@misc{8344,
  abstract     = {{BACKGROUND:The future of work in Germany is shaped by megatrends like globalization, automatization, digitization, and the demographic change. Furthermore, mass customization and the increasing usage of AI even in manual assembly offers new opportunities as well as it creates new challenges. OBJECTIVE:The trend towards mass customization in turn leads to increased complexity in production, which results in additional mental workload. This effect will continue in the foreseeable future. METHOD:Especially for small and medium sized companies, the backbone of Germany’s economy, automatization and Human-Robot-Collaboration will take time to develop. Information assistance systems are and will be a bridging technology to help organizations to manage increasing complexity and the mental workload of their employees to not only boost productivity but also keep their workforce healthy. The ongoing demographic change further underlines the need to use information assistance systems to compensate possible age-associated deficits, but also keep older employees committed to their work and avoid effects of disengagement or disenfranchisement through participatory ergonomics. RESULTS: Information assistance systems can only develop their inherent potential if they are designed to support employees of varying age, competence levels, and affinity for technology. Participatory development and early engagement are key factors for an increased acceptance and usage of the systems as well as the individualization to make it suitable for each individual employee. CONCLUSION:Expanding the functionalities to an adaptive assistance system, using physiological correlates of mental workload as an input, is conceivable in the future. }},
  author       = {{Bläsing, Dominic and Hinrichsen, Sven and Wurm, Susanne and Bornewasser, Manfred}},
  booktitle    = {{Work}},
  issn         = {{1875-9270 }},
  keywords     = {{Cognitive ergonomics, aging workforce, complexity, mixed-model assembly}},
  number       = {{4}},
  pages        = {{1535--1548}},
  publisher    = {{IOS Press}},
  title        = {{{Information assistance systems as preventive mediators between increasing customization and mental workload}}},
  doi          = {{http://doi.org/10.3233/WOR-211283}},
  volume       = {{72}},
  year         = {{2022}},
}

@misc{9360,
  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.}},
  author       = {{Goppold, Marvin and Herrmann, Jan-Phillip and Tackenberg, Sven and Brandl, Christopher and Nitsch , Verena}},
  booktitle    = {{Work}},
  issn         = {{1875-9270 }},
  keywords     = {{Vocational education, digital twin, work system design}},
  number       = {{4}},
  pages        = {{1563--1575}},
  publisher    = {{IOS Press}},
  title        = {{{An error-based augmented reality learning system for work-based occupational safety and health education}}},
  doi          = {{10.3233/WOR-211243}},
  volume       = {{72}},
  year         = {{2022}},
}