Astronaut teams must operate in high-risk environments, where emergencies arise and decisions, or choices among alternatives, carry weighty consequences such as mission success costing billions of dollars or even are a matter of life and death (Landon et ah, 2018). In other high-reliability environments (i.e., places where decisions are costly), such as Antarctica, teammates have expressed the utmost importance of ‘mutual decision-making’ so that members are in agreement before enacting their shared choices (Atlis, Leon, Sandal, & Infante, 2004). These extreme teams express the importance of team cognition as the basis of decisions (Atlis et ah, 2004). Team cognition is the multilevel study of team-learning processes and knowledge outcomes (Fiore et ah, 2010; Kozlowski & Chao, 2012). The study of team cognition was born from shared mental models (Cannon-Bowers, Tannenbaum, Salas, & Volpe, 1995), although the field has expanded to include transactive memory systems and various learning-related constructs that support team performance (Kozlowski & Chao, 2012; Salas et ah. 2009).

Team Learning

Team learning includes knowledge building, macrocognition, and team reflexivity. Individual knowledge building occurs when a team member learns information about a problem or domain relevant to their work. Behavioral processes like collaboration and communication allow individual knowledge building to translate to team knowledge building, which is one reason that team learning is considered an outcome to team adaptation (Burke et ah, 2006; Kozlowski & Chao, 2012). Macrocognition refers to the process of building team knowledge in support of problem-solving outcomes

(see Fiore et al., 2010). Team reflexivity, an essential component of team learning, is the ‘extent to which teams collectively reflect upon and adapt their working methods and functioning’ (Schippers, West, & Dawson, 2015, p. 769), and is important for teams to prepare for future cognitive tasks (Schippers, Edmondson, & West, 2014). Teams that are high on reflexivity are able to reflect upon errors and change their future behavior to prevent the same errors from recurring, thereby reducing risk in future operations. Reflexivity allows teams the cognitive space for learning and may promote the self-awareness necessary for them to recognize their work demands and understand the team’s capacity to respond to such demands (Schippers, West, & Dawson, 2015). While team learning can be conceptualized as an outcome, according to the IMOI model, these outcomes can be an input and part of the team process for predicting future outcomes (Ilgen, Hollenbeck, Johnson, & Jundt, 2005). For instance, NASA astronaut teams must build their individual knowledge, engage in macrocognition, and be high on team reflexivity to effectively problem-solve during missions.

Team Learning in Decision-Making

One example of a decision-making model for extreme environments is the SAFE-T model, which urges trainees to focus on situational awareness, SA, plan formulation, F, plan execution, E, and team learning, T (Power, 2018). Exploratory research supports this model, and found that high-performing teams on a decision-making task spent more time sharing information and a shorter amount of time deciding on the plan (Uitdewilligen & Waller, 2018). While the SAFE-T model emphasizes team learning, evidence shows that team learning goal orientation does not predict decision-making performance, rather, team performance proves goal orientation (i.e., focus on competition and performance) was seen to excel at decision-making due to higher levels of team planning (Uitdewilligen & Waller, 2018). However, we urge decision-making teams, such as NASA astronaut flight teams, to continuously learn from their experiences, so that they will build their team knowledge outcomes, and thus future decisions will be quicker and easier to make.

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