Suchergebnisse

Objective: The present study investigated factors that explain when and why different groups of teammates are more likely to request and accept backup from one another when needed in an environment characterized by extreme time pressure and severe consequences of error: commercial air traffic control (ATC). Background: Transactive memory theory states that teammates develop consensus regarding the distribution of their relative expertise as well as confidence in that expertise over time and that this facilitates coordination processes. The present study investigated whether this theory could help to explain between-team differences in requesting and accepting backup when needed. Method: The present study used cross-sectional data collected from 51 commercial ATC teams. Hypotheses were tested using multiple regression analysis. Results: Teammates with greater experience working together requested and accepted backup from one another more than those with lesser experience working together. Teammate knowledge consensus and perceived team efficacy appear to have mediated this relationship. Conclusion: Transactive memory theory extends to high-stress environments in which members' expertise is highly overlapping. Teammates' shared mental models about one another increase the likelihood that they will request and accept backup. Application: Teammate familiarity should be considered when choosing among potential replacement team members. Training strategies that accelerate the development of teammate knowledge consensus and team efficacy are warranted.

This research investigated the effects of guided team self-correction using an empirically derived expert model of teamwork as the organizing framework. First, the authors describe the process used to define this model. Second, they report findings from two studies in which the expert model was used to structure the process of guided team self-correction. Participants were U.S. Navy command and control teams (25 in Study 1, 13 in Study 2). Results indicated that teams debriefed using the expert model-driven guided team self-correction approach developed more accurate mental models of teamwork (Study 1) and demonstrated greater teamwork processes and more effective outcomes (Study 2) than did teams debriefed using a less participative and chronologically organized approach that is more typical for these teams.

Objective: This article presents a model for predicting complex collaborative processes as they arise in one-of-a-kind problem-solving situations to predict performance outcomes. The goal is to outline a set of key processes and their interrelationship and to describe how these can be used to predict collaboration processes embedded within problem-solving contexts. Background: Teams are increasingly called upon to address complex problem-solving tasks in novel situations. This represents a domain of performance that to date has been underrepresented in the research literature. Method: Multidisciplinary theoretical and empirical literature relating to knowledge work in teams is synthesized. Results: A set of propositions developed to guide research into how teams externalize cognition and build knowledge in service of problem solving is presented. First, a brief overview of macrocognition in teams is provided to distinguish the present work from other views of team cognition. Second, a description of the foundational theoretical concepts driving the theory of macrocognition in teams presented here is provided. Third, a set of propositions described within the context of a model of macrocognition in teams is forwarded. Conclusion: The theoretical framework described in this article provides a set of empirically testable propositions that can ultimately guide practitioners in efforts to support macrocognition in teams. Application: A theory of macrocognition in teams can provide guidance for the development of training interventions and the design of collaborative tools to facilitate knowledge-based performance in teams.