AI를 활용한 산업안전교육 프로그램 개발 요구조사

Abstract

Objectives: This study aimed to identify workplace demands and necessities for the development of AI·VR-based program to enhance the effectiveness of industrial safety education. The research particularly examined differences by business size and factors influencing workers’ willingness to adopt such systems. Methods: A structured survey was conducted with 107 employees from various industries nationwide. The questionnaire covered general char- acteristics, current safety education status, and the necessity of digital safety education systems. Data analysis included frequency distribution, cross-tab- ulation with chi-square and Fisher’s exact tests, and logistic regression to determine predictors of willingness to participate in AI-based program. Results: Workplaces with fewer than 50 employees, despite weak digital infrastructure, showed high expectations for accident reduction and demand for train- ing focused on critical risks, while those with over 300 employees emphasized data-driven evaluation and training optimization. Work experience, digital technology use, and recognition of the need for digital safety training were significant predictors of adoption intention. However, AI·VR training remains in an early stage of adoption, with technical limitations and workplace acceptance issues identified as barriers. Conclusions: The findings highlight the importance of differentiated strategies tailored to workplace size. Small businesses require support for digital infrastructure and practical training mod- ules, while large organizations need advanced systems for evaluation and optimization. This study provides foundational insights for the design of AI·VR- based education Program contributes to policy and institutional improvements for industrial accident prevention.