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Investigating a self-scoring interview simulation for learning and assessment in the medical consultation
Journal article   Open access   Peer reviewed

Investigating a self-scoring interview simulation for learning and assessment in the medical consultation

Catherine Bruen, Clarence Kreiter, Vincent Wade and Teresa Pawlikowska
Advances in medical education and practice, Vol.8, pp.353-358
01/01/2017
DOI: 10.2147/AMEP.S128321
PMCID: PMC5457147
PMID: 28603434
url
https://doi.org/10.2147/AMEP.S128321View
Published (Version of record) Open Access

Abstract

Experience with simulated patients supports undergraduate learning of medical consultation skills. Adaptive simulations are being introduced into this environment. The authors investigate whether it can underpin valid and reliable assessment by conducting a generalizability analysis using IT data analytics from the interaction of medical students (in psychiatry) with adaptive simulations to explore the feasibility of adaptive simulations for supporting automated learning and assessment. The generalizability (G) study was focused on two clinically relevant variables: clinical decision points and communication skills. While the G study on the communication skills score yielded low levels of true score variance, the results produced by the decision points, indicating clinical decision-making and confirming user knowledge of the process of the Calgary-Cambridge model of consultation, produced reliability levels similar to what might be expected with rater-based scoring. The findings indicate that adaptive simulations have potential as a teaching and assessment tool for medical consultations.
Education & Educational Research Education, Scientific Disciplines Social Sciences

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