Intelligent Clinical Training during the COVID-19 Pandemic

被引:1
作者
Suebnukarn, Siriwan [1 ]
机构
[1] Thammasat Univ, Res & Innovat Div, Pathum Thani, Thailand
来源
2021 18TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE-2021) | 2021年
关键词
COVID-19; intelligent tutoring system; virtual reality; e-learning; clinical training; VIRTUAL-REALITY; TOMOGRAPHY;
D O I
10.1109/JCSSE53117.2021.9493841
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Clinical training is one of the most challenging areas for education especially during the COVID-19 pandemic. There are limited access to apprenticeship training in the complex scenarios with corresponding difficulty training in a time-effective manner. Our work on intelligent clinical training systems provides one effective solution to this problem by introducing intelligent clinical training systems that can supplement tutoring sessions by expert clinical instructors. The Bayesian representation techniques and algorithms for generating tutoring feedback in medical problem-based learning group problem solving made important contributions to the field of Intelligent Tutoring Systems. In particular, it was one of the first systems for tutoring groups of students and the first intelligent tutoring systems for medical problem-based learning. The virtual reality simulator we developed is one of the most sophisticated dental simulators. It stands out as the first dental simulator to integrate sophisticated analysis of the surgical procedure. Particularly noteworthy is also the creative way to understand important issues such as differences in expert and novice performance, the effectiveness of virtual pre-operative practice, and the teaching effectiveness of the simulator. The systems have been implemented in undergrad pre-clinical training and postgrad pre-surgical training with strong scientific evidence of their effectiveness.
引用
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页数:5
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