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Cited by 588

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Measuring Team Knowledge

Open access
Cooke, Nancy J., Salas, Eduardo, Cannon-Bowers, Janis A., Stout, Renée J.·2000·Human Factors: The Journal of the Human Factors and Ergonomics Society

Abstract

Multioperator tasks often require complex cognitive processing at the team level. Many team cognitive processes, such as situation assessment and coordination, are thought to rely on team knowledge. Team knowledge is multifaceted and comprises relatively generic knowledge in the form of team mental models and more specific team situation models. In this methodological review paper, we review recent efforts to measure team knowledge in the context of mapping specific methods onto features of targeted team knowledge. Team knowledge features include type, homogeneity versus heterogeneity, and rate of knowledge change. Measurement features include knowledge elicitation method, team metric, and aggregation method. When available, we highlight analytical conclusions or empirical data that support a connection between team knowledge and measurement method. In addition, we present empirical results concerning the relation between team knowledge and performance for each measurement method and identify research and methodological needs. Addressing issues surrounding the measurement of team knowledge is a prerequisite to understanding team cognition and its relation to team performance and to designing training programs or devices to facilitate team cognition.

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Metadata

Authors
Cooke, N. J., Salas, E., Cannon-Bowers, J. A., & Stout, R. J.
Venue
Human Factors: The Journal of the Human Factors and Ergonomics Society
Published
2000-03
Volume
42
Issue
1
Pages
151-173
ISSN
  • 0018-7208 (ISSN-L)
  • 1547-8181
OpenAlex
W2156274117
Cited by
588
References
4
FWCI
19.83
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Measuring Team Knowledge. https://app.cochat.ai/papers/10.1518/001872000779656561
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Cooke, N. J., Salas, E., Cannon-Bowers, J. A., & Stout, R. J. (2000). Measuring Team Knowledge. Human Factors: The Journal of the Human Factors and Ergonomics Society. https://doi.org/10.1518/001872000779656561

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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