Cognitive Transfer Revisited: Can We Exploit New Media to Solve Old Problems on a Large Scale?
The work we report in this special issue attempted to exploit the power of technology and cognitive theory to help make conceptual systems taught in large college courses truly useful in students' future lives. Facing evidence that traditional instructional models have not succeeded in this reg...
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Published in: | Journal of educational computing research Vol. 35; no. 2; pp. 145 - 162 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Los Angeles, CA
SAGE Publications
2006
Baywood Publishing Company, Inc |
Subjects: | |
Online Access: | Get full text |
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Summary: | The work we report in this special issue attempted to exploit the power of technology and cognitive theory to help make conceptual systems taught in large college courses truly useful in students' future lives. Facing evidence that traditional instructional models have not succeeded in this regard, we sought feasible course designs and computer-based tools that would close the gap between classrooms and practice. Using a tool for online course building that we developed during the course of our work, we designed and examined alternative theory-based instructional models that systematically integrated video case study with collaborative problem-based and text-based learning. The contexts of our research were online learning science courses for teachers taught at UW-Madison and Rutgers University. Our contribution summarizes findings from several years of design research and offers evidence concerning the strengths and limitations of the instructional model that evolved during our work. As part of our model, we have created cognitive tools to support collaborative learning by providing video cases as shared contexts and collaboration spaces and activity structures for students to share information, compare perspectives, and engage in collaborative design. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0735-6331 1541-4140 |
DOI: | 10.2190/0576-R724-T149-5432 |