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Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination
Cognitive work analysis is useful to develop displays for complex situations, but it has not been well explored in providing support for human-automation coordination. To fill this gap, we propose a degree of automation (DOA) layering approach, demonstrated by modeling an automated financial trading...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187463/ https://www.ncbi.nlm.nih.gov/pubmed/30369838 http://dx.doi.org/10.1177/1555343417709669 |
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author | Li, Yeti Burns, Catherine M. |
author_facet | Li, Yeti Burns, Catherine M. |
author_sort | Li, Yeti |
collection | PubMed |
description | Cognitive work analysis is useful to develop displays for complex situations, but it has not been well explored in providing support for human-automation coordination. To fill this gap, we propose a degree of automation (DOA) layering approach, demonstrated by modeling an automated financial trading domain, with a goal of supporting interface design in this domain. The abstraction hierarchy and the decision ladder each adopted an additional layer, mapping functions allocated to the trader and to the automation. In addition to the mapping, we marked the four stages of automation on the decision ladder to provide guidance on representing the function allocation at the task level. Next, we compared the DOA layering approach to how automation was represented in the cognitive work analysis literature. We found that a DOA-layered decision ladder, which included well-developed knowledge of the stages and levels of automation, can be suited to modern automated systems with different DOAs. This study suggests that the DOA layering approach has important implications for designing automation displays and deciding stages and levels of automation and may be a useful approach for modeling adaptive automation. |
format | Online Article Text |
id | pubmed-6187463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-61874632018-10-24 Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination Li, Yeti Burns, Catherine M. J Cogn Eng Decis Mak Article Cognitive work analysis is useful to develop displays for complex situations, but it has not been well explored in providing support for human-automation coordination. To fill this gap, we propose a degree of automation (DOA) layering approach, demonstrated by modeling an automated financial trading domain, with a goal of supporting interface design in this domain. The abstraction hierarchy and the decision ladder each adopted an additional layer, mapping functions allocated to the trader and to the automation. In addition to the mapping, we marked the four stages of automation on the decision ladder to provide guidance on representing the function allocation at the task level. Next, we compared the DOA layering approach to how automation was represented in the cognitive work analysis literature. We found that a DOA-layered decision ladder, which included well-developed knowledge of the stages and levels of automation, can be suited to modern automated systems with different DOAs. This study suggests that the DOA layering approach has important implications for designing automation displays and deciding stages and levels of automation and may be a useful approach for modeling adaptive automation. SAGE Publications 2017-05-22 2017-12 /pmc/articles/PMC6187463/ /pubmed/30369838 http://dx.doi.org/10.1177/1555343417709669 Text en © 2017, Human Factors and Ergonomics Society http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Article Li, Yeti Burns, Catherine M. Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title | Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title_full | Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title_fullStr | Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title_full_unstemmed | Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title_short | Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination |
title_sort | modeling automation with cognitive work analysis to support human-automation coordination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187463/ https://www.ncbi.nlm.nih.gov/pubmed/30369838 http://dx.doi.org/10.1177/1555343417709669 |
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