Validating the CIERT Framework for Critical Incident and Emergency Response Training

Arman Hamzehlou Kahrizi,Alexander Ferworn

2023 16th International Conference on Advanced Computer Theory and Engineering (ICACTE)(2023)

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摘要
This research aims to examine the data's normality, item correlation, and internal consistency within the Critical Incidents and Emergency Response Training framework proposed in a previous study. The experiment was conducted using the Universal Simulation Platform for improvised explosive device neutralization training. Participants from the Computational Public Safety Lab were involved, and we utilized 91 framework items to assess trainee performance and training effectiveness. The results indicated high internal consistency and reliability across most metrics, except for the Usability metric, which displayed lower internal consistency. Additionally, the data underwent normality assessment through the Shapiro-Wilk test. Ultimately, 52 items were retained after removing those with weak correlations with the questionnaire's global score. By refining the framework and selecting relevant metrics, this study offers valuable insights into the effectiveness of software-based simulators for critical incident training. Future research should concentrate on validating and expanding the framework using larger and more diverse participant samples, as well as exploring alternative data transformation techniques and non-parametric methods for analyzing variables that deviate from assumptions of normal distribution.
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关键词
virtual reality,simulator,critical incident and emergency response training,efficacy,metric,framework,training evaluation,skill acquisition,preparedness,response capability
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