Automation and its Effects on Mental Workload in Industrial Sectors
| dc.contributor.author | Staab, Verena | |
| dc.date.accessioned | 2024-08-21T11:08:42Z | |
| dc.date.available | 2024-08-21T11:08:42Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Automation technology has profoundly transformed modern life, promising further evolution in safety and efficiency. However, it also fundamentally alters work dynamics, notably in the maritime sector where automation is increasingly prevalent. This dissertation investigates how automated systems impact mental workload and human-technology interactions in maritime contexts. By adapting a framework based on cognitive load theory, it analyzes predictors (e.g., automation, system design, level of autonomy, individual differences) of mental workload through systematic reviews and experimental studies. Key challenges include recruiting specialized maritime participants and deploying equipment in operational settings. By addressing these challenges, the dissertation aims to enhance understanding and implementation of automation, offering practical insights for optimizing human-technology interfaces in maritime automation. | en |
| dc.identifier.doi | 10.18420/muc2024-mci-dc-281 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/44388 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Mensch und Computer 2024 - Workshopband | |
| dc.relation.ispartofseries | Mensch und Computer | |
| dc.rights | https://creativecommons.org/licenses/by/4.0/ | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Human-Machine Interaction | |
| dc.subject | Mental Workload | |
| dc.subject | User Experience | |
| dc.subject | Autonomy | |
| dc.subject | Maritime | |
| dc.title | Automation and its Effects on Mental Workload in Industrial Sectors | en |
| dc.type | Text/Conference Paper | |
| gi.conference.date | 1.-4. September 2024 | |
| gi.conference.location | Karlsruhe | |
| gi.conference.sessiontitle | MCI: Doctoral Consortium |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- muc2024-mci-dc-281.pdf
- Größe:
- 735.05 KB
- Format:
- Adobe Portable Document Format