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PubMed · 9743779

Tutor intervention profile: reliability and validity.

Abstract

An instrument has been developed to provide tutors with feedback about their performance in problem-based tutorial groups. This questionnaire consists of 33 statements reflecting the behaviour of the tutor in the tutorial group when students analyse the case and generate learning issues and the behaviour of the tutor when students report back to the tutorial group about their self-study. The statements are grouped on theoretical dimensions found in the literature about co-operative learning and problem-based learning. This study focuses on the validity and the reliability of this instrument. Confirmatory factor analysis showed that a four-factor model showed a weak fit, whereas each separate factor fitted the data reasonably well. The four factors are: (1) elaboration; (2) directing the learning process; (3) integration of knowledge and (4) stimulating interaction and individual accountability. These factors were strongly correlated with the overall judgement of the tutor at the end of the unit, so the concurrent validity of this instrument was high. Generalizability studies indicated that the rating scales provide reliable information with a sample size of student responses falling within the range of real tutorial group sizes. The results of this study show that the instrument for providing tutors with feedback is valid and reliable. This questionnaire can be used in staff development activities and also provides needs assessment for faculty development.

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BibTeXRIS

W S De Grave, D H Dolmans, C P van der Vleuten. 1998. Tutor intervention profile: reliability and validity.. https://doi.org/10.1046/j.1365-2923.1998.00226.x

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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↗