Goals & objectives team composition, the configuration of member attributes and their relationships, is a critical enabling feature of fostering effective teamwork and likely to play an important role…

This is a 3-year, $1,317,092.53 research grant awarded by the National Aeronautics and Space Administration (NASA) to Northwestern University, a private university in Evanston, Illinois. The grant is part of NASA's CREWS (Crew Recommender for Effective Work in Space) program and aims to: (1) identify the effects of team composition on team functioning in long-duration space exploration (LDSE) and the critical factors driving this effect, (2) identify patterns of this effect with different team compositions, (3) identify methods for composing teams for LDSE, (4) develop a predictive team composition model, and (5) provide recommendations for composing teams for LDSE. The research will involve developing an agent-based model, conducting virtual experiments, and validating the model in HERA and NEMO analog environments. The research products will include a predictive model of team composition in LDSE and a proposed interface to assist in staffing and managing LDSE crew and mission teams. This grant does not have a set-aside designation.

Goals & objectives team composition, the configuration of member attributes and their relationships, is a critical enabling feature of fostering effective teamwork and likely to play an important role in the effectiveness of future long-duration space exploration (ldse). Limited research on team composition in environments analogous to ldse exists, and currently how team composition can be used to optimize crew functioning and performance is unclear. Our research aims to: (1) identify the effects of team composition on team functioning in ldse and the critical factors of team composition driving this effect, (2) identify particular patterns of this effect with different team compositions, (3) identify methods for composing teams for ldse, (4) develop a predictive team composition model for use in composing teams and identify potential issues with already composed teams, and (5) provide recommendations for composing teams for ldse. To address these critical aims, we propose a 3-year, multi-method research effort, in which we: (1) develop an agent-based model of team composition for ldse based on empirical data linking key model inputs (e.g., individual difference variables, network relational factors, task characteristics) to team functioning (e.g., social integration, team processes, team cohesion, team conflict) in ldse-relevant contexts; (2) conduct virtual experiments using characteristics and relationships identified in phase i to identify the team functioning patterns that arise under different member compositions, and create a predictive model of team composition; and (3) conduct an initial validation of the model developed in phase 2 in the hera and nemo analogue environments using specific manipulations of key factors (e.g., compositions; situational characteristics). Research products critical to closing team GAP 8 will be developed including a predictive model of team composition in ldse, evidence in support of the model, and a mockup of a proposed interface to assist in the staffing and management of ldse crew and mission teams.