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.

This book constitutes the proceedings of the 14th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2018, held as part of the 20th International Conference, HCI International 2018, which took place in Las Vegas, Nevada, in July 2018. The total of 1171 papers and 160 posters included in the 30 HCII 2018 proceedings volumes was carefully reviewed and selected from 4346 submissions. EPCE 2018 includes a total of 57 papers; they were organized in topical sections named: mental workload and human error; situation awareness, training and team working; psychophysiological measures and assessment; interaction, cognition and emotion; and cognition in aviation and space.

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.

Macrocognition Metrics and Scenarios: Design and Evaluation for Real-World Teams translates advances by scientific leaders in the relatively new area of macrocognition into a format that will support immediate use by members of the software testing and evaluation community for large-scale systems as well as trainers of real-world teams. Macrocognition is defined as how activity in real-world teams is adapted to the complex demands of a setting with high consequences for failure. The primary distinction between macrocognition and prior research is that the primary unit for measurement is a real-world team coordinating their activity, rather than individuals processing information, the predominant model for cognition for decades. This book provides an overview of the theoretical foundations of macrocognition, describes a set of exciting new macrocognitive metrics, and provides guidance on using the metrics in the context of different approaches to evaluation and measurement of real-world teams.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computing methods, new applications, new philosophies . . . , new challenges. Much of the development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The potentially devastating effect of an operator making the wrong decision in the control of a highly automated system or process is well known. However as even more large-scale automated systems become likely, for example automated highways for cars, it is increasingly important to be able to assess the safety of these mixed or joint systems. Carlo Cacciabue's monograph on the modelling and simulation of these mixed processes of technological systems and human operators is extremely timely. The monograph provides an up-to-date and systematic presentation of the basic concepts and tools needed. This comprehensive coverage of the subject also includes a review of the last twenty years of research effort in the field.

This book presents the latest work in the area of naturalistic decision making (NDM) and its extension into the area of macrocognition. It contains 18 chapters relating research centered on the study of expertise in naturalistic settings, written by international experts in NDM and cognitive systems engineering. The objective of the book is to present the reader with exciting new developments in this field of research, which is characterized by its application-oriented focus. The work addresses only real-world problems and issues. For instance, how do multi-national teams collaborate effectively? How can surgeons best be supported by technology? How do detectives make sense of complex criminal cases? In all instances the studies have been carried out on experts within their respective domains. The traditional field of NDM is extended in this work by focusing on macrocognitive functions other than decision making, namely sense-making, coordination and planning. This has broadened the scope of the field. The book also contains a theoretical discussion of the macro-micro distinction. Naturalistic Decision Making and Macrocognition will be relevant to graduate students, researchers and professionals (including professionals and researchers in business, industry and government) who are interested in decision making, expertise, training methods and system design. The material may be used in two ways: theoretically, to advance understanding of the field of naturalistic decision making; and practically, to gain insight into how experts in various domains solve particular problems, understand and deal with issues and collaborate with others.

The Oxford Handbook of Expertise provides a comprehensive picture of the field of Expertise Studies. It offers both traditional and contemporary perspectives, and importantly, a multidiscipline-multimethod view of the science and engineering research on expertise.