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In order for cognitive systems engineering (CSE) to deliver the benefits of recent theoretical advances in actual systems being developed, the insights of CSE must be transformed into pragmatic engineering practices. The CSE engineering practices described in this article (using the applied cognitive systems engineering methodology as an exemplar) are typical of just such an engineering adaptation of revolutionary science and represent engineering practices that are dedicated to building effective systems. CSE research insights can have a significant impact on their corresponding systems engineering (SE) practices by expanding SE's concept of a system from just the technology components to a joint cognitive system (Hollnagel & Woods, 2005) and expanding the associated SE practices appropriately. This article uses the Department of Defense system life cycle and the SE V-model (Forsberg & Mooz, 1992) as SE process exemplars to illustrate how CSE engineering practices can be integrated into the SE process. Specifically, we propose four key integration points where CSE can contribute significantly to the SE process: concept refinement, software development, testing, and postsystem development (i.e., operations support, training, and maintenance). Our approach shows that the practice of CSE does not compete with SE but, instead, augments current SE practices to ensure that the technology components are engineered with the users' cognitive needs in mind.

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Cognitive Systems Engineering (CSE) techniques are widely used for the description and analysis of the sources of cognitive complexity and explicating the basis of expertise within a work domain. However, the results of the CSE techniques often focus on work analysis and are only weakly coupled to the design of decision support systems that are built based on those analyses. In fact, some within the CSE community have suggested that such a design epiphany occurs as if by magic. If CSE is to be treated as an engineering discipline, it cannot rely on magic to create systems. The approach described in this paper assumes that an explicit relationship between system design and supported cognitive work is fundamental to the design's effectiveness. The goal is a pragmatic, effective engineering process that explicitly designs systems according to relationships between cognitive work requirements and decision support concepts.