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Extract the Knowledge Structure of Medical Problem Solving: Learning from Cognitive Science

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Medical diagnosis is a central component of medical competency, while being considered a challenge for young physicians. Teaching the ways that medical experts solve clinical problems will enhance students' learning gains. However, medical problems are often dealt differently across cases, physicians, and expertise levels. In order to extract expertise from experts, this study is to review and summarize the techniques for expertise extraction in the field of cognitive science, and explored the relevancy for studying medical problem-solving. Methods: The literature and books on ”extracting expertise” in medicine or in other fields are retrieved. The expertise extraction techniques included those being used in identifying knowledge components/facts, in establishing relationship between stored medical knowledge and in making inferences. Results: There are several extraction techniques being validated and reliable for use. The techniques are generally divided into two categories, direct and indirect. The direct methods that are considered applicable are: interview, questionnaire, observation of task performance, protocol analysis, and interruption analysis. The indirect techniques appropriate for uses are: hierarchal clustering, general weighted networks, ordered trees from recall, and repertory grid analysis. Conclusion: The extraction techniques in cognitive science are valid in understanding expertise in medical problem-solving. The choice of the tools should be dependent on the information, the purpose and the environment. With the use of experts' thoughts, teaching and learning in medical problem-solving will be greatly enhanced.

References


Janet EB: Knowledge Elicitation Tool Classification. Available at: [http://web.cs.wpi.edu/Research/aidg/KE-Rpt98.html] Accessed on 11 Sep, 2011.
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Cited by


Kuo, R. (2002). 利用知識地圖與問題解決方法設計出題系統 [master's thesis, Chung Yuan Christian University]. Airiti Library. https://doi.org/10.6840/cycu200200497

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