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Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
Published on: March 3, 2023
Does self-modulated learning vs. algorithm-regulated learning of dermatology morphology affect learning efficiency of
Danya Traboulsi1, Jori Hardin1, Laurie Parsons1
1Division of Dermatology, Department of Medicine, University of Calgary, Alberta, Canada.
Background:
Deliberate practice is an important method of skill acquisition and is under-utilized in dermatology training. We delivered a dermatologic morphology training module with immediate feedback for first year medical students. Our goal was to determine whether there are differences in accuracy and learning efficiency between self- regulated and algorithm-regulated groups.
Methods:
First year medical students at the University of Calgary completed a dermatologic morphology module. We randomly assigned them to either a self-regulated arm (students removed cases from the practice pool at their discretion) or an algorithm-regulated arm (an algorithm determined when a case would be removed). We then administered a pre-survey, pre-test, post-test, and post-survey. Data collected included mean diagnostic accuracy of the practice sessions and tests, and the time spent practicing. The surveys assessed demographic data and student satisfaction.
Results:
Students in the algorithm-regulated arm completed more cases than the self-regulated arm (52.9 vs. 29.3, p<0.001) and spent twice as much time completing the module than the self-regulated participants (34.3 vs. 17.0 min., p<0.001). Mean scores were equivalent between the algorithm- and self-regulated groups for the pre-test (63% vs. 66%, n = 54) and post-test (90% vs. 86%, n = 10), respectively. Both arms demonstrated statistically significant improvement in the post-test.
Conclusion:
Both the self-regulated and algorithm-regulated arms improved at post-test. Students spent significantly less time practicing in the self-directed arm, suggesting it was more efficient.
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