View in EDS

An error-based augmented reality learning system for work-based occupational safety and health education.

Saved in:
Bibliographic Details
Title: An error-based augmented reality learning system for work-based occupational safety and health education.
Authors: Goppold, Marvin, Herrmann, Jan-Phillip, Tackenberg, Sven, Brandl, Christopher, Nitsch, Verena
Source: Work; 2022, Vol. 72 Issue 4, p1563-1575, 13p, 4 Black and White Photographs, 2 Diagrams, 2 Charts
Subject Terms: WORK environment, HEALTH education, NATIONAL competency-based educational tests, AUGMENTED reality, INDUSTRIAL safety, VOCATIONAL education, ELECTRICAL injuries, LEARNING strategies, EXPERIENCE, RESEARCH funding
Abstract: BACKGROUND: Errors can have dangerous consequences, resulting in a preventive strategy in most company-based technical vocational education and training (TVET). On the contrary, errors provide a useful opportunity for learning due to mismatches of mental models and reality and especially to improve occupational safety and health (OSH). OBJECTIVE: This article presents a didactic concept for developing a learning system based on learning from errors. Learners shall directly experience the consequences of erroneous actions through presenting error consequences in augmented reality to avoid negative, dangerous, or cost-intensive outcomes. METHODS: Empirical data prove errors to be particularly effective in TVET. A formal description of a work system is systematically adopted to outline a connection between work, errors concerning OSH, and a didactic concept. A proof-of-concept systematically performs a use case for the developed learning system. It supports critical reflections from a technical, safety, and didactical perspective, naming implications and limitations. RESULTS: By learning from errors, a work-based didactic concept supports OSH competencies relying on a learning system. The latter integrates digital twins of the work system to simulate and visualise dangerous error consequences for identified erroneous actions in a technical proof-of-concept. Results demonstrate the ability to detect action errors in work processes and simulations of error consequences in augmented reality. CONCLUSION: The technical learning system for OSH education extends existing learning approaches by showcasing virtual consequences. However, capabilities are limited regarding prepared learning scenarios with predefined critical errors. Future studies should assess learning effectiveness in an industrial scenario and investigate its usability. [ABSTRACT FROM AUTHOR]
Copyright of Work is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:BACKGROUND: Errors can have dangerous consequences, resulting in a preventive strategy in most company-based technical vocational education and training (TVET). On the contrary, errors provide a useful opportunity for learning due to mismatches of mental models and reality and especially to improve occupational safety and health (OSH). OBJECTIVE: This article presents a didactic concept for developing a learning system based on learning from errors. Learners shall directly experience the consequences of erroneous actions through presenting error consequences in augmented reality to avoid negative, dangerous, or cost-intensive outcomes. METHODS: Empirical data prove errors to be particularly effective in TVET. A formal description of a work system is systematically adopted to outline a connection between work, errors concerning OSH, and a didactic concept. A proof-of-concept systematically performs a use case for the developed learning system. It supports critical reflections from a technical, safety, and didactical perspective, naming implications and limitations. RESULTS: By learning from errors, a work-based didactic concept supports OSH competencies relying on a learning system. The latter integrates digital twins of the work system to simulate and visualise dangerous error consequences for identified erroneous actions in a technical proof-of-concept. Results demonstrate the ability to detect action errors in work processes and simulations of error consequences in augmented reality. CONCLUSION: The technical learning system for OSH education extends existing learning approaches by showcasing virtual consequences. However, capabilities are limited regarding prepared learning scenarios with predefined critical errors. Future studies should assess learning effectiveness in an industrial scenario and investigate its usability. [ABSTRACT FROM AUTHOR]
ISSN:10519815
DOI:10.3233/WOR-211243