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Effect of Intelligent Tutor Induced Pausing on Learning Simulated Surgical Skills

McGill University · 2024
ClinicalTrials.gov · Datasets · License: Public Domain · 2024
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artificial-intelligenceclinical-trialmedical-studentsnaneurosurgeryvirtual-reality
Traditional training of surgical technical skills relies on mentorship from experienced surgeons, who continuously evaluate and change trainee performance to prevent errors and potential patient harm by providing verbal instructions. These educators may also pause the procedure, explaining the risks associated with the trainee's actions, and may personally demonstrate proper techniques to the students. Studies examining pausing while providing medical care outline that these approaches allow for learning. An artificial intelligent (AI) tutoring system, the Intelligent Continuous Expertise Monitoring System (ICEMS), improves learning in a surgical simulated operation by providing trainees with verbal instructions upon error identification. However, the effect of including a pause during this AI teaching has not been studied. Therefore, the ICEMS post-error identification methodology has been altered to include a pause with the intelligent tutor voice instruction. The aim of this study is to determine the effect of pausing on surgical skill acquisition and transfer among pre-medical and medical students. This will be done by comparing their performance in repeated simulated tumour resection tasks.
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