Macrocognition: The Science and Engineering of Sociotechnical Work Systems

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Background

The increasing complexity of work systems and changes in the nature of workplace technology over the past century have resulted in an exponential shift in the nature of work activities, from physical labor to cognitive work. Modern work systems have many characteristics that make them cognitively complex: They can be highly interactive; comprised of multiple agents and artifacts; information may be limited and distributed across space and time; task goals are frequently ill-defined, conflicting, dynamic and emergent; planning may only be possible at general levels of abstraction or require adaptive solutions; some degree of proficiency or expertise is required; the stakes are often high; and uncertainty, time-constraints and stress are seldom absent. To complicate matters further, cognition in complex work settings is typically constrained by broader professional, organizational, and institutional practice and policy. These features of cognitive work present significant challenges to scientific methodology and theory, and subsequent design of reliable interventions.


Historically, philosophers and scientists have attempted to understand the mental activities experienced during cognitive work at multiple levels of analysis using divergent methods. Some have examined cognition at an associative, contextual, functional or holistic level, relying on naturalistic methods to understand the higher mental processes as they work in harmony during goal-directed behavior. Others have embraced experimental methods and favored internal over external validity, often reducing cognition to a psychology of fundamental acts, such as short-term memory access with millisecond shifts in attention.


More recently, Macrocognition has evolved as a complementary paradigm. Macrocognitive researchers have studied the cognitive functions and processes associated with skilled, adaptive, collaborative, and resilient cognitive work in the context of the aforementioned complexities of psychotechnical and sociotechnical work systems. Typically, this research has been carried out using cognitive task analytic techniques that draw on both naturalistic and (quasi-)experimental methods. The primary goals of research in Macrocognition are to better understand cognitive adaptations to complexity, to increase our theoretical understanding of the organism-environment relations by studying the mapping between cognitive work and real-world demands, and to promote use-inspired research capable of improving system performance.


The aim of this Topic is to highlight the exciting psychological research on Macrocognition in cognitive science, cognitive ergonomics, and cognitive systems engineering. In particular, we are interested in soliciting papers from those individuals interested in: (i) Cognitive adaptations to complexity; (ii) Expertise; (iii) Accelerated learning; (iv) Proficiency scaling; (v) Mentoring, training, and professional development; (vi) Improving work system performance; (vii) Issues for the methodology of cognitive task analysis and the rigorous handling of qualitative data; (viii) Developing measures and metrics for analysis at the work systems level; (ix) Developing performance support technology; (x) Human-technology interaction; (xi) Human-centred design; or (xii) Developing policy and funding priorities. In addition, we are interested in research that addresses multiple level of analysis, particularly those relating macrocognition to microcognition or higher levels (e.g., social networks) of system performance.

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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