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WADEIn II: a case for adaptive explanatory visualization
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Source Annual Joint Conference Integrating Technology into Computer Science Education archive
Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education table of contents
Bologna, Italy
SESSION: Human computer interactions table of contents
Pages: 48 - 52  
Year of Publication: 2006
ISBN:1-59593-055-8
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Authors
Peter Brusilovsky  University of Pittsburgh, Pittsburgh, PA
Tomasz D. Loboda  University of Pittsburgh, Pittsburgh, PA
Sponsors
SIGCSE: ACM Special Interest Group on Computer Science Education
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Adaptive explanatory visualization is an attempt to integrate two promising approaches to program visualization: adaptive visualization and explanatory visualization. The goal of this paper is to demonstrate the ideas of adaptive explanatory visualization using a practical example. The paper introduces the WADEIn II system for the visualization of expression evaluation in the C programming language, shows how expression evaluation visualizations can be made adaptive, and explains our approach to the adaptive generation of explanations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Dancik, G. and Kumar, A.N. A tutor for counter-controlled loop concepts and its evaluation. In: Proc. of 2003 Frontiers in Education Conference (FIE 2003), (Boulder, CO, November 5-8, 2003), Session T3C.
 
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Hundhausen, C.D., Douglas, S.A., and Stasko, J.T. A meta-study of algorithm visualization effectiveness. Journal of Visual Languages and Computing, 13, 3 (2002), 259--290, available online at http://lilt.ics.hawaii.edu/~hundhaus/writings/VL2000-Experiment.pdf.
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Kumar, A.N. Model-based generation of demand feedback in a programming tutor. In: Kay, J. (ed.) Supplementary Proceedings of the 11th International Conference on Artificial Intelligence in Education (AI-ED 2003). IOS Press, Amsterdam, 2003, 425--432.
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Collaborative Colleagues:
Peter Brusilovsky: colleagues
Tomasz D. Loboda: colleagues