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Dynamical Modeling of Communications for Assessment and Enhancement of Team Performance

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-09-C-0138
Agency Tracking Number: N074-023-0371
Amount: $491,718.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N07-T023
Solicitation Number: N/A
Timeline
Solicitation Year: 2007
Award Year: 2009
Award Start Date (Proposal Award Date): 2008-12-15
Award End Date (Contract End Date): 2010-05-15
Small Business Information
5810 S. SOSSAMAN RD. SUITE 108
MESA, AZ 85212
United States
DUNS: 786521273
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Steven Shope
 President
 (480) 988-1000
 sshope@cerici.org
Business Contact
 Jennifer Winner
Title: Administrative Director
Phone: (480) 988-1000
Email: jwinner@cerici.org
Research Institution
 ARIZONA STATE UNIV.
 Polemnia G Amazeen
 
Department of Psychology P.O. Box 871104
Tempe, AZ 85287
United States

 (480) 727-7075
 Nonprofit College or University
Abstract

Defense transformation and network-centric operations have created a need for highly-responsive, networked teams of individuals. Individuals on those teams each contribute a unique but complementary sets of skills and knowledge (and multicultural backgrounds), but a major challenge in forming teams is getting those individuals to function as an efficient, integrated unit. There exists a challenge to develop a toolset for monitoring team behavior in real-time, detecting time-phased anomalies, and intervening to increase team effectiveness. One inroad to addressing this question is to use a ubiquitous byproduct of teams: communications. In Phase I, we showed the feasibility of discriminating between normal team activity and anomalous team activity using dynamical modeling of team communications. Specifically, we applied dynamical modeling to real-time communication flow data (i.e., who is talking to whom, when, and for how long) for the purpose of assessing, in real-time, team synchronization and shared understanding. In Phase II, we propose to continue to refine this approach, validate the dynamical model results, and determine the effectiveness of the method. In Phase II we will develop and advanced prototype of the tool capable of being implemented it in dynamic team settings.

* Information listed above is at the time of submission. *

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