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Automated summative feedback improves performance and retention in simulation training of mastoidectomy: a randomised controlled trial
Published online by Cambridge University Press: 28 October 2021
Abstract
This study aimed to investigate the effects of automated metrics-based summative feedback on performance, retention and cognitive load in distributed virtual reality simulation training of mastoidectomy.
Twenty-four medical students were randomised in two groups and performed 15 mastoidectomies on a distributed virtual reality simulator as practice. The intervention group received additional summative metrics-based feedback; the control group followed standard instructions. Two to three months after training, participants performed a retention test without learning supports.
The intervention group had a better final-product score (mean difference = 1.0 points; p = 0.001) and metrics-based score (mean difference = 12.7; p < 0.001). At retention, the metrics-based score for the intervention group remained superior (mean difference = 6.9 per cent; p = 0.02). Also at the retention, cognitive load was higher in the intervention group (mean difference = 10.0 per cent; p < 0.001).
Summative metrics-based feedback improved performance and lead to a safer and faster performance compared with standard instructions and seems a valuable educational tool in the early acquisition of temporal bone skills.
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- Copyright © The Author(s), 2021. Published by Cambridge University Press
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Dr A Frithioff takes responsibility for the integrity of the content of the paper
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