Bridging strategies for VR-based learning

A distributed immersive virtual environment was deployed as acomponent of a pedagogical strategy for teaching third gradechildren that the Earth is round. The displacement strategy isbased on the theory that fundamental conceptual change requires analternative cognitive starting point which doesnt invoke thefeatures of pre-existing models. While the VR apparatus helped toestablish that alternative framework, conceptual change wasstrongly influenced by the bridging activities which related thatexperience to the target domain. Simple declarations of relevanceproved ineffective. A more articulated bridging process involvingphysical models was effective for some children, but the multiplerepresentations employed required too much model-matching forothers.

[1]  Stella Vosniadou,et al.  Mental Models of the Day/Night Cycle , 1994, Cogn. Sci..

[2]  J. Confrey A Review of the Research on Student Conceptions in Mathematics, Science, and Programming , 1990 .

[3]  John R. Anderson,et al.  The Transfer of Cognitive Skill , 1989 .

[4]  Kenneth D. Forbus,et al.  The Roles of Similarity in Transfer: Separating Retrievability From Inferential Soundness , 1993, Cognitive Psychology.

[5]  S. Vosniadou Capturing and modeling the process of conceptual change. , 1994 .

[6]  Christine Youngblut,et al.  Educational Uses of Virtual Reality Technology. , 1998 .

[7]  A. diSessa Toward an Epistemology of Physics , 1993 .

[8]  Marilyn C. Salzman,et al.  ScienceSpace: virtual realities for learning complex and abstract scientific concepts , 1996, Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium.

[9]  R. Siegler,et al.  Mechanisms of cognitive development. , 1989, Annual review of psychology.

[10]  L. Schauble,et al.  Beyond Modularity: A Developmental Perspective on Cognitive Science. , 1994 .

[11]  John Clement,et al.  Observed Methods for Generating Analogies in Scientific Problem Solving , 1987, Cogn. Sci..

[12]  A. Reber Implicit learning and tacit knowledge , 1993 .

[13]  Andrea A. diSessa,et al.  Knowledge in pieces : An evolving framework for understanding knowing and learning , 1988 .

[14]  Stellan Ohlsson,et al.  Learning to do and learning to understand : a lesson and a challenge for cognitive modeling , 1996 .

[15]  Robert J. Sternberg,et al.  Mechanisms of cognitive development , 1984 .

[16]  E. Aronson The Jigsaw Classroom , 1978 .

[17]  Peter A. Bibby,et al.  Information technology and multiple representations: new opportunities – new problems , 1997 .

[18]  J. Bruer Schools for Thought: A Science of Learning in the Classroom , 1993 .

[19]  A. Karmiloff-Smith Précis of Beyond modularity: A developmental perspective on cognitive science , 1994, Behavioral and Brain Sciences.

[20]  Carl H. Smith,et al.  Inductive Inference: Theory and Methods , 1983, CSUR.

[21]  Michelene T. H. Chi,et al.  Conceptual Change within and across Ontological Categories: Examples from Learning and Discovery in Science , 1992 .

[22]  Robert J. Crutcher,et al.  The role of deliberate practice in the acquisition of expert performance. , 1993 .

[23]  Keith J. Holyoak,et al.  The cognitive basis of knowledge transfer. , 1987 .

[24]  Jim X. Chen,et al.  A Model for Understanding How Virtual Reality Aids Complex Conceptual Learning , 1999, Presence: Teleoperators & Virtual Environments.

[25]  R. Driver,et al.  Children's Ideas in Science , 1985 .

[26]  C. Bereiter Toward a Solution of the Learning Paradox , 1985 .

[27]  Jere Confrey,et al.  Chapter 1: A Review of the Research on Student Conceptions in Mathematics, Science, and Programming , 1990 .

[28]  Mariana G. Hewson,et al.  The role of conceptual conflict in conceptual change and the design of science instruction , 1984 .