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Systematic evaluation and increased structure in a radiology elective.

Abstract

Diagnostic radiology is expanding, playing an increasingly central role in patient care, which heightens the importance of radiology teaching in undergraduate medical education. This study examined the impact of increased structure and systematic evaluation on student performance in a radiology elective. The evaluation protocol included premultiple and postmultiple choice examinations (70 questions each), a film interpretation quiz (ten films, 20 questions), faculty assessment of a student oral case presentation, and student evaluations of the elective experience. The relationships among the evaluation techniques, as well as differences in class level and course ratings were also examined. Two different treatment groups were studied. Group 1 was given general objectives and information regarding availability of recommended resources, including self-learning materials for the elective, didactic seminars, and viewbox exposure. Group 2 was given specific written instructional objectives, a structured schedule for viewing the self-learning materials, and the same seminars and viewbox exposure. The statistically significant higher performance of the structured group suggests that medical students achieve the objectives of an elective better when learning activities are well defined, structured, and systematically evaluated. In addition, those students receiving the structured experience rated the radiology elective more favorably.

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BibTeXRIS

C E Blane, J G Calhoun, B R Maxim, W Martel, W K Davis. Systematic evaluation and increased structure in a radiology elective.. https://doi.org/10.1097/00004424-198505000-00003

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Conditional reliability of admissions interview ratings: extreme ratings are the most informative.

CONTEXT: Admissions interviews are unreliable and have poor predictive validity, yet are the sole measures of non-cognitive skills used by most medical school admissions departments. The low reliability may be due in part to variation in conditional reliability across the rating scale. OBJECTIVES: To describe an empirically derived estimate of conditional reliability and use it to improve the predictive validity of interview ratings. METHODS: A set of medical school interview ratings was compared to a Monte Carlo simulated set to estimate conditional reliability controlling for range restriction, response scale bias and other artefacts. This estimate was used as a weighting function to improve the predictive validity of a second set of interview ratings for predicting non-cognitive measures (USMLE Step II residuals from Step I scores). RESULTS: Compared with the simulated set, both observed sets showed more reliability at low and high rating levels than at moderate levels. Raw interview scores did not predict USMLE Step II scores after controlling for Step I performance (additional r2 = 0.001, not significant). Weighting interview ratings by estimated conditional reliability improved predictive validity (additional r2 = 0.121, P < 0.01). CONCLUSIONS: Conditional reliability is important for understanding the psychometric properties of subjective rating scales. Weighting these measures during the admissions process would improve admissions decisions.

Education, Medical, Undergraduate↗