In the modern work environment, performance is rarely a product of standardized actions, but instead is contingent on a series of judgments and decisions. Decision making underlies the bulk of everyday work behaviors, ranging from simple (e.g., deciding which tasks to prioritize) to complex (e.g., deciding which actions to take following an emergency). It is therefore critical to understand how decision-making processes operate and how such processes can be improved through training and development interventions. Indeed, there are multiple long-standing streams of research seeking to do just that, most falling under the formalempiricist or rationalist paradigms (Cohen, 1993). Both approaches suggest that decision makers build and test models when selecting between concurrently available options (Cohen, 1993), with the rationalist approach emphasizing the role of human error in the construction and use of such models (Ross, Shafer, & Klein, 2006). More recently, however, the naturalistic decision making (NDM) framework has been put forward as a means of explaining how decisions are made in real-world, complex environments (Klein et al., 1993). Specifically, while other decision-making paradigms are based on controlled lab experiments, proponents of the NDM approach argue that the inherent complexity and constraints of most real-world contexts do not allow for the careful construction and con - sideration of models of choice. Instead, decision makers rely on previous

experience to interpret the situation at hand and select an appropriate course of action (Klein et al., 1993).