how virtual reality aids complex conceptual learning. Presence (in press).
27. Singley, M., & Anderson, J. R. (1989). The transfer of cognitive skill. Cambridge, MA: Harvard University Press.
28. Stemberg, R. J., (Ed.), (1984). Mechanisms of cognitive development. New York: W. H. Freeman.
29. Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Leaning and Instruction, 4, 45-69.
30. Vosniadou. S., & Brewer, W. F. (1994). Mental models of the day/night cycle. Cognitive Science, 18, 123-183.
31. Youngblut, C. (1998) Educational uses of virtual reality technology. Technical Report IDA Document D-2128, Institute for Defense Analyses, Alexandria, VA.