The relation between learners' experience in simulations and diagnostic accuracy: generalizability across medical and teacher education

  • Simulation-based learning is being increasingly implemented across different domains of higher education to facilitate essential skills and competences (e.g. diagnostic skills, problem-solving, etc.). However, the lack of research that assesses and compares simulations used in different contexts (e.g., from design perspective) makes it challenging to effectively transfer good practices or establish guidelines for effective simulations across different domains. This study suggests some initial steps to address this issue by investigating the relations between learners' experience in simulation-based learning environments and learners' diagnostic accuracy across several different domains and types of simulations, with the goal of facilitating cross-domain research and generalizability. The findings demonstrate that used learners' experience ratings are correlated with objective performance measures, and can be used for meaningful comparisons across different domains. Measures ofSimulation-based learning is being increasingly implemented across different domains of higher education to facilitate essential skills and competences (e.g. diagnostic skills, problem-solving, etc.). However, the lack of research that assesses and compares simulations used in different contexts (e.g., from design perspective) makes it challenging to effectively transfer good practices or establish guidelines for effective simulations across different domains. This study suggests some initial steps to address this issue by investigating the relations between learners' experience in simulation-based learning environments and learners' diagnostic accuracy across several different domains and types of simulations, with the goal of facilitating cross-domain research and generalizability. The findings demonstrate that used learners' experience ratings are correlated with objective performance measures, and can be used for meaningful comparisons across different domains. Measures of perceived extraneous cognitive load were found to be specific to the simulation and situation, while perceived involvement and authenticity were not. Further, the negative correlation between perceived extraneous cognitive load and perceived authenticity was more pronounced in interaction-based simulations. These results provide supporting evidence for theoretical models that highlight the connection between learners' experience in simulated learning environments and their performance. Overall, this research contributes to the understanding of the relationship between learners’ experience in simulation-based learning environments and their diagnostic accuracy, paving the way for the dissemination of best practices across different domains within higher education.show moreshow less

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Metadaten
Author:Olga Chernikova, Matthias Stadler, Daniel Sommerhoff, Christian Schons, Nicole Heitzmann, Doris Holzberger, Tina Seidel, Constanze Richters, Amadeus J. PickalORCiDGND, Christof Wecker, Michael Nickl, Elias Codreanu, Stefan Ufer, Stephanie Kron, Caroline Corves, Birgit J. Neuhaus, Martin R. Fischer, Frank Fischer
URN:urn:nbn:de:bvb:384-opus4-1146287
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/114628
ISSN:2451-9588OPAC
Parent Title (English):Computers in Human Behavior Reports
Publisher:Elsevier BV
Type:Article
Language:English
Year of first Publication:2024
Publishing Institution:Universität Augsburg
Release Date:2024/08/02
Volume:15
First Page:100454
DOI:https://doi.org/10.1016/j.chbr.2024.100454
Institutes:Philosophisch-Sozialwissenschaftliche Fakultät
Philosophisch-Sozialwissenschaftliche Fakultät / Empirische Bildungsforschung
Philosophisch-Sozialwissenschaftliche Fakultät / Empirische Bildungsforschung / Lehrstuhl für Learning Analytics and Educational Data Mining
Dewey Decimal Classification:3 Sozialwissenschaften / 30 Sozialwissenschaften, Soziologie / 300 Sozialwissenschaften
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)