Presentation
Measuring Multidimensional Team Adaptation
DescriptionRecognizing their adaptive nature, recent research has shifted toward viewing teams as dynamical systems, in which team states emerge through ongoing interactions rather than being predefined at the individual level (Gorman et al., 2010; Gorman et al., 2017; Grimm et al., 2023; Ramos-Villagrasa et al., 2017). Most studies, however, focus on single measurement modalities, limiting insights into system-wide adaptation. This study addresses this gap by using Collective Systems Adaptation (CSA) analysis, a multivariate time-series method designed to detect synchronized changes across multiple dimensions of team interaction. We applied CSA to three complementary measures of team interaction: Communication Flow (information distribution), Geospatial Coordination (spatial organization), and Workload Synchrony (pupillometry-based measure of cognitive strain). These dimensions were integrated to examine how adaptive processes emerge across multiple measures of team interaction. Teams were observed during high-fidelity simulated combat missions, and adaptation events identified through CSA were used to predict combat effectiveness. Our findings show that multidimensional measures of adaptation accounted for 11% to 55% of the variability in performance outcomes, supporting the value of multi-modal analysis for understanding team dynamics. These results demonstrate the potential for real-time assessment of team adaptation, with applications for training, monitoring, and decision support in complex domains.
Event Type
Lecture
TimeThursday, October 16th4:30pm - 4:50pm CDT
LocationGrand E/F
Human Performance Modeling