2000Human Factors The Journal of the Human Factors and Ergonomics SocietyOpen access

Measuring Team Knowledge

Nancy J. Cooke, Eduardo Salas, Janis A. Cannon‐Bowers, Renée J. Stout

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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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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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Available 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.

Key concepts: Knowledge management, Cognition, Team effectiveness, Relation (database), Computer science, Team composition, Context (archaeology), Empirical research

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