Modeling framework of team contexts for the design of laboratory experiments and team training

Taro Kanno, Satoru Inoue, Daisuke Karikawa, Dingding Chao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper presents a modeling framework of team structure that describes major elements of team settings and conditions and the relationships between them. These are the elements of human, task, resource, expertise, authority, tools and devices, and place. The relationships between these elements can capture and summarize important aspects of team structure such as the distribution and sharing of objects and functions to each team member and the physical environment. This paper provides details of the proposed modeling framework and discusses how to assess and quantify the similarity between a naturalistic team setting and a simulated or game-like setting.

Original languageEnglish
Title of host publicationAdvances in Human Error, Reliability, Resilience, and Performance - Proceedings of the AHFE 2017 International Conference on Human Error, Reliability, Resilience, and Performance, 2017
EditorsRonald Laurids Boring
PublisherSpringer Verlag
Pages155-161
Number of pages7
ISBN (Print)9783319606446
DOIs
Publication statusPublished - 2018
EventAHFE 2017 International Conference on Human Error, Reliability, Resilience, and Performance, 2017 - Los Angeles, United States
Duration: 2017 Jul 172017 Jul 21

Publication series

NameAdvances in Intelligent Systems and Computing
Volume589
ISSN (Print)2194-5357

Conference

ConferenceAHFE 2017 International Conference on Human Error, Reliability, Resilience, and Performance, 2017
Country/TerritoryUnited States
CityLos Angeles
Period17/7/1717/7/21

Keywords

  • Design of experiments and training
  • Mesocognition
  • Similarity assessment
  • Team architecture

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