Primer (Introduction)

The second volume of this handbook, Contemporary ResearchStudies, Models Methods, and Measures, builds on the girders presented in the first volume by examining distributed team cognition through different approaches that can be taken to simulate, model, measure, and analyze it. Like the diversity found in team composition, there are also many levels of diversity in the approaches taken to study distributed team cognition. A handbook should provide as many approaches deemed reasonable to communicate all the various dimensions of complexity that comprise interdisciplinary teamwork. Additionally, specific research studies have been undertaken to study the interconnections among teams, technologies, information, and context and are provided to demonstrate the value and worth of specific approaches and methodologies. While volume 2 does not capture every possible approach to contemporary research, the purpose is gather together relevant and representative information for fellow researchers to utilize and be cognizant of.

Volume 2 begins with Chapter 1 presented by my co-editor Mica R. Endsley and provides an insightful review of team situation awareness as related to and found evident in different domains. Her review portrays a lot of valuable information in conceptualizing and operationalizing the construct as applicable to distributed team cognition as processes, devices, and mechanisms contribute to the construct. In particular, the chapter elucidates research and findings relevant to measuring and modeling the construct for use in experiments and engineering design. Of great value is the idea of different devices that facilitate information sharing for team members and what requirements are salient.

The second chapter by Johansson, Granlund, and Berggren presents a very incisive review of C3Fire, the microsimulation that has been used for a wide variety of experiments and approaches to investigate distributed team cognition for the last 20 years. Within that time span the simulation has yielded a wide berth of discoveries in team cognition and distributed cognition that are highly relevant to understanding models, measures, and techniques. The chapter points out the versatility of a dynamic simulation and what it can mean for an integrated research program. The simulation itself is heavily coupled to the real-world domain of emergency response in addressing forest fires and becomes a bridge between experimental studies and field work. Many findings relative to coordination, dynamic decision making, and collaboration are highlighted throughout the chapter.

The third chapter by Dunbar, Gorman, Grimm, and Werner provides a nice review of framing team cognition through a dynamic systems lens. The chapter provides details as to how to apply methods of dynamic systems approach to specific domains, and what this might mean in terms of modeling and measuring team behavior. The chapter is valuable in the sense it provides yet another alternative worldview in framing and in turn researching distributed team cognition. The chapter also addresses the contemporary issues surrounding human- autonomy teaming and what may be done to assuage problem areas and address dynamic actions.

The fourth chapter by Naikar provides yet another alternative world view in approaching distributed team cognition: cognitive systems engineering. This view, like some of the others presented in volume 1, is highly aligned with the theories of ecological psychology but specifically makes use of models that capture interrelated elements of sociotechnical systems. The chapter’s primary emphasis looks into the nature of self-organizing teams wherein work is both distributed and adaptive to the demands within the workplace. The chapter makes use of models of cognitive w'ork analysis and design methods but specifically details the diagram of work possibilities which emphasizes computation work for both actors and artifacts.

The fifth chapter by Khaleghzadegan, Kazi, and Rosen explores the basis of team dynamics within the complexity of natural work environments through reviewing measurements directly valuable for distributed team cognition. The important area of measurement surrounding teamwork that involves physiological indicators within team cognition is of particular interest within the chapter. The authors review team cognition with special interest towards unobtrusive measurement strategies and look at shared physiology, linguistic and paralinguistic speech features, and activity tracking generating a very interdisciplinary approach to measurement. Their chapter weighs heavily towards the value of simulation, use of event-based methods, and technological advancement in distributed team cognition environments when considering unobtrusive markers.

The sixth chapter by Drury, Pfaff, and Klein addresses and reviews the strategic topic of causal mental models in distributed teams. The chapter explores techniques for assessing and comparing causal mental models to determine salient differences within their content. The authors utilize two rigorous modeling tools that derive from distributed cognition as part of the basis to compare models: (1) descriptive to simulation modeling and (2) distributed coordination space. The use and value of these two tools are highlighted in an example. DESIM is further elaborated in terms of limits and capabilities and the type of modeling situations for teamwork for which it is best suited.

The seventh chapter by Schaffer, Humann, O’Donovan, and Hollerer looks at some of the more advanced technological elements underlying complex teamwork by exploring areas of modeling and quantitative measurement in dynamic human- agent cognition. The focus is within recommender systems wherein human cognitive bandwidth may be required to interact with computational agents. The authors provide a statistical-based modeling technique to address this kind of interaction for two task paradigms. The results provide intriguing aspects related to cognitive traits and beliefs as relevant for agent interaction that are pertinent for considering global situation awareness, trust, and appropriate workload.

The eighth chapter by Karl Perusich delves into ways of considering complex and fuzzy relationships within distributed information that emerges across time. The fuzzy cognitive map is introduced as a qualitative modeling technique to capture changing situations that are present in most fields of practice that individuals and teams engage with. The modeling technique is conceptualized, explored and reviewed, and explained as relevant for a real-world modeling example. The chapter then shows how a cognitive map can be constructed to capture expert-situational knowledge. The chapter demonstrates how the fuzzy cognitive maps can be used for prediction of behavior.

The ninth chapter by Johnson, Vignatti, and Duran again draws focus to the important area of human-machine teaming and reviews the requirements necessary for effective performance. The chapter points out that traditional task analytical approaches are inadequate and instead concentrates on principles-based interdependence. Much of the chapter then lends credence to the Interdependence Analysis tool and how it can be used in addressing joint activity in understanding human factors considerations and technological constraints. The tool is explained and developed for use in designing human-machine teaming coupling for distributed team cognition applications.

The tenth chapter by Tolston, Funke, Riley, Mancuso, and Finomore explores the higher order relational properties inherent in team cognition by utilizing observables present in team activity. The chapter is hence predicated on measuring the emerging information processing that implicitly relies on knowledge structures utilized by interacting teammates as they uncover, share, and negotiate the meaning of their goal-directed behavior with a context-specific setting. The chapter reviews and presents a very critical measure for understanding team mental models and cooperative work: team communication analysis. The authors review the challenges present in using this type of analysis and address issues that are relevant for use of these kind of analyses. They then articulate the need and use of a specific kind of analysis— conceptual recurrence analysis—as a means for analyzing the structural semantic content of team communications. The work relies upon a bottom-up modeling technique that is based on natural language. This kind of analysis is applied to collaborative consensus building tasks for further understanding whereupon its value is derived.

In conclusion, volume 2 builds upon volume 1 but provides the reader examples of specific kinds of research studies, different methodologies, and measures used to comprehend constructs within distributed team cognition, and shows how unique modeling techniques can improve prediction, design, and understanding of salient variables that contribute to distributed team cognition. Volume 1 and volume 2 in turn provide a basis for thinking about and exploring solutions to challenges that arise in distributed team cognition involving technology innovation, design practice, and interface development within specific applied contexts (fields of practice) which will be addressed in volume 3.

Michael D. McNeese

1 Situation Awareness in Teams

 
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