Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers

This paper discusses results from two successive rounds of virtual mines rescue training. The first round was conducted in a surround projection environment (360-VR), and the second round was conducted in desktop virtual reality (Desktop-VR). In the 360-VR condition, trainees participated as groups,...

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Main Authors: Shiva Pedram, Richard Skarbez, Stephen Palmisano, Matthew Farrelly, Pascal Perez
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Virtual Reality
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/frvir.2021.627333/full
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author Shiva Pedram
Richard Skarbez
Stephen Palmisano
Matthew Farrelly
Pascal Perez
author_facet Shiva Pedram
Richard Skarbez
Stephen Palmisano
Matthew Farrelly
Pascal Perez
author_sort Shiva Pedram
collection DOAJ
description This paper discusses results from two successive rounds of virtual mines rescue training. The first round was conducted in a surround projection environment (360-VR), and the second round was conducted in desktop virtual reality (Desktop-VR). In the 360-VR condition, trainees participated as groups, making collective decisions. In the Desktop-VR condition, trainees could control their avatars individually. Overall, 372 participants took part in this study, including 284 mines rescuers who took part in 360-VR, and 243 in Desktop-VR. (155 rescuers experienced both.) Each rescuer who trained in 360-VR completed a battery of pre- and post-training questionnaires. Those who attended the Desktop-VR session only completed the post-training questionnaire. We performed principal components analysis on the questionnaire data, followed by a multiple regression analysis, the results of which suggest that the chief factor contributing to positive learning outcome was Learning Context, which extracted information about the quality of the learning content, the trainers, and their feedback. Subjective feedback from the Desktop-VR participants indicated that they preferred Desktop-VR to 360-VR for this training activity, which highlights the importance of choosing an appropriate platform for training applications, and links back to the importance of Learning Context. Overall, we conclude the following: 1) it is possible to train effectively using a variety of technologies but technology that is well-suited to the training task is more useful than technology that is “more advanced,” and 2) factors that have always been important in training, such as the quality of human trainers, remain critical for virtual reality training.
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spelling doaj.art-663fdc3e8d1448e9b5d29c7d10d0774e2022-12-21T22:31:19ZengFrontiers Media S.A.Frontiers in Virtual Reality2673-41922021-02-01210.3389/frvir.2021.627333627333Lessons Learned From Immersive and Desktop VR Training of Mines RescuersShiva Pedram0Richard Skarbez1Stephen Palmisano2Matthew Farrelly3Pascal Perez4SMART Infrastructure Facility, University of Wollongong, Wollongong, NSW, AustraliaDepartment of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, AustraliaSchool of Psychology, University of Wollongong, Wollongong, NSW, AustraliaCoal Services Pty Ltd., Lake Macquarie, NSW, AustraliaSMART Infrastructure Facility, University of Wollongong, Wollongong, NSW, AustraliaThis paper discusses results from two successive rounds of virtual mines rescue training. The first round was conducted in a surround projection environment (360-VR), and the second round was conducted in desktop virtual reality (Desktop-VR). In the 360-VR condition, trainees participated as groups, making collective decisions. In the Desktop-VR condition, trainees could control their avatars individually. Overall, 372 participants took part in this study, including 284 mines rescuers who took part in 360-VR, and 243 in Desktop-VR. (155 rescuers experienced both.) Each rescuer who trained in 360-VR completed a battery of pre- and post-training questionnaires. Those who attended the Desktop-VR session only completed the post-training questionnaire. We performed principal components analysis on the questionnaire data, followed by a multiple regression analysis, the results of which suggest that the chief factor contributing to positive learning outcome was Learning Context, which extracted information about the quality of the learning content, the trainers, and their feedback. Subjective feedback from the Desktop-VR participants indicated that they preferred Desktop-VR to 360-VR for this training activity, which highlights the importance of choosing an appropriate platform for training applications, and links back to the importance of Learning Context. Overall, we conclude the following: 1) it is possible to train effectively using a variety of technologies but technology that is well-suited to the training task is more useful than technology that is “more advanced,” and 2) factors that have always been important in training, such as the quality of human trainers, remain critical for virtual reality training.https://www.frontiersin.org/articles/10.3389/frvir.2021.627333/fullVirtual realityImmersive technologyTrainingHigh risk industryMining industryRegression modelling
spellingShingle Shiva Pedram
Richard Skarbez
Stephen Palmisano
Matthew Farrelly
Pascal Perez
Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
Frontiers in Virtual Reality
Virtual reality
Immersive technology
Training
High risk industry
Mining industry
Regression modelling
title Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
title_full Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
title_fullStr Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
title_full_unstemmed Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
title_short Lessons Learned From Immersive and Desktop VR Training of Mines Rescuers
title_sort lessons learned from immersive and desktop vr training of mines rescuers
topic Virtual reality
Immersive technology
Training
High risk industry
Mining industry
Regression modelling
url https://www.frontiersin.org/articles/10.3389/frvir.2021.627333/full
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