Distributed Team Cognition: Integration, Evolution, and Insight
Michael D. McNeese
Philosophical Quest of the Handbook...................................................................3
Direction and Structure.........................................................................................5
What Is the Focus of the Handbook?....................................................................6
What Do We Mean by Distributed Cognition?.....................................................7
What Are the Underlying Needs for a Handbook?...............................................8
Examples of What We Mean by Distributed Team Cognition.......................11
Developmental History: A Personal Perspective.....................................................12
With Design in Mind...........................................................................................13
Imprints and Opportunity in Dayton and Beyond...............................................16
An Emergent Research Pathway....................................................................21
In 2001, Michael D. McNeese, Eduardo Salas, and Mica R. Endsley published a book entitled New Trends in Cooperative Activities: System Dynamics in Complex Environments. That book was designed to capture state-of-the-art research involving team cognition as it occurred in dynamic environments. Nineteen years have passed since publication of that volume and a lot of things in the world have changed dramatically. The passage of time and the presence of disruptions provides new Zeitgeists for understanding how teamwork and team cognition have evolved given:
- • consideration of theoretical frameworks,
- • derivation and reification of cognitive science concepts/cognitive processes,
- • methodological diversification and innovation,
- • progression of knowledge capture tools and measurement of different phenomena,
- • socio-cultural embodiment in various fields of practice, and
- • the rapid design/development of information, communication, and cognitive technologies.
These evolutionary imprints jointly contribute to what is meant by distributed team cognition. As we embark on this current journey 19 years later to collectively review and comprehend distributed team cognition, it is imperative to be mindful of the history and roots from whence it came. Therein, while the authors of the chapters within necessarily point toward the contemporary mindset they also flow from the foundation and work of many scientists who came before them. History is important and should be recognized and not forgotten. At the same time, it is the pull of the future that challenges us to make progress within this exciting area of science and research.
The Handbook of Distributed Team Cognition provides a refreshing look at what has transpired within team research as informed through cognitive activity and technological advancement, as distributed across the digital global society. Our intent is to enlighten the reader with the specifics of evolutionary thought that demonstrate how team cognition has been transformational in its impact on human beings. The purpose of this first chapter is to look at some of the philosophical underpinnings that led to producing this handbook. Philosophical underpinnings necessarily are generated from the worldviews that an author believes in, the history and development of work, and how important disruptions cause individuals and society to change how they interpret and defend reality. To demonstrate this idea, I will provide a personal-developmental look at how my own passions and experience eventually evolved into research within the distributed team cognition genre. In addition to philosophical underpinnings, this chapter builds a foundational footing and flooring of the handbook in terms of what to expect. We provide rationale for why this undertaking was initiated and needed. It is our hope that the handbook induces new' thinking and inspiration to further cognitive science while reviewing cogent research in terms of theory, methods, measurements, and applications.
The focus of research and development related to distributed team cognition derives from the attention and keen awareness that any given researcher takes longitudinally across time, thought, and place. And this may place each of us in a distinct realm of meaning for a given topic, i.e., our understanding of a phenomena, process, or technology but based on scientific evidence, not opinion. The color of meaning derived absolutely depends on many influences, disruptions, adaptation and assimilation of new directions with supportive research results, practical considerations, and the value accorded to many biases, streams of thought, beliefs, and experiences that together formulate what is referred to as knowledge. While knowledge exists at the general, principled level across many studies and replications, it exists at specific and personal levels as well. Specific knowledge helps human beings (and computational) agents reason about the world around them (their sense surround) in ways that coincide with their constructed interpretation. Personal knowledge is construed and constructed according to the contexts we experience and derive—over and over again. It is specific and subjective but also can be generalized to the point of objective truth in ways that make sense to many, and again is distilled across time and culture. This distillation can change the outcome of the construction over time so what was true 20 years ago may not hold today. Specific and personal knowledge is therefore malleable in formation and changes based on what you already know (and resides in the memory that contains it). Having said this, knowledge is sharable across cultures, groups, and teams accordingly. In fact, many of our concepts for this handbook derive from basic level ideas surrounding shared knowledge among agents (e.g., common ground, team mental model, team schema, common operational picture, jointly constructed memories, and so on). What agents do with the knowledge they have or share dovetails into action, achievement, and performance.
Knowledge as design (Perkins, 1986) takes what we know (individual and team level) to the state of what may be accomplished (activity and performance) through what can be produced (designs), and in turn how well a design may be leveraged by actors in a situated context (use). This premise is directly coupled to ideas resonate within the research areas of distributed cognition (Hollan, Hutchins, & Kirsh, 2000), team cognition (McNeese, Salas, & Endsley, 2001; Salas, Fiore, & Letsky, 2013), and interactive team cognition (Cooke, Gorman, Myers, & Duran, 2013). Ideas about distributed cognition and team cognition appear throughout this handbook in the form of what we know, how we generate designs for use, and how we act in a wide variety of applications and fields of practice. Distributed cognition involves the individual as related to the broader sense-surround wherein an individual is embedded within a given environment. That often includes the necessity that workers leverage individual work with others (i.e. working together) to achieve a desired outcome (goal) where complex and complicated interdependencies are operative. And the outcome is resonant with using cognitive processes to assess situations, make decisions, or solve problems. This larger world of interaction frequently revolves around the dynamics of teamwork and reveals collective, cultural, and socio-technical values if it rings true (i.e., reflects universality).
Philosophical Quest of the Handbook
In some ways, a handbook could be construed as generating a five-dimensional maze where time = theories/perspective, width = approach/methods, length = applications, and height = technologies. If you can imagine a 3-D block that changes dimensions through time you can induct the construct of a matrix that emerges according to given research foci. But to travel through the matrix one might choose any single point within the block to represents an instantiation point. If one imagines the center the block as a place to start (with a given theory, method, application, and technology utilized), as you move in any direction you change one of these dimensions and therein alter the research focus taken. As one moves across time with differing dimensions of these constructs being utilized for their own research niche, the fifth dimension—from instantiation-to-abstraction—can be hypothesized for a researcher. One might look at this for a specific researcher but in the concourse of a handbook this matrix represents the population of many worldviews that have been derived across set timelines, hence an abstraction of abstractions. Obviously, this only represents a select subset and not all possible viewpoints. Therein, the fifth dimension indicates an abstraction or generalization emanating from a given point within the overall matrix to a collectivist derivation of topics that are culturally current and relevant to researchers who share interests in distributed team cognition.
Stated another way the matrix shows the evolution of science across time from a concrete point to levels of abstraction. That is, at any given point a reader is surrounded by contiguous spectra that are highly related to a researcher’s specific interests—in this case distributed team cognition concepts. The further out from a given point—in all dimensions—suggests a greater distance or abstraction from the specifics that a given researcher has taken and is engaged in. As one takes in spectra positions there may be segues for generalization or even general knowledge can be transmitted across time and demonstrate the qualities of invariance or veridicality. One may enter the matrix through different portals that transport one to different sectors representative of a select spectra of research. Sectors can be contiguous such that passages interconnect sectors to traverse complex interdisciplinary research space.
Therein, the handbook taken as a whole does represent a complex interdisciplinary research space and contains all the elements above with the intent to inform the reader at the general knowledge level as well as the specific research spectra level. Hopefully it provides the reader with a thoughtful circulation of ideas, conceptual trajectories, and boundary constraints evident in distributed team cognition. The 5-D matrix also functions as a mirror in that it allows a reader to assimilate the content they read with what they already know for themselves with respect to a given niche (the process associated with expanding their own internal concept map for a research area or topic). This affords generative learning, reflection, and metacognition as one compares, processes, and integrates differing points of view within the handbook with one’s own centric point of view (i.e., beliefs) to determine the degree of fit. Reflection is certainly dependent upon each of our backgrounds, abilities, training, experiences, culture, and biases and therein anyone’s assimilation of the Handbook of Distributed Team Cognition can be different but also contain common ground, just as our individualistic cognition is different, and yet at some degree of abstraction is the same. (We enter the handbook via portals closest to our way of thinking most likely.)
Specific openings represent certain intellectual spaces that are relevant for a given aspect of the handbook but do not necessarily generalize and therein do not represent the holistic overall intellectual space. Because each of us represent a unique set of individual differences—the ways we think about distributed team cognition, the manner by which we go about conducting research, and the concepts we produce for technological designs to support distributed cognitive activities can necessarily be different from other researchers. At the same time as research scientists, professional educators, engineers and designers, and futurists we share a common ground of knowledge that sets foundations that are meaningful in the broader sense. We hope to capture multiple perspectives from many viewpoints as well as formulate a contemporary common ground of knowledge for the reader, within the books that comprise the handbook. For you the reader, the handbook’s purpose is to provide multiple, useful examples of research that generate principles, processes, and practical applications within the distributed team cognition research space.
Our own guidance in understanding this complex interdisciplinary research space came from advisors, mentors, and colleagues who watched over us and pointed us in the right direction. It is our hope that the authors presented in this handbook add to your level of knowledge and therein provide additional guidance to expand understanding. What we thought we knew many years ago certainly has evolved over time, being shaped and refined through these influences, relationships, consequences, and the truth of our lives. As one reads through the chapters resident throughout the three volumes that comprise the handbook, the prose traces through the specific heritage of learning, perspective, and practice for a set of authors. Because the scope of the handbook addresses and drills down on interdisciplinary research topics, the academic disciplines represented span across cognitive science, systems engineering, psychology, computer science, information-communication technology, humancomputer interaction, anthropology, human factors, and design, in addition to other cogent disciplines as needed.
As we contemplated the focus and direction for the handbook one of the central principles considered was to supply multiple perspectives and yet show precipitous integration and even glances of invariance within a topic at hand. It is our hope that the multiple perspectives provided herein can prosper the reader, activate the curious minded, and at the same time cover a large expanse of intellectual space within the distributed team cognition genre while making sense of it all. As you read through the handbook it is akin to a labyrinth where passages connect to synthesize integrative thoughts that ring true.
Direction and Structure
The previous section provided background, motivation, inspiration, and some of the historical layers underlying the development of the handbook. The next few sections focus more on foundations, content, rationale, and the emphasis taken in the overall composition. While information in these next sections may overlap it is intended to show the reader the why, what, who, and how of distributed team cognition. To begin we have organized the overall handbook to consist of three individual volumes. One can obtain all of the books or just the ones that generate interest. One will find some topics to be more distributed across the three volumes than others (after all it is distributed cognition!). We have structured the three volumes in the Handbook of Distributed Team Cognition topically as follows: Volume 1, Foundations and Theoretical Perspectives; Volume 2, Contemporary Research— Studies, Methods, Models, and Measures; and Volume 3, Fields of Practice and Applied Solutions. These three volumes span relevant, current topics in the information continuum within distributed team cognition. At the beginning of each volume a primer is provided which outlines the concept of the volume and provides a brief synopsis of each chapter.
What Is the Focus of the Handbook?
The primary direction undertaken within this handbook focuses on the interdisciplinary study of distributed team cognition as defined by the interrelationships and appropriate action potentials inherent in information, technology, people, work, and context. The handbook approaches and defines current worldviews of distributed cognition as they are related to what cognition is, what cognition does, and how it is distributed and carried out as part of teamwork. As such the definition of distributed cognition is cognitive activity (individual, teams, computational agents) intended to address or overcome complex challenges, problems, or constraints that are distributed across and influenced by a specific context or environment. Distributed team cognition is used in many different application domains, but one example of this would be the way police work to understand a crime, the crime scene, the perpetrator, how the analytics of the situation emerges especially across different venues and with different timelines, and how distributed cognition and specific information and communication technologies play out and are used in conjunction with distributed cognition explanations. This is no more evident than with the real-world example of the Boston Marathon bombings which took place in 2013 whereupon multiple teams worked together to gain an understanding of a continuously emergent situation that spanned across multiple contexts and required the use of a variety of technologies (e.g., face recognition technology) to make sense of the analytics underlying decision making, problem solving, context, and judgment.
One of the strong components within the handbook is the role of technology as a disruptive agent that transforms team cognition in terms of definition, process, and application. Technology has been distributed across our lives in so many ways and is partly responsible for the revolution in the digital global economy. Its use makes our lives easier and more complicated all at the same time. We may take it for granted and not realize when or how it has been important to address many real-world problems encountered at the societal and individual level. Technology does not exist in a vacuum but has been innovated as a means to an end. It can and has worked for both good and evil. Unfortunately, all too often it has not been designed with much consideration for human needs or team capabilities but simply evolved just because it was possible to do so. While this may be good for purposes of invention, the human use of technologies has historically not been a prime consideration although this has changed in the last half century owing to the practice of human factors engineering (Meister, 1999; Wickens, Hollands, Banbury, & Parasuraman, 2013).
This handbook provides the landscape for how technology has been positively influenced by information, people, and context in many fascinating and productive ways. In particular, it examines how (1) teams have put technology to use with focus on distributed applications and (2) how technology has amplified the capabilities for quick and efficient distributed information within problem solving and decision making. It focuses on cognitive processes that teams use as they are distributed across contexts, tools, and apps, and recognizes the varieties of information representation that are now possible to enhance problem comprehension. Taken together the handbook weaves a tapestry of interdisciplinary research which we refer to as distributed team cognition to capture these notions and more. While team cognition and distributed cognition have their own distinct entities (our research groups have published within each genre respectively) current research is now reflective of the integrative coupling of these areas (more on that later).
What Do We Mean by Distributed Cognition?
Distributed cognition is relative to human, social, cultural, and organizational factors that dynamically emerge within the context and are often contingent upon availability of data, information, and knowledge resident within a technological milieu. Cognition is distributed across many planes and subject to dynamic fluctuation given constraints that are active at any given moment. Distributed cognition is not about cognition only viewed as resident within the brain but takes the broader view that cognition is embodied (see Varela, Thompson, & Rosch, 1991; Wilson, 2002), represented within the situated context w'here it is operative, and is entwined with activity. While there are many other definitions cogent to distributed cognition (Hutchins, 1995; Zhang & Norman, 1994) the definition stated in the previous section emphasizes the mutual interplay among cognition, culture, and artifacts with the understanding that activity develops through dynamic interaction in the midst of multiple constraints. This particular definition is similar to ideas put forth under the auspices of ecological psychology, situated cognition, enactive cognition, and situated learning. These are the footers that formulate my own worldview and in turn have led to the motivation to produce a handbook that has broad precepts. This includes giving credence to other worldview's as well. Inherently, the philosophy and viewpoints of any chapter herein may vary according to influences and history of the individuals composing the chapter. The intention is to capture diverse viewpoints rather than promulgate one specific framew'ork. While this is a goal one can also derive levels of integration across the chapters that are relevant for certain concepts, principles, processes, methods, measures, application, and practice even though different contexts that are utilized reflect unique histories and findings.
Many w'orldviews (i.e. philosophies, conceptualization, and integrated system of beliefs) have been used to derive distinct connotations for questions such as (1) What is cognition? (2) Where does cognition exist? (3) What does cognition produce? (4) How' is cognition constructed? (5) How is cognition carried out in the real wwld and distributed as part of teamwork (distributed team cognition)? While the first four meta-level questions are extremely important and actually presuppose question five, it is question five that really generates the foundation and formulates the focus of this handbook. Indeed our own wwk suggests that cognition is strongly coupled with cooperative activities (team cognition, McNeese et al., 2001; Salas, Cooke, & Rosen, 2008), distributed and coordinated across multiple vantage points according to need (distributed cognition, Hollan et al., 2000), situated within specific contexts (situated cognition, Brown, Collins, & Duguid, 1989), built through continuous experience as shaped by individuality, history, learning, and culture (Lave & Wenger, 1991), predicated on the availability of data, information, and knowledge (information sciences, Zins, 2007), and is extended or augmented through the use of technology (information and communication technologies, mobile devices, ubiquitous computing, computational agents, the worldwide web, social networks, etc.).
Yet there are few volumes that provide multiple perspectives across various worldviews in an attempt to understand the complex interrelationships that are distributed across cognition, information, technology, people, work, and context. The handbook incorporates trends, topics, and trajectories that span across this broad panorama and includes topics from information and cognitive sciences, industrial-organizational psychology, computer science, computer-supported cooperative work, humancomputer interaction, learning science and gaming, and other cogent viewpoints.
The topics that resonate in the handbook provide an interdisciplinary nexus that articulates contemporary directions in distributed team cognition as relevant for the society we live in. The handbook examines and reviews unique worldviews of cognition (the why), presents unique state-of-the-art theories, research, and technological innovations that inform distributed cognition (the what), highlights innovative methodologies in use (the how), and provides examples of applications and cases within specific fields of practice (the use) as understood by recognized world-class experts (the who). Together the topics—as reflected within a given chapter—formulate collective frame of minds that represents a new synthesis of cognition.
What Are the Underlying Needs for a Handbook?
The primary emphasis of the first editor’s scholarship over the last two decades has examined teams, work, and cognition through particular research lenses: situated cognition (Brown et al., 1989; Young & McNeese, 1995), team cognition (Salas, Fiore, & Letsky, 2013; Mohammed, Hamilton, Tesler, Mancuso, & McNeese, 2015), situation awareness (Endsley, 1995; McNeese & Perusich, 2000), and ecological basis of cognition (Hutchins, 1995; McNeese & Forster, 2017). The research underlying these perspectives has advanced theoretical positions that emphasize the roles that social factors, information sciences, experience, and technology have in the development and support of teamwork such as problem solving (Young & McNeese, 1995), decision making (McNeese, Mancuso, McNeese, Endsley, & Forster, 2014), or the transfer of knowledge (McNeese, 2000). Historically, this work is traceable to the intellectual pursuits of John Dewey (1938) and the interdisciplinary problem-based learning theories of John Bransford (Bransford, Brown, & Cocking, 2000).
A strong part of advancing the socio-cognitive and socio-technical aspects of teamwork necessarily includes related focus on integrative methodologies that provide ecological and concomitant interpretive powers (e.g., see AKADAM, advanced knowledge acquisition and design methodology, McNeese et al., 1995; A Framework for Cognitive Fieldwork, McNeese, Bautsch, & Narayanan, 1999; The Living Lab Approach, McNeese, Mancuso, McNeese, Endsley, & Forster, 2013). Other components of this focus transact across social psychology and how it influences intelligent systems (Wellens & McNeese, 1987, 1999; McNeese, 2006). Yet the overwhelming intent of this work is to expand interdisciplinary connections to make distributed team cognition more meaningful to our everyday lives, and to enhance and understand more clearly the roles of context, socially coupled systems, and information and communications technologies (e.g., Fan, McNeese, & Yen, 2010).
Our own work includes many studies, dissertations, and research grants appropriated for an integrated framework to examine distributed team cognition that emphasizes (a) cognitive systems, (b) contextual fields of practices, (c) socio-technical/socio-computational studies, and (d) human-in-the-loop simulations and modeling. To further extend and highlight the work mentioned above my co-editors provide an even more extensive bandwidth with much recognition and highly cited studies in the areas of team cognition, training, situation awareness, and simulation studies that complement, reify, and provide sound coverage of team cognition work over the last 25 years. That work for all of us has spanned across multiple positions in government, business-industry, and academia so it is inclusive of many types of experiences, layered understanding, and positions on the topic. Indeed, our joint book in the early part of the 2000s (McNeese et al., 2001) provided foundations and trends within an emergent team cognition community. Almost 20 years later it is important to assess what has evolved, what is important now’ as the state of the art, what may come to pass as the future of distributed team cognition, and how team cognition has inherently become more distributed with the influence of information sciences and technology.
We have produced many papers, given many presentations, and received grants that clarify various directions mentioned above. Yet rarely are the multiple perspectives and worldviews that underlie distributed team cognition available for consumption within a single volume. Therein the raison d’etre for this handbook can be delineated (i.e., “Why this book now?”). The first justification is based on the idea of thoughtfully designing a handbook that brings together top scholars to present multiple perspectives on team cognition in one fell sw'oop (what was referred to earlier as collective frame of minds). This alone would provide a useful and current research volume to specify the logical connections among worldviews, theory, methods, application, and practice.
As we consider recent work from all of us in areas of distributed team cognition, team mental models, team situation awareness, information sharing, and decision making, it is only natural to think about how significant the reach of team cognition has been and to examine how' it is extended through the influence and application of information sciences and information technologies. Therein, the second justification for the handbook is to show how information sciences and technology has evolved team cognition to be more in line with distributed cognition areas. Breaking this down in perhaps a deeper way we can now say that “distributed” connotes more than just cognition distributed across place (i.e., the contextual and cultural basis for distributed cognition, see Scribner & Tobach, 1997). It is true that one of the primal meanings of distributed cognition is that of knowing how thoughts are linked to work in context. But being distributed also means more than just that. It means that cognition is distributed across time and place (temporality proceeds into the future but is often reliant on the past, often referred to as temporal work, see Mohammed et al., 2015). Cognition necessarily distributes information where collaborative information must be sought, defined, retrieved, reified, foraged, and saved (often referred to as collaborative information seeking, see N. J. McNeese & Reddy, 2017, and information fusion, see Hall & Jordon, 2010) and information is distributed across an array of team members (participants interacting towards a joint goal where common ground emerges along the way). Cognition is distributed from an individual to a team and back to individuals in varying degrees of interdependency (often referenced as knowledge transfer and collective induction, see McNeese, 2000). And finally, cognition in today’s society is distributed across many levels of computation and technology (e.g., social informatics, web and mobile computing, artificial intelligence, the rise of enterprise networks, big data analytics, and the internet of things all can produce new ideas and conceptualizations of what cognition is and what it means as well as how group-team definition varies) and is reified to new levels through dynamic collaborative interaction.
Looking at this point with a bit more depth, distributed technologies such as the internet have fundamentally changed what we mean by team cognition and how it is practiced in 2020. Technologies have been disruptive towards defining what cognition means in 2020. First, distributed cognition is now very much influenced by virtual work that transpires through the providence of ubiquitous computing, social informatics, the internet of things, and smartphone applications. Unfortunately, many of the original theoretical perspectives on team and distributed cognition that emanated out of psychology and communications communities are entrenched in the assumptions of the computational substrate of the 1980s, and hence are rather uninformed by monumental gains in virtual interaction, data science, robotic enablement, crowdsourcing, and human-autonomous systems.
Second, a lot of work in distributed cognition is from unary points of view that tend to not be interdisciplinary but often are subject to certain biases within a given scientific community. For example, the communities of computer-human interaction (CHI), computer-supported cooperative work (CSCW), human factors (HF), situated cognition, cognitive science and modeling (CogSci), cognitive systems engineering (CSE), and naturalistic decision making (NDM) all touch upon distributed cognition but have different mindsets, methods, biases, and levels of understanding and are often insular to each other rather than facilitating mutual learning. Their funding profiles and sources may also highlight directions and outcomes that are not similar. This can result in guarded values and closed minds that are typically not open to discussion, discernment, and hermeneutics that could advance further growth and development across worldviews.
Third, “cognition” is not typically seen in very broad terms but frequently is only equated to traditional cognitive studies that are grounded in memory, learning, reasoning, and judgment. While these areas are genuinely important and have been researched extensively, it is imperative that the other powers of the mind are examined, such as creativity, intuition, values, imagination, emotion, and culture, wherein collective mindfulness is a useful construct.
Fourth, the areas of application for distributed cognition concepts are very wide open and expanding with the spread of technological innovation. For example, one of our groups at Penn State embarked on a unique twist of this kind of work: cyber situation awareness (see McNeese and Hall, 2017), as have others but it is just beginning to scratch the surface of interdisciplinary applications. Other application areas/ domains that are emerging for consideration of distributed cognition theory and concepts are intelligent systems in natural gas that interconnect data, humans, objects, locations, and supply chains; risk/crisis informatics; health, disease, and medical informatics; climate change and geospatial information science; online interactive learning environments; understanding terrorist social networks; uninhabited vehicles; and human-robot interaction, to name a few. Let’s examine some specific contexts in which distributed team cognition could occur.
Examples of What We Mean by Distributed Team Cognition
In addition to the example provided earlier we provide two specific examples of how distributed team cognition is evident within society today, specifically reinforcing the ideas that distributed team cognition is often highly interdependent upon various forms of information and communication technologies. The first example comes from the emergency medicine/hospital domain. An ambulance is called to the scene of a car accident wherein one car has T-boned another. There are multiple injuries that have occurred as each car has multiple occupants. Indeed, this represents an emergency situation wherein time is essential, there are a number of uncertainties with respect to the severity of the injuries, a team of teams approach is necessary (inclusive of initial responders, ambulance crew, help flight crew, and police), an emergent context changes what is known when, and multiple layers of information are distributed across the context, the people involved, the vehicles themselves, and potentially in camera technologies that have recorded the accident. Not only are medical concerns utmost in priority but potential litigious issues will be at play (who caused the accident). This particular situation represents a distributed cognitive event that is dependent on team performance and individual roles within a team, team-to-team transfer of information, and joint problem solving/naturalistic decision making, as well as the use of technology to communicate the state of the emergency across all parties, but also information technology that is used to ascertain situation awareness about the conditions of the occupants. One occupant (a driver) is severely injured and is taken by air-flight to a trauma unit twenty miles from the scene while three other occupants are taken by ambulance to a local hospital. Both the air flight and the ambulance are setup to transmit and convey information (both auditory, visual, and actual photographic imagery) directly to the appropriate hospital units to prepare physicians, specialists, and nurses prior to arrival at the hospital. This is very important for problem solving and decision making particularly with respect to temporal expedience. Therein, this kind of situation is one example of distributed team cognition in an applied domain.
Another contemporary example surrounds the distributed nature of information and cyber security. Multiple hacking incidents have occurred at the highest level of the Department of Defense and other government agencies (on a daily basis). While there are many tools for determining the sources and patterns of hacking and perpetrated attacks, a more nuanced approach would include looking at the humancentered aspects of information security, cyberwarfare, and risk. Some of the work we have partaken (see Cooke & McNeese, 2013; McNeese & Hall, 2017) indicates that these integrated topics of research must indeed be approached from a wholistic perspective representative of distributed team cognition that provides analysis and prognosis to look at (1) interdependent layers of contextual perturbations (inclusive of data, information, knowledge, wisdom), (2) the role of team cognition in both producing and recognizing articulated attacks (strategic offensive and defensive information warfare), and (3) increasing use of a multitude of data science techniques and requisite information technologies that compose distributed cognition to formulate the power underlying situation awareness, risk, and deceptive behaviors. This domain is often only considered from a blunt individualistic, techno-centric methodology that completely ignores the human-centered and distributed cognition approaches needed to break down intent and complex behaviors. The domain has a necessity for considering a team of team’s approach to make sense of complex situations, requires a high degree of information sharing for success, and very much requires that a deep understanding of the emergent—often hidden—context that pervades this research area.
As I began to conceptualize the model for this handbook one thing that struck me is how in the world did I get from early childhood interests and thinking—way back when—to my current level of expertise now? And how did this collective experience come to develop the area for which this handbook has been designed? The authors contributing to the handbook can all ask this same question and the developmental trajectories will obviously be different, but meaningful in terms of the shaping patterns, awareness, and insights that led to research within distributed team cognition. This is how research interests come to pass. To make this extant, the next part of this beginning chapter looks at the longitudinal evolution of distributed team cognition from my own personal, autobiographical outlook. Walker (2017) discusses why autobiography is a legitimate methodological technique to reveal critical research as a narrative inquiry. Walker suggests that “stories reflect a set of values, rules, norms that oversee a person’s learning and sense of logic (Maynes, Pierce, & Laslett, 2008)” and “when viewed as source of data, autobiographical narratives situate reflexivity within contexts of cultural settings (DeGloma, 2010) that offer researchers an important set of social and individualized contexts to study (Brockmeier, 2012)” (Walker, 2017, p. 1896). The following critical inquiry seeks to trace historical markers, interdisciplinary connections, and firsthand personal knowledge as pertinent in deriving and constructing this handbook. Necessarily, this example shows how one could come to develop a research niche in distributed team cognition over a long developmental timeframe. Walker emphasizes the point that inquiries such as this provide a basis for identity and lifelong learning. It is inferred then that these components are pivotal in establishing a researcher’s awareness, attention to detail, and progression towards expertise within a scientific subject matter.
DEVELOPMENTAL HISTORY: A PERSONAL PERSPECTIVE
As I consider where my life has taken me it certainly is the case that it has been influenced by research and design (R&D) opportunities in many different facets, through multiple distinct venues, and with unexpected outcomes across time (literally over 60 years of shaping influences). As it turns out design has surrounded me in somewhat unusual circumstances prior to the research focus taking hold. Therein, perhaps design and research (D&R) is a better descriptor of a major persuasion on my life. My earliest interests in design occurred through an awareness in imagining inventions and then sketching or drawing them out (early drafting proclivity!). While in grade school I should have paid more attention to teachers but instead—beginning in the third grade—I would lay my head down on my desk and draw and draw and draw. I know this sounds strange but laying my head down enabled me to “see” the design come to life (maybe just a form of concentration). Obviously, this did not help me with assignments and quizzes but the desires of my heart—inventing and drawing— were assuaged.
With Design in Mind
One primary venue for drawing and “first designs” was through sketching and refining cars for many purposes. Cars and car design were my passion and at five years old I had a keen interest in Car Craft and Hot Rod magazines. They provided motivation for thinking about new designs. As I began reading about performance in cars I started to get engaged with engineering that resulted in improving performance. I also realized that design and performance in cars was intimately coupled with the driver (the human element). Therein, this was the first sense of the human factor as it involved automotive design. In these early days then there was a nexus of form, function, and use. This enabled designs to be transformed into products that accomplished their performance objectives. This was my first foray into user-centered design (building cars around the driver and what s/he was capable of doing). While the engineering design interests continued to unfold I also had creative passion for the aesthetics of car design which correlated more with the field of industrial design. These interests formulated strong seeds that grew into diverse pursuits. I ended up obtaining early degrees in design and technology and psychology, and worked as an engineering designer for several years before the research focus emerged. The seeds of design however took some interesting twists and turns. One of the elements within design that touched my curiosity was the idea that designs could be transformative, both at the individual and the societal level. At the time, I did not realize this consciously but the seeds that set the groundwork for my research expression and evolution where intimately tied to understanding the crossroads of previously distinct vocations or professions, which in contemporary circles today is expressed as interdisciplinary sciences.
I had the fortunate opportunity of growing up in the Dayton-Kettering, Ohio, area which is historically known as a hotbed of design, innovation, and industrial manufacturing (see Bernstein, 1996). Indeed, the city of Kettering was named for none other than Charles Kettering who designed the first self-starter for automobiles and established Delco (Dayton Engineering Laboratories Company) which was the research and design arm of General Motors Corporation. Dayton was the second largest GM town in the country during the 1960s and ’70s and was heavily involved in the auto engineering industry. My father worked for Chrysler Air Temp in Dayton, ironically, in the job position of time study engineering.
As I approached ten years old, I developed an awareness of what Dayton was known for in the areas of invention, engineering, and technological progress. The Wright brothers, inventors of the airplane and early flight technology, were pioneers in the innovative spirit behind design. The influence of the Wright brothers was pervasive across many areas of engineering and aviation, and is something native Daytonians are proud of. Growing up in the Dayton-Kettering area as a grade schooler meant that our house was about eleven miles from Wright-Patterson Air Force Base. I started getting interested in flight oddly enough by watching the flight paths of F-4s literally fly over our house as they made their approach to the base. Certainly, there were other aircraft that would fly over as well. But one of the amazing things the F-4s would do is fly faster than sound, hence producing sonic booms. We heard quite a few of these which added to my fascination and intrigue with flight. Another component of this interest was the zeal I experienced visiting the U.S. Air Force Museum (at the time in Fairborn, Ohio). Their displays of actual aircraft describing the history, performance, and precedence of many different flying machines was both incredible and fascinating. This also inspired me to think about new kinds of fast aircraft and make model versions therein. (In addition to creating and drawing designs I started an active hobby of making models—cars, planes, and ships.) The museum also amplified another upcoming interest—space flight—that I found intriguing but was a bit out there when I was ten years old. The museum had some displays of early rockets (likely from the Mercury program).
Actually, the space program was coming into its own in the 1960s with the Gemini and then Apollo missions sending astronauts into orbit and eventually to the moon. During the writing of this handbook, the country celebrated the 50th anniversary of Neil Armstrong, Buzz Aldrin, and Michael Collins’ first flight to the moon, resulting in humans walking on its surface. I want to mention this at this point as the space program was kind of a first revelation to me how individuals, teams, and technologies work together to achieve a monumental goal.
The space program was brought front and center while I was at Rolling Fields Elementary School (Kettering) and Jefferson Elementary School (Dayton) mainly because whenever there was a space launch, teachers would bring their televisions to school and we could watch what was happening live. This brought a real aura to make science especially relevant and applicable, even more so for me. As I reflect back on these days of splendor there are some very striking foundations of my awareness. This really is the first time wherein a command post with people working together (i.e., teamwork/interaction) was shown in process. The notorious ground control function was a large command post in Houston where engineers, scientists, and communication specialists all performed under a sense of pressure (stress to complete their specific role and function as coordinated with other specialists to produce a joint outcome). And while I was aware that teamwork was important in the mission control room to make Houston happen, I was not—as a ten year-old— cognizant of the concept of team of teams. But that was exactly what was happening on space launch days. There were multiple teams within ground control responsible for specific functionalities to be achieved (sub-goals) wherein the outputs of teams were connected to input, throughput, and output of other teams to achieve major timely goals, i.e., team performance. And teams were also needed in Cape Canaveral as well to facilitate the actual rocket launch on site. But most of all the astronauts typically worked together as part of a two-person or three-person team on the space capsule itself. In the case of Apollo 11 the three-person team then bifurcated into a two-person team engaged in the control of Challenger to approach the landing on the moon, then in preparing and actually walking on the moon, but at the same time still working with Michael Collins in the main space capsule.
Not only was the prominence of tremendous teamwork on display for a nation to be in awe of, but for me this was the time when remotely located, distributed work actually meant something for a real situation. While I must say these words per se were not part of my vocabulary given my age, they were understood intrinsically through the communication and actions that emerged as astronauts engaged tasks in their respective environments. The moon is 238,855 miles from earth. Seeing astronauts that far away communicate and talk to ground control provided an applied understanding of what these words meant in reality. Not only were they communicating remotely from such a far-off distance, but remote control and monitoring of information within the spacecraft and throughout the mission demonstrated the notions of distributed remote interaction and distributed information as used across different contexts. The control dynamics associated with information, humans, and joint actions taken could be done at distance! It seemed magical for a ten year old!
The notion of distributed also connoted that the role of context was heavily transacted with the way information is perceived and used to make things happen across distance. Today we might think about this as related to ecological dimensions of time-space-control. Often this is specified by information embedded in the mutual interactions of affordances and effectivities (see Young & McNeese, 1995)—even though obviously at ten years old I did not understand these principles—they certainly apply to many complex problems in current culture. One example of this is the idea that gravity changes the time-space-control interaction that astronauts had to learn in order to move and work in space. Ironically, I remember watching simulations that they used to experience what loss of gravity would be like in space and realizing for the first time what a simulation was and how it could help astronauts become aware of their new situations (even though I knew nothing about situation awareness in 1964).
While observing that teamwork was highly resident throughout the space mission there was one additional element definitely worth mentioning. It is that the command post (mission control and launch control) was a place w'here technological support was critical for enabling team interaction throughout various stages of the mission. This could take different shapes. The space mission was the first place I recognized that NASA team members (albeit lined up next to each other in linear fashion) were interacting with large screen display technologies with information specific to a team’s function. Concomitantly, team members also used specific control devices to manipulate information and perform physical actions requisite within their task demands. This turned out to be an early example of classic human factors—as engaged to support the overall space mission pertaining to individual, team, and team of team applications. It was relevant to me. It represented multiple layers of designs to be considered specifically in support of performance. It also showed individuals worked in the context of a team and that teams needed to collaborate with other teams to jointly produce work that accomplished tactical and strategic objectives—amazing outcomes!
In summary, this early realization provided recognition that teams were incredibly important to achieving complex system objectives and mission success. This is when teams, and in particular, distributed teams connected through technology, became real for me. Why do I report these early reflections? Because many chapters throughout this handbook take a distinct perspective and different perspectives do not just magically appear—they come from somewhere, from given influences. These innate perspectives are typically motivated by an individual’s passion in life (often at an early age). That passion along with their personal mindset, interests, and experiences help to shape the research topics which constitute unique formulation about teams, cognition, and technologies. As a case in point, my early proclivities toward design and invention as related to cars, flight, and space flight eventually became the girders that produced much of my interdisciplinary research space. As irony would have it, 30 years later I would be working in the design of collaborative environments as informed by team performance experiments in the context of distributed command posts (more on that in a bit).
Imprints and Opportunity in Dayton and Beyond
While I continued my car design niche in the fifth grade (I began mixing two genres together by creating designs for rocket-powered cars and jet-powered water bikes), I also started to read more about inventors in general but specifically the Wright brothers. They actually began their expertise with bike mechanics and designs prior to developing ideas pertinent to flight. As Bernstein (1996) points out the Wrights and other inventors in Dayton were what he referred to as “grand eccentrics.” Many of their beliefs and ideas were off the beaten path. Another intriguing avenue of the Wright brothers’ approach was bionic design wherein they observed birds in flight and tried to emulate the processes, structure, and mechanisms of birds within their concepts for flying machines. Little did I know in the early 1960s that I would later be intimately involved in the engineering and design of human-centered aircraft at Wright-Patterson—sometimes we are surprised where life takes us and how we became scientists within team cognition. The paths and trajectories are often eccentric, nonlinear to normal progressions. While the Wright brothers are the most famous inventors and people from Dayton there are some other inventor influences that need to be mentioned, too.
Another element of technological progress intrinsic to Dayton was the National Cash Register Company (NCR) as headed up by John Patterson—he was the chief executive officer. Yes, this is the “Patterson” which Wright-Patterson Air Force Base is named after. NCR headquarters in Dayton was actually one of the first and preeminent companies involved in the design, manufacture, and sales of mechanical computers—the cash register. The mechanical computer preceded but contributed to concepts employed in the electronic computer (cash denoting numbering and counting systems and registers for storage, memory, and manipulation of numbers—all of which are important for computing). John Patterson became internationally famous not only for overseeing the NCR company and producing cash registers internationally, but as a pioneer in innovative management and merchandising techniques which contributed to the industrial revolution in America. Charles Kettering actually worked at NCR before establishing Delco and invented the first electronic cash registers while there. Eventually Kettering would become chief of research at GM where he went on to invent spark plugs, leaded gasoline, four-wheel brakes, and the automatic transmission. His home was the first in the United States to employ air conditioning (via Freon, which was invented under his leadership). Later in his life, along with GM president Alfred Sloan, he established the Sloan-Kettering Institute for Cancer Research. Truly, this was an amazing fellow and inventor’s inventor.
As it would turn out, NCR and IBM were two of the very first computer-based companies to begin research and design in electronic computing, therein developing many types of computational products that are still in the marketplace today. Both companies also incorporated new avenues that helped to pioneer the field of humancomputer interaction (HCI) that preceded many of the contemporary company’s focus and incorporation of user experience in their product designs (see Grudin, 2005 for a history of HCI; Stuster, 2006 for stories about early human factors accomplishments; Harrison, Henneman, & Blatt, 1994 for early HCI work at NCR). An early reported extension of the NCR computer system was first used in the development of bar code scanning for supermarket checkout. These systems were developed in the late 1960s and represent some of the first intersections of humans, computers, and commercial products. The scanned checkout is still active today to help customers process their items efficiently independent of the grocery clerk. Early human factors research was conducted on this system by Lewis Hanes, NCR Research Center, Dayton, Ohio (see Stuster, 2006). The first in-store use of the barcode scanner was at the Marsh Supermarkets, Inc., Troy, Ohio. One small irony is that when my wife Judy and I were first married we lived in Troy and shopped at that very store where the first scanners were tested. Hence, the history of NCR has been very prominent in computation for a long period of time.
Therein, my life in Dayton was heavily entwined with design and aspects of how design could inspire new creations to unfold. As I spanned from grade school into high school (ironically at the John H. Patterson Cooperative High School in Dayton) my hobbies and interests turned more seriously towards design. I was accepted into the drafting and engineering specialization at Patterson. The high school was entirely unique in that it preceded what we now term career academies.1 A student selected a career path that they hoped to pursue and coursework was designed around that trajectory. But more importantly as juniors and seniors one was able to work in business and industry in an area highly related to career choice. We would— cooperatively—work for two weeks in our jobs, then go to school for two weeks to study academic material inclusive of college preparatory and technical coursework. To do this required going to high school through July but at age sixteen I was working in the role of an engineering assistant/nameplate designer. This kind of high school experience prepared me greatly for college where I majored in engineering design and psychology.
When I graduated from the University of Dayton in 1977 I went to work as a draftsperson and worked for four years “on the board” earning my way up to senior designer. My work in this initial post-college position was actually at the Wright-Patterson Air Force Base for the Systems Engineering Avionics Facility (SEAFAC). This was critical as it exposed me very early on to systems engineering and computing, in particular avionics design. Most all of my cooperative education experiences in high school and college focused on engineering design rather than industrial design. Yet my true interests were strongly emerging in the area of design of systems that involved humans which at the time was referenced as human factors, engineering psychology, or systems psychology. In 1981,1 got my big break towards that end which sparked a career that led to human factors and eventually research in team cognition.
While working as a designer at SEAFAC my employer paid for me to get a master’s degree in experimental cognitive psychology (again at the University of Dayton). In 1977, I started taking late afternoon and evening coursework to accomplish this goal. I was trying to fuse together a multidisciplinary approach with some of my elective courses to forge a cognitive approach to computing and human factors (what would later transmogrify into two of my main areas, humancomputer interaction and artificial intelligence). In 1981,1 had all my course work completed and was beginning work on my MA thesis which was focused on the perceptual recognition of complex images using hemispheric specialization (traditional cognitive psychology experiments were conducted). One day I was out for a walk and had lunch in a scenic area at Wright-Patterson Air Force Base. I had however forgotten my drink. After I ate I was thirsty so I decided to go to the nearest building for a drink of water or a vending machine Coke. I walked into a building nearby and as I looked up in the corridor there was a sign that said “Human Factors Branch.” To make a long story short I ended up interviewing for a civil servant position—engineering psychologist—in that branch and in June of 1981 I became an employee of the USAF! My early childhood dreams of designing aircraft were beginning to come true in an unusual way to say the least. I worked for my branch chief, Dr. Richard Schiffler, in the home office for a few years and was assigned also to the KC-10 systems program office to be the human factors engineer for that entire program.
Another big break came along in 1983 when I was assigned to the “skunkworks” (USAF Crew Station Design Facility) to be part of the design team of the electronic, computerized cockpit for the F-16. This was a dream job as there were many simulators there and in particular an F-16 hybrid that was hooked up to PDP-11 computers to generate imagery-symbology and new ideas for informatics in the cockpit. This enabled running many experiments utilizing novice and expert pilots involving human-computer interaction designs for the F-16 cockpit. After the pilots would participate in their experiment we would conduct in-depth interviews with them, and then go back to the drawing board to incorporate changes in design for the next experiment to continue to test performance to the point where it showed improvements. This process enabled a form of continuous process improvement that eliminated errors and created the best possible human-computer interface for the pilot. This is about as good as it gets for a human factors career in applied research and design. However, I was missing a key critical piece—the basic science component of human factors, cognition, and design. Therein, in 1984 I did a lateral transfer to the USAF Aerospace Medical Research Lab (AFAMRL) as an engineering research psychologist. I am sorry to belabor one with all the messy details to get to this point but this was the developmental history and awareness that brought me right up to the point of engagement with distributed cognition/team cognition/information communication technologies.
One of the things that I learned working in real-world human factors is that the power of the context often drives decisions as to how to support the human (or a team) within complex systems design. That has certainly been the case as my research area translated from applied human factors engineering to research in team performance, and is often specifically the basis of understanding what distributed team cognition means. The context of teamwork has driven how my interests and perspectives evolved over time. Context can infer situated settings and fields of practice and points to the socio-technological sense surround that an individual or team encounters. I was first intrigued with context and what it meant, with interest in space operations as a child (e.g., what it was like flying in a spacecraft getting ready to land on the moon). But the depth of meaning progressed to teams in support of various fighter pilot operations. While at work in ASD I soon discovered that most jobs were not really only individualistic but touched on team operations at different points in time.
When I became a scientist at AFRL in 1984 the first focus of my research was looking at how cognition facilitated individual and team performance. With respect to teamwork, the context focused on military command, control, communication, and intelligence (C3I) communities. Part of this research thrust included how to design support systems for teams that usually involved problem solving, decision making, situation awareness, and actionable intelligence. This was literally the point in my timeline when research in team cognition began (1984). Research began attuning the use of new information and communication technologies for select tasks one would encounter in these environments (e.g., large group display to display information for use in military command posts, McNeese & Brown, 1986). Therein, one could frame this as principles of human factors engineering applied to a specific context that included the presence of dynamic teamwork. It signaled the “coming of age” of my intellectual interests and passions with my specific academic training. While this was a kind of “basic level” approach taken in the mid-1980s the research specificity morphed and sharpened into looking at how the cognitive components of teamwork (team cognition) might be amplified and supported by intelligent systems (e.g., decision aids). The interaction of team cognition (human and machine agents) within specified C3I environments revealed challenging dynamics and wicked constraints, distributed and frequently only partial information availability, and the distributed presence of human actors outside of a given locale. It necessarily included mutual levels of influence from tangible variables such as individual differences, cultural predilection, and temporal integration/rhythm, to name a few. This interaction thus chiseled a foundation for what we term distributed team cognition.
So why was this time in the USAF important in contributing to my awareness (beyond what I have communicated above) in reference to distributed team cognition? First, it melded together my passion for technological design and psychological science. Second, it made an amazing connection between basic research and applied real-world settings (what the government/military referenced as 6.2 applied research levels of R&D) while still affording some focus on 6.1 basic research, which I considered the perfect mix. Third, it amplified my ability to actually conduct interdisciplinary research according to my joint interests in cognition, computer information sciences, human factors engineering, and collaborative systems and technologies, and to publish in these areas. Fourth, it enabled me to communicate and work with world leaders in the above-mentioned areas and to understand their collective expertise (renowned scientists and engineers such as Mica R. Endsley, Herbert Simon, Robert Williges, Kenneth Boff, William Rouse, Gary Klein, Jens Rasmussen, Eduardo Salas, John Flach, Kenneth Hammond, David Woods, Robert Hoffman, Penny Sanderson, and many others). And the connection at AFRL also provided some of my closest research colleagues (some of whom I still work with). My experience at AFRL in C3I more specifically allowed me to look at the interconnections between individual and team performance (as relative to command posts at first but then more generally later on) and how this performance could be supported through collaborative systems—information and communication technologies. Finally, and perhaps most importantly, it provided two educational opportunities that significantly amplified my career in distributed team cognition: (1) progression towards a PhD (through USAF support) at Vanderbilt University in cognitive science (1989-1992) and (2) provision of a sabbatical taken as a visiting professor at The Ohio State University in the Department of Integrated Systems Engineering (1997-1999).
While at Vanderbilt University I directed half my focus and coursework towards computer science and Al, allowing more technological insights to flourish. As part of the program I also emphasized the areas resonant within cognition (memory, learning, problem solving, decision making, collaborative work) which would continue to guide my research niche many years into the future and in fact formulate the foundational edge for this handbook. This allowed me to do research in cooperative learning, artificial intelligence, decision aiding, human-computer interaction, and computer-supported cooperative work. However, while at Vanderbilt I received more exposure to other philosophies in cognitive science which led to even more awareness of the ecological approach to cognitive systems. This ended up creating—for me anyway—a belief and philosophy in what is best described as distributed cognition, situated cognition, or embedded cognition. One of the chapters in this handbook is by my office mate at Vanderbilt, Dr. Michael Young (and his colleagues). We both grew up under the intellectual influence of Dr. John Bransford which influenced our mutual thinking around distributed/situation cognition and the practice of learning. In 1995, we jointly published a book chapter that specifically focused on what a situated cognition approach would mean for the area of problem solving (Young & McNeese, 1995). You will see visions of this in our chapters and elsewhere but the handbook is designed to present multiple philosophies so there are many approaches present. But this is the approach I have taken and continue to advocate.
As is often the case in government research laboratories one can be reassigned to promising new areas to generate new insights and research responsibilities. Once I returned to Wright-Patterson AFB from Vanderbilt I was placed in the position of Director of the Collaborative Design Technology Laboratory. I was in charge of studying how collaborative technologies could help improve performance in distributed design teams (as a field of practice). This is a great example where distributed team cognition was present. In my vast amount of years as a researcher this was really the only cognate area where I was both an actual practitioner and researcher which obviously made it highly unique (e.g., McNeese, Zaff, Brown, Citera, &
Wellens, 1992; McNeese, Zaff, Brown, Citera, & Selvaraj, 1993). Stated another way it represented the apex of my passion for design and my increasing proclivity to study team cognition wherein collaborative technologies could make a difference in team performance. We really looked at a variety of variables within distributed design teams using different kinds of methodologies and approaches (see Citera et al., 1995; McNeese, Zaff, Citera, Brown, & Whitaker, 1995; Whitaker, Selvaraj, Brown, & McNeese, 1995).
In the mid-1990s, in yet another twist of positions at AFRL, after this first lab went away I was made director of a bigger laboratory, the Collaborative Systems Laboratory, which crossed team cognition, information and communication technologies, and situated context. This newer laboratory returned the contextual focus back to C3I and focused on looking at more generalizations with respect to distributed team cognition. These laboratories and the research conducted therein represent the interdisciplinary, transformative nature of my research direction and passions.
As the millennium came to a close major new changes were in store for my career. Based on the research established at AFRL in team cognition and cognitive science I took a job as associate professor in the new' School of Information Sciences and Technology at The Pennsylvania State University (University Park, Pennsylvania) where I stayed for 17 years until my retirement in 2017. (I am currently Professor Emeritus at Penn State University.) One of the junctures representing the first half of my research career was the publication of our New Trends in Cooperative Activities book in 2001 (McNeese et al., 2001). As mentioned at the beginning of this chapter that was two decades ago and a lot happened at Penn State while I was there. I continued publishing and getting various grants associated with distributed team cognition. I was able to translate doing research in the C’l context (from the military arena) into the field of practice of emergency crisis management (civilian sector) in additional to a few other contexts.
As mentioned one can have many directions and focuses w'hen studying teams in multiple contexts under varying conditions. The research our groups have conducted over the years has changed quite a bit and been readily modified dependent on the specificity of details within the boundary constraints of the context studied. To be more concrete early on in the USAF (mid-1980s) the context focused on military and primarily USAF command posts but this morphed more into emergency crisis management during the 2000s. There are similarities but also many differences that abound. After 9/11 the surge of interest in research related to crisis operations and crisis informatics became much greater and many of us were motivated to understand how teamw'ork contributed to contemporary crisis management problems in order to improve real-world operations (Brewer & McNeese, 2004; MacEachren, Fuhrmann, McNeese, Cai, & Sharma, 2005; McNeese et al., 2005).
An Emergent Research Pathway
As an example of our research profile in emergency crisis management, one of the specific research paradigm-contexts that we have used extensively is called the NeoCITIES simulation.2 The context underlying NeoCITIES conveys a notional representation of a 911 call center dispatch engaged in emergency crisis management operations as a team (Hamilton et al., 2010; Jones, McNeese, Connors, Jefferson, & Hall, 2004; McNeese et al., 2005). While the representation is not real per se it is built on knowledge elicited from real experts and insights from observations in the field (Terrell, McNeese, & Jefferson Jr, 2004). The contextual foundation of the simulation is predicated on the idea that a functional crisis management team consists of fire, police, and hazmat members that work both together and separately. They need to jointly address team decision making while being simultaneously engaged in individual decision making as relevant for their respective tasks. The simulation incorporates events and situations that emerge across time which have differing demands. The demands that arise require resources unique to each member, and that have to be allocated at strategic points in time to reduce the severity of an event (e.g., the fire member allocates the resource fire truck and the hazmat member allocates a cleanup crew to jointly respond to the situation). Team resources are limited in amounts and time they stay at an event, therein the allocation decision needs to be made tactically but in the midst of the emergent joint situation. The team cognition required employs distributed information that helps to define the problem state and team situation awareness, and leads to correct decisions about action. In this problem, the team must understand the overall problem as it emerges, be aware of joint demands (team situation awareness), while still devoting part of their attention to individual tasks that occur as well. While the situations are fairly well-defined the team must plan, share, and communicate to be successful (emulative of the real-world team activities).
Inherent in the NeoCITIES simulation is the idea that team members could be distributed across space (remotely located) but yet have the demand to work synchronously. NeoCITIES is an example of what a research paradigm-context can be for distributed team cognition, as defined in one particular way, but is just one instantiation of what could be established. The chapter by Marhefka et al. (in this book) provides more in-depth research using NeoCITIES and clarifies experiments with more specificity. As one reads through this handbook other unique research paradigm-contexts will be provided to help a reader expand their knowledge of research within distributed team cognition.
Many of us have come in contact with the themes provided in this first chapter (teamwork, cognition, technology, context) albeit in unique and very different ways. I have just reviewed my own personal story in terms of developmental and cultural derivation as it relates to becoming a scientist exploring distributed team cognition. Each author within this handbook could do something similar. As you read through the contributions presented keep in mind that each set of authors address their respective subject as a function of their own personal history and a set of experiences. While this produces multiple perspectives that help to explain the values of distributed team cognition, the integration of perspectives traces invariance in a way where at given levels of abstraction, common ground is certainly possible to a degree. As the next decade of research emerges, new perspectives about truth will dawn as the boundaries between human and artificial intelligences are lessened.
- 1. In 1968 the John H. Patterson Cooperative High School was designated as a nationwide top ten high school primarily based on the innovation in cooperative education at the high school level.
- 2. NeoCITIES was conceptually derived from the original CITIES simulation, see Wellens (1993).
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