Cognitive Systems Engineering
a course presented over five days
Presented by Dr. Gavan Lintern
Please be advised that the "Cognitive Systems Engineering" course title has now been updated to "Human Systems Integration: The Cognitive Element". To visit the current page please click here
Cognitive Systems Engineering is a specialty discipline of systems development that addresses the design of systems containing humans. Drawing on contemporary insights from cognitive, social and organizational psychology, cognitive systems engineers seeks to design systems that are more effective and more robust. The focus is on amplifying the human capability to perform cognitive work by integrating technical functions with the human cognitive processes they need to support and on making that cognitive work more reliable.
Cognitive systems engineers assist with the design of human interfaces, communication systems, training systems, teams and management systems. They employ principles and methods that bear on the design of procedures, processes, training and technology.
Examples of systems that will benefit are military command and control, civil air traffic control, transportation, communication, process control, power generation. power distribution, health care and large-scale project infrastructure.
Who Should Attend This Course?
Anyone directly involved with analysis and design of human-systems functionality or who develops sub-systems with which humans must interact will benefit from this course. Additionally, program managers who hire and task human-systems analysts and designers or who must assess the overall potential of envisioned or existing human-centric systems will benefit, for example:
- All designers of systems that include humans as operators, users, patients, professional staff, or managers
- Human-system integrators
- Specifiers of user interfaces
- Designers of user interfaces
- Designers responsible for usability
- Systems engineers
- Software engineers who implement user requirements
- System safety engineers
- Engineering managers and team leaders
More generally, managers in all technical and non-technical areas will develop profound insights about human individual, team and organisational behaviour that impact the successful operation of any large-scale enterprise.
Those who are uncertain whether they should enrol in this course might consider enrolling in PPI's one-day seminar on this topic, where they will develop a good appreciation of the strategy of cognitive systems engineering and the need for state-of-the-art methods of cognitive analysis and cognitive design in development of safe and effective human-centric engineering solutions.
Training Methods and Materials
The course is delivered primarily in an interactive presentation format with brief participatory exercises. An experiential information-management exercise undertaken early in the first day provides a basis for delegates to develop a situational appreciation of the central ideas. The experiences gained by delegates during that exercise together with documented narratives of counter insurgency operations by US Marines are used throughout the day as source material for collaborative analysis and design activities.
View a Flash movie, delivered by Dr. Lintern, on the relationship between cognitive systems engineering and systems engineering. This movie is a 25-minute summary of the course.
This world-leading course teaches methods of cognitive analysis and cognitive design, and illustrates how they can be applied to enhance human systems effectiveness and safety within system development and acquisition. It also offers an in-depth treatment of the rationale, strategies and benefits of cognitive systems engineering.
Having completed the course, delegates will understand the critical role that state-of-the-art methods of cognitive analysis and cognitive design play in achieving excellent, safe, human-centric engineering solutions. Delegates will be able to apply state-of-the-art methods of Cognitive Systems Engineering at a threshold level of competency. They will be able to identify the role that Cognitive Systems Engineering should play in an engineering project, to identify and evaluate sources of Cognitive Systems Engineering expertise, and to evaluate the work products of Cognitive Systems Engineering.
The course, while standing alone, complements PPI's 5-day Systems Engineering course.
Cognition is a problem area for standards. The human cognitive system is nonlinear and contextually dependent. There is currently insufficient knowledge to write meaningful standards that will guide a designer towards the development of effective cognitive support systems such as, for example, decision support systems and situation awareness support systems. Even where standards name a relevant problem area, such as workload, they offer no meaningful advice beyond the homily that workload should not be excessive. They offer no useful advice about how to assess whether or not workload is excessive or how to design so that it is not. The cognitive systems engineering course deals with this issue.
The engineering professions have many powerful analysis and modeling tools that find valuable service in other disciplines. However, context dependence and nonlinearity were once largely ignored in the engineering disciplines and even now, remain as challenging problems. Cognitive systems engineering has, from its inception and by necessity, confronted context dependence and nonlinearity and, as a result, has developed sets of tools that can address these problems.
Additionally, humans are powerful, multi-function systems. Few engineering tools address the human in any way but those that do, typically treat the human as a user or operator rather than as a functional part of the system. Such an approach fails to take advantage of the unique capabilities that a human can contribute to system performance.
Humans are, indeed, adaptable. The more resourceful members of our species can make anything work for them. However, it does take effort. When the human operators have to struggle with a system to get it to work for them, they have less time and energy for productive work. Furthermore, any system that is difficult to use demands more extensive training, which is an additional cost. Most troubling, clumsy systems induce human error, which can result in huge costs in time, material, and human life.
Those who think this ignore the fact that human errors are typically induced by poor design. Additionally, this sort of attitude assumes implicitly that systems are always well-designed and well maintained and that design engineers can anticipate all contingencies. The extensive record on industrial disasters shows otherwise. Indeed, human adaptability and resourcefulness are strengths, without which, complex modern systems could not work.
Automation is the holy grail of human systems integration. However, humans are inevitably participants as designers, managers and benefactors. The idea of a fully automated system that can deal with all contingencies without human intervention is a science-fiction fantasy. Once we retreat from that ideal and allow humans some interventionist role, the interface between the machine and the human must be configured on the basis of cognitive systems engineering principles. The cognitive systems engineering course deals with this issue and offers a sensible perspective on the way that automation can be used to good effect.
What is the added value for anything? If you add insulation or double-glazed windows to your home to save energy costs, you can calculate the costs and estimate the savings. That is straightforward enough. Large-scale engineering projects are not as straightforward. To assess the added value of cognitive systems engineering, we would have to track and compare projects that used no cognitive systems engineering versus those that used a minimal amount versus those that used a decent amount, and even then, we would have to assess the quality of the cognitive systems engineering that was used. Those sorts of data are not available anywhere. The course does, however, discuss a small set of selected projects in which a modest amount of cognitive systems engineering saved many times its cost. The course also covers incidents in which flawed cognitive performance has resulted in huge costs in terms of loss of productivity and loss of human life.
A well planned cognitive systems engineering effort is more likely to decrease costs and to speed design. The real issue is whether the human interfaces and the cognitive supports are done well or poorly. It will certainly cost more and delay system delivery if they are done poorly at first and then have to be redone.
Cognitive Systems Engineering is a professional discipline that uses formal methods of cognitive analysis and cognitive design to ensure that cognitive work is both efficient and robust. The aim is amplify and extend the human capability to know, perceive, decide, plan, act and collaborate by integrating system functions with the cognitive processes they need to support.
Human Factors Engineering is a professional discipline that uses formal methods of analysis and design to ensure that work is both efficient and robust. Note the similarity of this definition to the one for Cognitive Systems Engineering; the only difference being that all references to cognition have been removed. Human factors engineering is a broader discipline that takes account of physical as well as cognitive work. Alternatively, it could be said that Cognitive Systems Engineering is a sub-discipline of Human Factors Engineering. The terms Ergonomics and Engineering Psychology are sometimes used instead of Human Factors Engineering. Some think of Ergonomics as a discipline that focuses primarily on physical work but that view is not universal. There is no useful distinction between Engineering Psychology and Human Factors Engineering.
Yes, cognitive systems engineering is just one piece of systems engineering but it has an important role to play. A module in the course covers this in extensive detail.
Yes, it is covered there but its role is not well described. Cognitive Systems Engineering can be deployed to good effect in any information-intensive work domain. Health care, military command-and-control and industrial power generation are just three work domains that can benefit from the systematic analysis and design of cognitive work. The focus is on helping workers think more effectively by design of support technologies, work processes or training. In that regard, Cognitive Systems Engineering seems most relevant to the Human Systems Integration domains of Manpower, Training, Human Factors Engineering and Safety as defined in the INCOSE Systems Engineering Handbook (V 3.1, August 2007, Appendix M ).
That is not to belittle the remaining domains of Personnel, Environment, Occupational Health, Habitability and Survivability, or even to claim that Cognitive Systems Engineering could not contribute in those areas, but rather to point out that the current work in the Cognitive Systems Engineering does not currently offer much that is useful for those remaining domains.
As with any engineering or scientific discipline, cognitive systems engineers have their own jargon and tend to be parochial. The treatment of cognitive systems engineering in this course cuts through the jargon to bring a consistent and understandable terminology to the discussion. Once you understand the basic concepts and strategies and can talk about them in generally understandable language, you should be able divert cognitive systems engineers from their parochial concerns and have them pay attention to your concerns.
Cognitive Systems Engineering Course Outline
0. Introduction - What is Cognitive Systems Engineering?
1. Cognitive Systems Engineering in Context
- Systems Boundary Analysis for a selected system
- Develop requirements for the selected system
- Identify human systems integration issues with an emphasis on those related to cognitive work
- Reassessment of cognitive work issues for the selected system
2. Cognitive Task Analysis for Teams
- Team Cognition
- Build a team-referenced Macro-Cognitive cheese wheel
- Applied Cognitive Task Analysis
- Build Cognitive Requirements Table
3. Cognitive Task Analysis for Individual Cognition
- Summary Review of Cognitive Task Analysis for teams
- Critical Decision Method & Naturalistic Decisions
- Knowledge Acquisition, Demonstration of the Critical Decision Method
- Build individual-referenced Macro-Cognitive cheese wheel
- Knowledge Acquisition, Critical Decision Method
- Build Decision Requirements Table
4. Decision Centered Design
- Principles of Decision Centered Design
- Decision Centered Design
- Cognitive Indicators
- Use Cognitive Indicators Evaluate design proposals from previous group exercise
- Summary Review of Decision Centered Design
5. Cognitive Work Analysis, Part 1
- Cognitive Work Analysis, Overview
- Structure and Function, Work Domain Analysis
- Build an Abstraction-Decomposition Space
- Work Organisation
- Build a Contextual Activity Map
6. Cognitive Work Analysis, Part 2
- Cognitive Transformations
- Build a Decision Ladder
- Cognitive Strategies
- Build a strategy diagram and strategy table
- Levels of Cognitive Processing
- Annotate the strategy diagram and strategy table
- Social Transactions
- Build a Social Transactions Matrix and a Transaction Network
7. Cognitive Requirements
- Summary Review of Cognitive Work Analysis
- Overview, compare Cognitive Task Analysis with Cognitive Work Analysis
- Requirements Analysis, review of PPI course SE5D
- Cognitive Requirements Analysis
- Requirements Parsing, review of PPI course SE5D
- Cognitive Requirements Parsing
8. Designing Cognitive Systems & Functional Interfaces
- Cognitive systems
- Design of a cognitive system
- Functional interface
- Design of a functional interface
- Verification and validation, review of PPI course SE5D
- Cognitive performance indicators for verification and validation
- Verification and Validation of Cognitive Solutions
9. Cognitive Systems engineering for the System Life Cycle
- Activities in the System Life Cycle, review of PPI course SE5D
- The Nature and Challenges of Cognitive Work in the System Life Cycle
- Human Systems Integration
- Application of cognitive systems engineering and human system integration to the System Life Cycle
- Cognitive systems engineering summarized
- Tailoring Cognitive systems engineering to specific activities or projects
- Getting the most out of Cognitive systems engineering methods
- Summary Review of Course
- Course Evaluation
- Wrap Up
About the Presenter - Dr. Gavan Lintern
Gavan Lintern earned his B.A. (1969) and M.A. (1971) degrees in experimental psychology from the University of Melbourne, Australia, and his Ph.D. (1978) in Engineering Psychology from the University of Illinois. He has worked in aviation-related human factors research at the Defence Science and Technology Organisation (then known as the Aeronautical Research Laboratories), Melbourne from 1971 to 1974, and in flight simulation research on a US Navy program in Orlando, Florida from 1978 to 1985. He returned to the University of Illinois in 1985 to take up a position as a faculty member at the Institute of Aviation. In 1997 he returned to the Defense Science and Technology Organisation in Melbourne. He returned to the US in 2001 to take up a position with Aptima, Inc in Boston, USA and then moved to General Dynamics Advance Information Systems in Dayton Ohio in 2003.View Full Gavan Lintern Biography
Cognitive Systems Engineering Training Links
Cognitive Systems Engineering Course Schedule
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