Subsequent refinements have incorporated temporal components, nonlinear dynamical extensions and quantitative metrics. The generation of heterologous multi-team models and linkage of them with team member speech frequencies has allowed comparisons across teams, training sessions and levels of experience (Stevens, R. H., Galloway, T., Wang, P. & Berka, C., 2012; Stevens, R.H., Gorman, J.C., Amazeen, P., Likens, A. & Galloway, T., 2013; Stevens, R. H. & Galloway, T., 2014; Likens, A. D., Amazeen, P. G.; Stevens, R., Galloway, T., & Gorman, J. C., 2014). The models developed are reliable, sensitive and valid indicators of the changing neurodynamics of teams around which standardized quantitative models can begin to be developed. The technology is intended for documenting how rapidly teams are progressing towards proficiency and expertise and for understanding why some teams function better than others.
Like most forms of social coordination, teamwork is complicated, complex, and noisy. It is complicated as teams generally form around tasks that are too difficult for individuals to accomplish alone and require a diversity of experience and expertise. It is complex in the circular causality and feedback among multiple systems and sub-systems involved. For instance, neurophysiological events give rise to speech and other forms of inter-person communications which in turn affect subsequent speech and behavior. It is also complex in the sense that behaviors emerge in teams that often could not be predicted beforehand; i.e., the whole can be greater than the sum of its parts. Finally, teams are noisy in the sense that as the team develops consensus, many actions may occur that are peripheral to the immediate task.
These properties of being complicated, complex, and noisy pose challenges for evaluating teams, and at some point, seemingly simple questions like “How is this team doing?” become difficult to answer, particularly if the goal is to capture quantitative measures of team improvement over time. Part of the challenge is that unlike the performance evaluations of individuals, there are few measures and models for rapidly comparing across teams. This is particularly true with teams of diverse experience, who are performing real-world tasks where errors may be infrequent and do not directly correspond to failure (Schmidt, Keeton, Slack, Leveton, & Shea, 2009).
We have proposed that neurodynamics may provide a platform for developing quantitative models of team organization and perhaps performance (Stevens, 2012; Stevens, Galloway, Wang, & Berka, 2012). It is not surprising that neurophysiologic activities are the underpinnings of the social coordination dynamics described above, yet it is only recently that their evolving dynamics in real-world teamwork settings have begun to be modeled (Dodel et al., 2011; Dumas, Nadal, Soussignan, Martinerie & Garnero, 2010; Stephens, Silbert, & Hasson, 2010; Stevens, Galloway, Berka, & Sprang, 2009).
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"Spirit of Innovation Award" Received by Dr. Ron StevensLeland S. Kollmorgen Spirit of Innovation Award was instituted in 2007 by the HFES Augmented Cognition Technical Group in honor of Leland S. Kollmorgen, Rear Admiral, U.S. Navy (Ret.). The award recognizes exceptional scientists and engineers who have made substantial and innovative contributions to the field of Augmented Cognition. The recipient is someone whose extensive endeavors have pushed the frontiers of discovery, innovation, and design in Augmented Cognition transcending the boundaries of human-systems computing and is a true inspiration to the HSI field. The Leland S. Kollmorgen Spirit of Innovation Award recipient is judged not only on accomplishments in the last year, but also on a career history of efforts contributing to the advancement of the Augmented Cognition field. Other criteria for selection include: resourcefulness and dedication in promoting and accomplishing innovative human-systems computing technologies, demonstrated leadership in forming and promoting teamwork among the various disciplines represented within the Augmented Cognition field, demonstrated professionalism and integrity, and the embodiment of the spirit of innovation and collaboration. |
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Recent PublicationsStevens, R. H., Galloway, T., Lamb, J., Steed, R. & Lamb, C. (2017). Linking Team Neurodynamic Organizations with Observational Ratings of Team Performance. Innovative Assessment of Collaboration, pp 315-330. Abstract: We have investigated the correlations between the levels of team resilience as determined by expert raters and the degree of the teams' neurodynamic organization determined by electroencephalography (EEG). Neurophysiologic models were created from submarine navigation teams that captured their dynamic responses to changing task environments during required simulation training. The teams were simultaneously rated for resilience by two expert observers using a team process rubric developed and adopted by the U.S. Navy. Symbolic neurodynamic representations of the power levels in the 1-40 Hz EEG frequency bands were created each second from each crew member. These symbols captured the EEG power of each team member in the context of the other team members and also in the context of the task. Quantitative estimates of the changes in the symbol distributions over time were constructed by a moving window of Shannon entropy. Periods of decreased entropy were observed when the distribution of symbols in this window became smaller, for example, when there were prolonged and restricted relationships between the EEG power levels among the crew members, that is, less neurodynamic flexibility. Team resilience was correlated with the neurodynamic entropy levels. The correlation sign, however, depended on the training segment with negative correlations during the presimulation briefing and positive correlations in the scenario training segment. These studies indicate that neurodynamic representations of teams can be generated that bridge the microscales of EEG measurement with macroscales of behavioral ratings. From a training perspective, the results suggest that neurodynamic rigidity (i.e., everybody on the same page) might be beneficial while teams are preparing for the simulation, but during the scenario, increased neurodynamic flexibility contributes more to team resilience. |
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