TY - JOUR
T1 - The relation between learners’ experience in simulations and diagnostic accuracy
T2 - Generalizability across medical and teacher education
AU - Chernikova, Olga
AU - Stadler, Matthias
AU - Sommerhoff, Daniel
AU - Schons, Christian
AU - Heitzmann, Nicole
AU - Holzberger, Doris
AU - Seidel, Tina
AU - Richters, Constanze
AU - Pickal, Amadeus J.
AU - Wecker, Christof
AU - Nickl, Michael
AU - Codreanu, Elias
AU - Ufer, Stefan
AU - Kron, Stephanie
AU - Corves, Caroline
AU - Neuhaus, Birgit J.
AU - Fischer, Martin R.
AU - Fischer, Frank
N1 - Publisher Copyright:
© 2024
PY - 2024/8
Y1 - 2024/8
N2 - 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 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.
AB - 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 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.
KW - Cross-domain research
KW - Diagnostic skills
KW - Higher education
KW - Learners' experience
KW - Simulation-based learning
UR - http://www.scopus.com/inward/record.url?scp=85197545860&partnerID=8YFLogxK
U2 - 10.1016/j.chbr.2024.100454
DO - 10.1016/j.chbr.2024.100454
M3 - Article
AN - SCOPUS:85197545860
SN - 2451-9588
VL - 15
JO - Computers in Human Behavior Reports
JF - Computers in Human Behavior Reports
M1 - 100454
ER -