Systematic literature review on usability and training outcomes of using digital training technologies in industry
This state-of-the-art literature review synthesizes findings from 33 articles reporting on the usability and training outcomes of digital training technologies and methods for industrial job roles, adhering to PRISMA guidelines, and analyzed based on PICOC framework. Collaborative efforts between ac...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Computers in Human Behavior Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2451958825000193 |
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| Summary: | This state-of-the-art literature review synthesizes findings from 33 articles reporting on the usability and training outcomes of digital training technologies and methods for industrial job roles, adhering to PRISMA guidelines, and analyzed based on PICOC framework. Collaborative efforts between academia and industry have led to industrial training evaluations. Most of which focus on augmented reality (AR) and mixed reality (MR). For benchmarking, digital training is commonly compared to paper-based manuals before digital instructions and peer-training, although a significant number of studies lack comparative analysis. Effectiveness, efficiency, and satisfaction are the primary parameters for assessing usability, with many studies prioritizing quantitative measures such as task completion times and error rates. Only 12 studies evaluated all three usability parameters, and a mere five papers incorporated major learning theories, with just three considering both learning theories and usability, indicating a need for more interdisciplinary research. While digital training technologies generally show improved performance over traditional manuals, comparisons with peer-training yield inconsistent results. This variability, combined with differences in context, populations, and evaluation methods, suggests that broader research is needed for definitive conclusions on the potential performance gains achieved by utilizing digital training technologies. |
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| ISSN: | 2451-9588 |