Communication Networks and Team Workload in a Command and Control Synthetic Task Environment
abstract: Despite the prevalence of teams in complex sociotechnical systems, current approaches to understanding workload tend to focus on the individual operator. However, research suggests that team workload has emergent properties and is not necessarily equivalent to the aggregate of individual w...
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ndltd-asu.edu-item-627392020-12-09T05:00:40Z Communication Networks and Team Workload in a Command and Control Synthetic Task Environment abstract: Despite the prevalence of teams in complex sociotechnical systems, current approaches to understanding workload tend to focus on the individual operator. However, research suggests that team workload has emergent properties and is not necessarily equivalent to the aggregate of individual workload. Assessment of communications provides a means of examining aspects of team workload in highly interdependent teams. This thesis set out to explore how communications are associated with team workload and performance under high task demand in all-human and human–autonomy teams in a command and control task. A social network analysis approach was used to analyze the communications of 30 different teams, each with three members operating in a command and control task environment of over a series of five missions. Teams were assigned to conditions differentiated by their composition with either a naïve participant, a trained confederate, or a synthetic agent in the pilot role. Social network analysis measures of centralization and intensity were used to assess differences in communications between team types and under different levels of demand, and relationships between communication measures, performance, and workload distributions were also examined. Results indicated that indegree centralization was greater in the all-human control teams than in the other team types, but degree centrality standard deviation and intensity were greatest in teams with a highly trained experimenter pilot. In all three team types, the intensity of communications and degree centrality standard deviation appeared to decrease during the high demand mission, but indegree and outdegree centralization did not. Higher communication intensity was associated with more efficient target processing and more successful target photos per mission, but a clear relationship between measures of performance and decentralization of communications was not found. Dissertation/Thesis Johnson, Craig Jonathon (Author) Cooke, Nancy J (Advisor) Gray, Robert (Committee member) Gutzwiller, Robert S (Committee member) Arizona State University (Publisher) Experimental psychology Organizational behavior Robotics Command and Control Communication Human–Autonomy Teaming Social Network Analysis Teamwork Workload eng 106 pages Masters Thesis Human Systems Engineering 2020 Masters Thesis http://hdl.handle.net/2286/R.I.62739 http://rightsstatements.org/vocab/InC/1.0/ 2020 |
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English |
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Dissertation |
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Experimental psychology Organizational behavior Robotics Command and Control Communication Human–Autonomy Teaming Social Network Analysis Teamwork Workload |
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Experimental psychology Organizational behavior Robotics Command and Control Communication Human–Autonomy Teaming Social Network Analysis Teamwork Workload Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
description |
abstract: Despite the prevalence of teams in complex sociotechnical systems, current approaches to understanding workload tend to focus on the individual operator. However, research suggests that team workload has emergent properties and is not necessarily equivalent to the aggregate of individual workload. Assessment of communications provides a means of examining aspects of team workload in highly interdependent teams. This thesis set out to explore how communications are associated with team workload and performance under high task demand in all-human and human–autonomy teams in a command and control task. A social network analysis approach was used to analyze the communications of 30 different teams, each with three members operating in a command and control task environment of over a series of five missions. Teams were assigned to conditions differentiated by their composition with either a naïve participant, a trained confederate, or a synthetic agent in the pilot role. Social network analysis measures of centralization and intensity were used to assess differences in communications between team types and under different levels of demand, and relationships between communication measures, performance, and workload distributions were also examined. Results indicated that indegree centralization was greater in the all-human control teams than in the other team types, but degree centrality standard deviation and intensity were greatest in teams with a highly trained experimenter pilot. In all three team types, the intensity of communications and degree centrality standard deviation appeared to decrease during the high demand mission, but indegree and outdegree centralization did not. Higher communication intensity was associated with more efficient target processing and more successful target photos per mission, but a clear relationship between measures of performance and decentralization of communications was not found. === Dissertation/Thesis === Masters Thesis Human Systems Engineering 2020 |
author2 |
Johnson, Craig Jonathon (Author) |
author_facet |
Johnson, Craig Jonathon (Author) |
title |
Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
title_short |
Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
title_full |
Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
title_fullStr |
Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
title_full_unstemmed |
Communication Networks and Team Workload in a Command and Control Synthetic Task Environment |
title_sort |
communication networks and team workload in a command and control synthetic task environment |
publishDate |
2020 |
url |
http://hdl.handle.net/2286/R.I.62739 |
_version_ |
1719368794483195904 |