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14 - Case-Based Reasoning

Published online by Cambridge University Press:  05 June 2012

By
Janet L. Kolodner
Edited by
R. Keith Sawyer
Janet L. Kolodner
Affiliation:
Georgia Institute of Technology
R. Keith Sawyer
Affiliation:
Washington University, St Louis
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Summary

In this chapter, I tell the story of case-based reasoning's contributions to the learning sciences. It is a story that begins in Artificial Intelligence and Cognitive Science in the 1970s. Roger Schank and his students were investigating ways for the computer to understand the everyday language we speak, and they were basing their work on observations about the way people seem to understand everyday language (Schank & Abelson, 1977). As part of those investigations, they were identifying schema-like knowledge structures that might organize different types of knowledge, and at the same time, identifying processes that could make inferences from those knowledge structures. Case-based reasoning (CBR) was born from this research in the 1980s as an attempt to make intelligent systems behave more like experts. As these researchers learned more about the processes that allow a reasoner to reason based on previous experiences, it became clear that case-based reasoning had much to offer education. Researchers began to use the principles of case-based reasoning to design learning environments, including adult education, museums, K–12 classrooms, and undergraduate education. Sometimes the computer has been integrated into those learning environments – as a tool that can provide the kinds of information and advice case-based reasoning says is useful for promoting successful project work and goal achievement, as a tool for eliciting the kinds of reflection that case-based reasoning says are important for learning productively from experience, or as an organizer of the learning sequence. Sometimes the computer has played little or no role.

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Chapter
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The Cambridge Handbook of the Learning Sciences , pp. 225 - 242
Publisher: Cambridge University Press
Print publication year: 2005

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References

Agogino, A., & Hsi, S (1994). The impact and instructional benefit of using multimedia case studies to teach engineering Design, Journal of Educational Hypermedia and Multimedia, 3(3/4), 351–376.Google Scholar
Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist, 26(3 & 4), 369–398.CrossRefGoogle Scholar
Domeshek, E., and Kolodner, J. L. (1993). Using the points of large cases. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM), 7(2), 87–96.CrossRefGoogle Scholar
Gray, J., Camp, P., Holbrook, J., Fasse, B., & Kolodner, J. L. (2001). Science talk as a way to assess student transfer and learning: Implications for formative assessment. http://www.cc.gatech.edu/projects/lbd/pubtopic.html.
Guzdial, M., & Kehoe, C. (1998). Apprenticeship-based learning environments: A principled approach to providing software-realized scaffolding through hypermedia. Journal of Interactive Learning Research, 9(3/4), 289–336.Google Scholar
Hammond, K. J. (1989) Case-based planning: Viewing planning as a memory task. Boston: Academic Press.CrossRefGoogle Scholar
Kolodner, J. L. (1983a). Maintaining organization in a dynamic long-term memory. Cognitive Science, 7(4), 243–280.CrossRefGoogle Scholar
Kolodner, J. L. (1983b). Reconstructive memory: A computer model. Cognitive Science, 7(4), 281–328.CrossRefGoogle Scholar
Kolodner, J. (1993). Case Based Reasoning. San Mateo, CA: Morgan Kaufmann Publishers.CrossRefGoogle Scholar
Kolodner, Janet L. (1997). Educational implications of analogy: A view from Case-Based Reasoning. American Psychologist, 52(1), 57–66.CrossRefGoogle ScholarPubMed
Kolodner, J. L., Crismond, D., Fasse, B., Gray, J., Holbrook, J., Puntembakar, S. (2003). Problem-based learning meets Case-Based Reasoning in the middle-school science classroom: Putting Learning-by-DesignTM into practice. Journal of the Learning Sciences, 12(4).CrossRefGoogle Scholar
Kolodner, J. L., Gray, J., & Fasse, B. B. (2003). Promoting transfer through Case-Based Reasoning: Rituals and practices in Learning by DesignTM Classrooms. Cognitive Science Quarterly, 3, 183–232.Google Scholar
Kolodner, J. L., Owensby, J. N., & Guzdial, M. (2004). Case-based learning aids. In Jonassen, D. H. (Ed.) Handbook of research for educational communications and technology (2nd Ed.). Mahwah, NJ: Lawrence Erlbaum Associates, pp. 829–861.Google Scholar
Kolodner, J. L., & Simpson, R. L. (1989). The MEDIATOR: Analysis of an early case-based problem solver. Cognitive Science 13(4), 507–549.CrossRefGoogle Scholar
Nagel, K., & Kolodner, J. L. (1999). SMILE: Supportive Multi-User Interactive Learning Environment http://www.cc.gatech.edu/projects/lbd/pubtopic.html.#software.
Owensby, J. N., & Kolodner, J. L. (2004). Case interpretation and application in support of scientific reasoning. In Forbus, K. D., Genter, D. and Regier, T. (Eds.), Proceedings of the 26th annual conference of the cognitive science society (pp. 1065–1070). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Papert, S. (1991). Situating constructionism. In Harel, I. & Papert, S. (Eds.), Constructionism (pp. 1–11). Norwood, NJ: Ablex Publishing Company.Google Scholar
Puntambekar, S., & Kolodner, J. L. (2004). Toward implementing distributed scaffolding: Helping students learn science from design. Journal of Research on Science Teaching, 42(2), 185–217.CrossRefGoogle Scholar
Redmond, M. (1992). Learning by Observing and Understanding Expert Problem Solving. Unpublished Ph.D. dissertation, College of Computing, Georgia Institute of Technology.Google Scholar
Schank, R. C. (1982). Dynamic memory. New York: Cambridge University Press.Google Scholar
Schank, R. C. (1999). Dynamic memory revisited. New York: Cambridge University Press.CrossRefGoogle Scholar
Schank, R. C., & Abelson, R. L. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Schank, R. C., & Cleary, C. (1994). Engines for education. Lawrence Erlbaum Associates. http://www.ils.nwu.edu/~e_for_e.Google Scholar
Schank, R. C., Fano, A., Bell, B., & Jona, M. (1994). The design of goal-based scenarios. Journal of the Learning Sciences, 3(4), 305–346.CrossRefGoogle Scholar
Schon, D. A. (1982). The reflective practitioner: How professionals think in action. New York: Basic Books.Google Scholar
Silver, E. A., Branca, N. A., & Adams, V. M. (1980). Metacognition: The missing link in problem solving? In Karplus, R. (Ed.), Proceedings of the Fourth International Conference for the Psychology of Mathematics Education (pp. 213–222). Berkeley: University of California.Google Scholar
Spiro, R. J., Feltovich, P. J., Jacobson, M. J., & Coulson, R. L. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31(5), 24–33.Google Scholar
Turns, J. (1997). Learning Essays and the Reflective Learner: Supporting Assessment in Engineering Design Education. Unpublished Ph.D. dissertation. School of Industrial and Systems Engineering. Georgia Institute of Technology.Google Scholar
Turns, J. A., Newstetter, W., Allen, J. K., & Mistree, F. (1997, June). The reflective learner: Supporting the writing of learning essays that support the learning of engineering design through experience, Proceedings of the 1997 American Society of Engineering Educators Conference. Milwaukee, WI.Google Scholar
Zimring, C. M., Do, E, Domeshek, E. and Kolodner, J. (1995) Supporting case-study use in design education: A computational case-based design aid for architecture. In Mohsen, J. P., ed., Computing in engineering: Proceedings of the second congress (pp. 1635–1642). New York: American Society of Civil Engineers.Google Scholar

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  • Case-Based Reasoning
  • Edited by R. Keith Sawyer, Washington University, St Louis
  • Book: The Cambridge Handbook of the Learning Sciences
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511816833.015
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  • Case-Based Reasoning
  • Edited by R. Keith Sawyer, Washington University, St Louis
  • Book: The Cambridge Handbook of the Learning Sciences
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511816833.015
Available formats
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To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Case-Based Reasoning
  • Edited by R. Keith Sawyer, Washington University, St Louis
  • Book: The Cambridge Handbook of the Learning Sciences
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511816833.015
Available formats
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