The Oxford Handbook of Cognitive Engineering

ISBN : 9780199757183

John D. Lee; Alex Kirlik
658 Pages
188 x 260 mm
Pub date
Mar 2013
Oxford Library of Psychology
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Cognitive engineering is an interdisciplinary approach to the analysis, modeling, and design of engineered systems or workplaces in which humans and technologies jointly operate to achieve system goals. As individuals, teams, and organizations become increasingly reliant on information technology and automation, it is more important than ever for system and workplace design to be maximally informed by state-of-the-art cognitive engineering research. This volume is the first authoritative handbook to cover this recent and rapidly growing field. The handbook collects and organizes contemporary cognitive engineering research, drawing on the original research of more than 60 contributing experts. Coverage of human factors, human-computer interaction, and the conceptual foundations of cognitive engineering is extensive, addressing not only cognitive engineering in broader organizations and communities, but also focusing on individual cognition, addressing topics of attention, decision making, and multi-tasking. This thorough approach speaks to the broad scope of cognitive engineering, spanning the individual operator to teams and organizations, with a focus on how systems of people and technology, often in the form of automation, influences performance. By collecting the best of cognitive engineering research in one volume, this book serves as both a convenient reference guide and as a useful entry point to the large and diverse research literature. As such, this handbook will be a valuable resource for researchers, students, and practitioners in cognitive engineering and a variety of related fields in need of guidance for how to put their products, systems, and services into the hands of human users, performers, and customers.


Part One: Cognitive Engineering: History and Foundations
Introduction to the Handbook
John D. Lee and Alex Kirlik
Part Two: Cognition in Engineered Systems
1. The Closed-Loop Dynamics of Cognitive Work
John M. Flach, Kevin Bennett, Richard J. Jagacinski, Max Mulder, and Rene van Paassen
2. Attention
Christopher Wickens
3. Multitasking
Dario D. Salvucci
4. Judgment and Prediction
Kathleen L. Mosier
5. Situation Awareness
Mica R. Endsley
6. Trust, Reliance, and Compliance
Joachim Meyer and John D. Lee
7. Learning and Retention
Frank E. Ritter, Gordon D. Baxter, Jong W. Kim, and Sowmyalatha Srinivasmurthy
8. Expertise
Walter R. Boot and K. Anders Ericsson
9. Neuroergonomics: Brain-inspired Cognitive Engineering
Raja Parasuraman
10. Communication in Socio-Technology Systems
Daniel G. Morrow and Ute M. Fischer
11. Team Cognition: Coordination across Individuals and Machines
Patricia Bockelman Morrow and Stephen M. Fiore
12. Organizational Design and Cognitive Work
Pascale Carayon and Peter Hoonakker
Part Three: Cognitive Engineering Methods
13. Cognitive Task Analysis
Beth W. Crandall and Robert R. Hoffman
14. Cognitive Work Analysis
Emilie M. Roth and Ann M. Bisantz
15. Decision-Centered Design
Laura G. Militello and Gary Klein
16. Situation Awareness Oriented Design
Mica R. Endsley
17. Cognitive Engineering to Support Successful Aging
Wendy A. Rogers, Marita A. O'Brien, and Arthur D. Fisk
18. Artifact Analysis as a Way to Understand Cognition
Christopher P. Nemeth and Richard I. Cook
19. Evaluation: Does the Cognitive Engineering Effort Do What It Was Envisioned to Do?
Leonard Adelman
20. Microworld Experimentation with Teams
Nancy J. Cooke and Jamie C. Gorman
21. Simulation to Assess Human Responses to Critical Events
L. Jane Easdown, Arna Banerjee, and Mathew B. Weinger
22. Simulation to Assess Safety in Complex Work Environments
Amy R. Pritchett
23. Metrics for Supervisory Control System Evaluation
M.L. Cummings and Birsen Donmez
24. Multi-tasking and Multi-Robot Management
Michael A. Goodrich
25. Human-Machine Cooperation
Jean-Michel Hoc
26. Learning from Failure
Daniel Hummerdal, Alexander Wilhelmsson, and Sidney Dekker
Part Four: Cognitive Engineering Models
27. Computational Cognitive Modeling of Interactive Performance
Michael D. Byrne
28. Computational Process Modeling and Cognitive Stressors: Background and Prospects for Application in Cognitive Engineering
Kevin A. Gluck and Glenn Gunzelmann
29. Modeling and Formal Analysis of Human-Machine Interaction
Asaf Degani, Michael Heymann, and Michael Shafto
30. Queuing and Network Models
Yili Liu
31. Bayesian and Signal Detection Models
Jason S. McCarley and Aaron S. Benjamin
32. Judgment Analysis
Alex Kirlik
33. Modeling Decision Heuristics
Konstantinos V. Katsikopoulos and Gerd Gigerenzer
34. Establishing the Micro-to-Macro Link in Cognitive Engineering: Multilevel Models of Socio-Computer Interaction
Wai-Tat Fu and Peter Pirolli
Part Five: Cognitive Technologies in Engineered Systems
35. Configural and Pictorial Displays
Kevin B. Bennett and John M. Flach
36. Emergence in Organizations and Human Collective Intelligence
Stephen J. Guastello
37. Multimodal Displays: Conceptual Basis, Design Guidance, and Research Needs
Nadine Sarter
38. Ecological Interfaces
Catherine M. Burns
39. Uncertainty Visualization and Related Techniques
Ann M. Bisantz
40. Adaptive Automation
David B. Kaber
41. Distributed Communities of Practice
Anna T. Cianciolo & Karen M. Evans

About the author: 

John D. Lee, Ph.D., is the Emerson Electric professor in the Department of Industrial and Systems Engineering at the University of Wisconsin, Madison and is Director of the Cognitive Systems Laboratory. Alex Kirlik, Ph.D., is a professor in the Departments of Computer Science, Psychology, and Systems Engineering at the University of Illinois at Urbana-Champaign, where he is also member of the Beckman Institute for Advanced Science and Technology.

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