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Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering

Chang, Haoqian; Pan, Ziqi; Cristea, Alexandra I.

Authors

Haoqian Chang

Ziqi Pan ziqi.pan2@durham.ac.uk
PGR Student Doctor of Philosophy



Abstract

Safety education and training are vital in the mining industry. However, traditional training relies on passive modalities, such as lectures, videos and brochures. These suffer from sever limitations - poor reproducibility, inefficient resource utilisation, and a lack of interactive feedback in one-size-fits-all training scenarios. Addressing these challenges, we introduce a novel hybrid approach combining virtual reality (VR) and electroencephalography (EEG) for training in the use of underground self-contained self-rescuers (SCSR). The VR component provides an interactive and immersive training experience, to facilitate a higher level of engagement compared to traditional methods. Initial EEG testing showed that VR training could elevate trainees’ brain activity, which may result in higher ratings and satisfaction. Beyond EEG we use also after-scenario questionnaire (ASQ) and system usability scale (SUS).

Citation

Chang, H., Pan, Z., & Cristea, A. I. (2024, July). Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil

Presentation Conference Type Conference Paper (published)
Conference Name AIED 2024: Artificial Intelligence in Education
Start Date Jul 8, 2024
End Date Jul 12, 2024
Online Publication Date Jul 2, 2024
Publication Date Jul 2, 2024
Deposit Date Nov 13, 2024
Publisher Springer Nature
Peer Reviewed Peer Reviewed
Pages 382-387
Series Title Communications in Computer and Information Science
Series ISSN 1865-0929
Book Title Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky
ISBN 9783031643118
DOI https://doi.org/10.1007/978-3-031-64312-5_47
Public URL https://durham-repository.worktribe.com/output/3093249