Suchergebnisse

Objective: We report an experiment in which three training approaches are compared with the goal of training adaptive teams. Background: Cross-training is an established method in which team members are trained with the goal of building shared knowledge. Perturbation training is a new method in which team interactions are constrained to provide new coordination experiences during task acquisition. These two approaches, and a more traditional procedural approach, are compared. Method: Assigned to three training conditions were 26 teams. Teams flew nine simulated uninhabited air vehicle missions; three were critical tests of the team's ability to adapt to novel situations. Team performance, response time to novel events, and shared knowledge were measured. Results: Perturbation-trained teams significantly outperformed teams in the other conditions in two out of three critical test missions. Cross-training resulted in significant increases in shared teamwork knowledge and highest mean performance in one critical test. Procedural training led to the least adaptive teams. Conclusion: Perturbation training allows teams to match coordination variability during training to demands for coordination variability during posttraining performance. Although cross-training has adaptive benefits, it is suggested that process-oriented approaches, such as perturbation training, can lead to more adaptive teams. Application: Perturbation training is amenable to simulation-based training, where perturbations provide interaction experiences that teams can transfer to novel, real-world situations.

Dynamical systems theory is becoming more popular in social and developmental science. However, unfamiliarity with dynamical analysis techniques remains an obstacle for developmentalists who would like to quantitatively apply dynamics in their own research. The goal of this article is to address this issue by clearly and simply presenting several analytical techniques for the study of dynamics. We placed emphasis on the use of dynamical analysis techniques for the examination of social and developmental phenomena. We present descriptions of five techniques, which include examples of how they have been or can be used in developmental research, with reference to seminal and approachable resources when appropriate.

Objective: Recurrence-based measures of communication determinism and pattern information are described and validated using previously collected team interaction data. Background: Team coordination dynamics has revealed that "mixing" team membership can lead to flexible interaction processes, but keeping a team "intact" can lead to rigid interaction processes. We hypothesized that communication of intact teams would have greater determinism and higher pattern information compared to that of mixed teams. Method: Determinism and pattern information were measured from three-person Uninhabited Air Vehicle team communication sequences over a series of 40-minute missions. Because team members communicated using push-to-talk buttons, communication sequences were automatically generated during each mission. Results: The Composition × Mission determinism effect was significant. Intact teams' determinism increased over missions, whereas mixed teams' determinism did not change. Intact teams had significantly higher maximum pattern information than mixed teams. Conclusion: Results from these new communication analysis methods converge with content-based methods and support our hypotheses. Application: Because they are not content based, and because they are automatic and fast, these new methods may be amenable to real-time communication pattern analysis.

Objective: We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. Background: When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. Method: Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. Results: Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. Conclusion: Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. Application: Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral).