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Recognition skills refer to the ability of a practitioner to rapidly size up a situation and know what actions to take. We describe approaches to training recognition skills through the lens of naturalistic decision-making. Specifically, we link the design of training to key theories and constructs, including the recognition-primed decision model, which describes expert decision-making; the data-frame model of sensemaking, which describes how people make sense of a situation and act; and macrocognition, which encompasses complex cognitive activities such as problem solving, coordination, and anticipation. This chapter also describes the components of recognition skills to be trained and defines scenario-based training.
The Handbook of Augmented Reality Training Design Principles is for anyone interested in using augmented reality and other forms of simulation to design better training. It includes eleven design principles aimed at training recognition skills for combat medics, emergency department physicians, military helicopter pilots, and others who must rapidly assess a situation to determine actions. Chapters on engagement, creating scenario-based training, fidelity and realism, building mental models, and scaffolding and reflection use real-world examples and theoretical links to present approaches for incorporating augmented reality training in effective ways. The Learn, Experience, Reflect framework is offered as a guide to applying these principles to training design. This handbook is a useful resource for innovative design training that leverages the strengths of augmented reality to create an engaging and productive learning experience.
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