Enhancing Remote Industrial Training Experiences with Asymmetric Virtual Reality: Experiences, Tools and Guidelines

Training in virtual reality (VR) is a valuable supplementing tool for advancing knowledge transfer that results in increased efficiency and accuracy of technicians in fieldwork. However, COVID-19 pandemic restrictions made it impossible for VR training centers to operate on a full scale, forcing tra...

Full description

Bibliographic Details
Main Authors: Alisa Burova, Viveka Opas, John Mäkelä, Jaakko Hakulinen, Timo Lindqvist, Sanni Siltanen, Roope Raisamo, Markku Turunen
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/15/7745
Description
Summary:Training in virtual reality (VR) is a valuable supplementing tool for advancing knowledge transfer that results in increased efficiency and accuracy of technicians in fieldwork. However, COVID-19 pandemic restrictions made it impossible for VR training centers to operate on a full scale, forcing traditional face-to-face learning sessions to become remote. In this article, we investigate the asymmetric use of a VR training solution—among devices with different levels of immersion and control—to enrich the content of remote training sessions. The VR in this case can be seen as a source of visual and other contextual information to advance the effects of situated learning and enhance knowledge transfer. To evaluate this approach, we conducted a remote user study with ten industrial maintenance and installation experts. We also introduce the “Research Panel” tool to gather reactions of learners during the remote training session. The expert user study results demonstrate the usefulness and relevance of asymmetric VR to improve remote training sessions and other application industrial scenarios, while the “Research Panel” data provided detailed insight into the session flow. Building on the qualitative findings, we present design guidelines to aid the adoption of asymmetric VR in the industrial context.
ISSN:2076-3417