Mental Model Convergence Cycles: Cognitive and Social Network Effects
Abstract
Whether service members are working in recognizance, exploration, maintenance, construction, or elsewhere in the field, they may be tasked co work as a team. In general, teams are thought to produce better quality outcomes than individuals working alone. Yet, given the inconsistency of teamwork effectiveness found by researchers for at least the last 35 years (Steiner, 1972; Mathieu et al., 2008), there is still much to be learned about why teams achieve, or fail to achieve, more than the sum of their parts. A burgeoning area of investigation in explaining why team effectiveness unfolds as it does is the area of cognitive networks. In particular, researchers argue that team mental models are cognitive repositories containing abstract representations relevant to task work and teamwork activities and, while held at the individual level, when content is shared across the members then the team may have more synergistic interactions and make better knowledge-based team decisions (Cooke et al., 2000: Mathieu et al, 2000: Mohammed & Dumville, 200 I). The investigation of team mental models has shown that team mental model sharedness (Burke et al., 2006: Rico et al., 2008) and team mental model accuracy (Edwards et al., 2006: Lim & Kline, 2006) have been key in explaining outcomes achieved, and the existence of both characteristics in combination is salient for team effectiveness (Marks et al., 2000; Mathieu et al., 2005). The process of bringing about team mental model sharedness and team mental model accuracy is called mental model convergence (McComb, 2007) and it is fueled by team communication (Kennedy & McComb, 2010) where members gather and integrate information into mental models. To uncover the dynamics in the way team mental models converge to be shared and/or accurate over time, the proposed research will investigate social network effects on the relationship between team communication and team mental models. The connection between social network effects and cognitive networks is motivated by social influence theory that has a history of studying the way people affect changes in others (Friedkin, 2006). As members communicate within their social network, they produce information and influence that prompt changes in cognition. That is the information quantity and quality is a result of the pattern of network interactions among team members (e.g. Poole, 1999) and the social influence is due to the presence or weight given to the speaker (Short et al., 1976). The social network effects will determine the opportunity for change and the magnitude of the resulting change in team mental model sharedness and accuracy. The proposed research will use computational modeling to simulate team communication and mental model dynamics by members working within a multi-team system environment (MTS). The computational model will be validated using records from teams in the extreme context of NASA s HERA analog. This data is sought because it provides a complete dialog record of teamwork by members in a MTS. For NASA, this research will reveal the threat to effectiveness of team mental model convergence over time (NASA Team Gap I), and potential countermeasures such as training and when those countermeasures are most useful in overcoming the threat (NASA Team Gap 3, Gap 5). In addition, by studying social and cognitive network effects this research will show how they combine to create synergistic benefits (NASA Team Gap 8). The predictive model uses process measures (NASA need MPTASK-01) to help identify potential sources of ineffectiveness over time (NASA need MPT ASK-04). Thus, this research is poised to help spaceflight crews and a number of other teams.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 14, 2019
- Source ID
- W911NF1810362
Entities
People
- Deanna Kennedy
Organizations
- Army Contracting Command
- United States Army
- University of Washington