An investigation of the difficulty of computer-based case simulations.
This study investigated the characteristics of computer-based case simulations (CCS) that may be associated with case difficulty. Difficulty was defined as the average rating by physicians of examinee performance on a nine-point scale or the passing rate on the cases. Two data sets were used, one fr...
| Publicado en: | Medical Education Vol. 32; no. 2; pp. 150 - 159 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
Mar1998
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105976171&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105976171 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03080110 ESF jtl: Medical Education issn: 03080110 maglogo: Y pubinfo: dt: Mar1998 vid: 32 iid: 2 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 105976171 2009781610 NLM9743766 105976171 ppf: 150 ppct: 9 formats: fmt: @attributes: type: P tig: atl: An investigation of the difficulty of computer-based case simulations. aug: au: Scheuneman JD Van Fan Y Clyman SG sug: subj: Computer Simulation Education, Medical Educational Measurement Feedback Female Male Pennsylvania Physical Examination Teaching Female Male ab: This study investigated the characteristics of computer-based case simulations (CCS) that may be associated with case difficulty. Difficulty was defined as the average rating by physicians of examinee performance on a nine-point scale or the passing rate on the cases. Two data sets were used, one from an administration of 18 cases, the other from an administration of 22 cases with 13 cases used on both occasions. Stepwise regression procedures were used separately for case properties and for analytic scoring of key variables to identify the best sets of predictors of case difficulty. Because of the small number of cases, regression results were evaluated for consistency across both data and both difficulty measures. For key variables, the best set of predictors included the number of different serious errors of commission, risk items, and benefit items. In general, cases were more difficult for higher values of these variables. For case variables, the only consistent variable was the length of the paragraph that provided patient history, with longer paragraphs associated with more difficult cases. Other variables were less consistent, but were often related to the structure of the simulation or the severity of the patient condition. Although the findings for case variables were limited, the analyses were very helpful in illuminating the interconnections among the variables within cases. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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