Journal Article


Teresa Pawlikowska
Vincent Wade
Clarence Kreiter
Catherine Bruen



teaching tool assessment for learning self learning learning and assessment teaching and assessment medical consultation self assessment decision making

Investigating a self-scoring interview simulation for learning and assessment in the medical consultation. (2017)

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.
Collections Ireland -> Royal College of Surgeons in Ireland -> PubMed

Full list of authors on original publication

Teresa Pawlikowska, Vincent Wade, Clarence Kreiter, Catherine Bruen

Experts in our system

Vincent Patrick Wade
Trinity College Dublin
Total Publications: 123