ERIC Number: EJ1405384
Record Type: Journal
Publication Date: 2024
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1939-1382
Modeling of Learning Processes Using Continuous-Time Markov Chain for Virtual-Reality-Based Surgical Training in Laparoscopic Surgery
Seunghan Lee; Amar Sadanand Shetty; Lora A. Cavuoto
IEEE Transactions on Learning Technologies, v17 p462-473 2024
Recent usage of virtual reality (VR) technology in surgical training has emerged because of its cost-effectiveness, time savings, and cognition-based feedback generation. However, the quantitative evaluation of its effectiveness in training is still not thoroughly studied. This article demonstrates the effectiveness of a VR-based surgical training simulator in laparoscopic surgery and investigates how stochastic modeling, represented as continuous-time Markov chain (CTMC), can be used to explicit determine the training status of the surgeon. By comparing the training in real environments and in VR-based training simulators, the authors also explore the validity of the VR simulator in laparoscopic surgery. The study further aids in establishing learning models for surgeons, supporting continuous evaluation of training processes for the derivation of real-time feedback by CTMC-based modeling.
Descriptors: Markov Processes, Computer Simulation, Teaching Methods, Surgery, Comparative Analysis, Medical Education, Validity, Feedback (Response), Instructional Effectiveness
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Institute of Biomedical Imaging and Bioengineering (NIBIB) (NIH); National Institutes of Health (NIH) (DHHS)
Authoring Institution: N/A
Grant or Contract Numbers: R44EB019802