Design of an IoT-Based Remote Learning System for Medical Skill Training in the Age of COVID-19: Focusing on CPR Skill Training

Abstract

Medical skill education has been scaled down due to the COVID-19 pandemic. In particular, the decrease in CPR skill training has caused the quality of medical services to deteriorate. While new online education methods have emerged, few studies exist on online teaching and its effects. Since the online teaching of medical skills presents several challenges for instructors, it has not been as effective as face-to-face training. This study designed a new remote system focusing on medical skill education. The proposed video-based application prototype uses an IoT device to measure CPR performance metrics and provides real-time data to users. It was tested using the Kano model on a small group of subjects. The effects of skill training were analyzed quantitatively and qualitatively. A comparative analysis of the remote group and face-to-face group revealed similar average values for appropriate compression depth. In other categories, the remote group fared poorer than the face-to-face group. Considering the high scores given to system usability in the USE survey, remote education shows promise as an alternative to face-to-face education. The significance of this study lies in being the first to develop and test a remote education system for medical skill training in the age of COVID-19.

Design and Implementation of an English Mobile Learning System Based on Weighted Naive Bayes

“…To support flexible learning, the system should also be designed to be easily accessible and user-friendly, with good mobile adaptability and stable performance [6] . Data analysis and learning assessment functionalities are important components of the English mobile learning system, aimed at collecting and analyzing learning data to evaluate learning outcomes and provide valuable insights to learners.…”