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Assessing clinical competence: Diffe...
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Fenn, Darien S.
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Assessing clinical competence: Differentiating experts in veterinary medicine from novices by their sequence of responses in clinical simulations.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Assessing clinical competence: Differentiating experts in veterinary medicine from novices by their sequence of responses in clinical simulations./
作者:
Fenn, Darien S.
面頁冊數:
311 p.
附註:
Source: Dissertation Abstracts International, Volume: 51-03, Section: B, page: 1543.
Contained By:
Dissertation Abstracts International51-03B.
標題:
Psychology, Psychometrics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9020198
Assessing clinical competence: Differentiating experts in veterinary medicine from novices by their sequence of responses in clinical simulations.
Fenn, Darien S.
Assessing clinical competence: Differentiating experts in veterinary medicine from novices by their sequence of responses in clinical simulations.
- 311 p.
Source: Dissertation Abstracts International, Volume: 51-03, Section: B, page: 1543.
Thesis (Ph.D.)--University of Oregon, 1989.
Expert clinicians learn through experience the most efficient and effective way to solve clinical problems. To the extent that this experience aids these experts in identifying the most important cues in the problem presentation and the most important actions to take given those cues, experts should follow a more specific sequence of actions than novices when confronted with the same clinical problems. This study compared the response sequences of 80 experienced veterinarians with 284 veterinary students on a computerized version of the Clinical Competency Test in Veterinary Medicine (CCT), using an empirical strategy of scale constructions. All methods of coding response sequences were superior to standard CCT scoring methods at differentiating the students from the professionals, although large variations between second- and third-year students and between individual problem scores were noted. No one method for encoding sequence of three examined emerged as clearly superior on all problems for both student groups, although there were some differences in individual problem scores. Empirically derived scales based on sequence outperformed unit-weighted endorsement scales on half the problems, but this advantage all but disappeared when regression-based weights were applied to the endorsement-selected items. Empirical scales accounted for up to 67% of the variance in scores for second-year students, and up to 30% of the variance for third-year students, compared to 45% and 1%, respectively, for third-year student scores. Differences between second- and third-year student performances may be accounted for by the presence of both content and process dimensions in problem-solving strategies.Subjects--Topical Terms:
1017742
Psychology, Psychometrics.
Assessing clinical competence: Differentiating experts in veterinary medicine from novices by their sequence of responses in clinical simulations.
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Expert clinicians learn through experience the most efficient and effective way to solve clinical problems. To the extent that this experience aids these experts in identifying the most important cues in the problem presentation and the most important actions to take given those cues, experts should follow a more specific sequence of actions than novices when confronted with the same clinical problems. This study compared the response sequences of 80 experienced veterinarians with 284 veterinary students on a computerized version of the Clinical Competency Test in Veterinary Medicine (CCT), using an empirical strategy of scale constructions. All methods of coding response sequences were superior to standard CCT scoring methods at differentiating the students from the professionals, although large variations between second- and third-year students and between individual problem scores were noted. No one method for encoding sequence of three examined emerged as clearly superior on all problems for both student groups, although there were some differences in individual problem scores. Empirically derived scales based on sequence outperformed unit-weighted endorsement scales on half the problems, but this advantage all but disappeared when regression-based weights were applied to the endorsement-selected items. Empirical scales accounted for up to 67% of the variance in scores for second-year students, and up to 30% of the variance for third-year students, compared to 45% and 1%, respectively, for third-year student scores. Differences between second- and third-year student performances may be accounted for by the presence of both content and process dimensions in problem-solving strategies.
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