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Article . 2022 . Peer-reviewed
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Article . 2022
Data sources: mEDRA
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An error-based augmented reality learning system for work-based occupational safety and health education

Authors: Marvin, Goppold; Jan-Phillip, Herrmann; Sven, Tackenberg;

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

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.

Keywords

Vocational Education, Augmented Reality, Educational Status, Humans, Health Education, Occupational Health

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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