Cognitive Engineering Degree

[Stephani Kapnick]

Researchin cognitive systems engineering and resilience focuses on the human-centered design of complex systems, including work focusing on air traffic flow management, airline operations control, cybersecurity, healthcare, information retrieval and analysis and military planning.

The Ohio State University hosts the oldest university program in Cognitive Systems Engineering (CSE). Since 1982, the Department of Integrated Systems Engineering has offered both undergraduate and graduate concentrations in CSE and, within the Cognitive Systems Engineering Laboratory, has conducted research focused on the intersection of people, technology and work in the design of complex systems.

Cognitive Systems Engineering at OSU provides an integrative perspective linking technology and the insights provided by the cognitive sciences to human-centered design within a broader systems perspective. This includes the design of advanced technological systems to support not only individual work, but also teamwork and larger distributed work systems encompassing coordination and collaboration across multiple roles and organizations.

To accomplish this, we take a highly interdisciplinary approach to the integration of technologies such as computer graphics and multimedia displays, artificial intelligence, data mining, information retrieval, sensing, and robotics with insights provided by the social sciences dealing with decision making and problem solving, perception, learning and memory, attention and group dynamics.

Our contributions to the basic science of CSE are concerned with understanding how new system designs influence the emergence of joint cognitive systems as a result of the adaptive interactions of people and technologies. To ensure that this research focuses on the important leverage points impacted by new approaches to system design, we study the impact of design concepts and innovations on the performances of skilled practitioners in existing and envisioned future systems.

Cognitive engineering is a method of study using cognitive psychology and cognitive neuroscience to design and develop engineering systems to support or improve the cognitive processes of users.[1]

"The idea is that people form a model. You present them with some instruments, tools, like a faucet, electric stove or something like that and demonstrate how it works. They then form in their heads a model that shows how it works inside to help them remember how to use it in the future. It may be a totally erroneous model of what is going on inside the black box."

Don Norman cited principles of cognitive engineering in his 1981 article, "The truth about Unix: The user interface is horrid." Norman criticized the user interface of Unix as being "a disaster for the casual user."[4] However the "casual user" is not the target audience for UNIX and as the Condon quote above indicates, a high level of user interface abstraction leads to cognitive models that may be "totally erroneous."

The Department of Electrical Engineering and Computer Science and the Department of Brain and Cognitive Sciences offer a joint curriculum leading to a Master of Engineering (MEng) in Computation and Cognition that focuses on the emerging field of computational and engineering approaches to brain science, cognition and machine intelligence.

The Master of Engineering in Computation and Cognition is a five- to five-and-a-half-year program in which Course 6-9 students earn a bachelors and master's degree. Students may earn the degree concurrently or sequentially with their undergraduate degree. Students will meet all degree requirements for the 6-9 major and complete an additional 90 units including 24 units of thesis work. The MEng compresses the coursework necessary for a four-year bachelor's and a two-year master's degree into ten or eleven semesters. Students begin fulfilling MEng requirements in their latter semesters as undergraduates.

Students in their junior year or first semester of senior year should submit an application in November or April. The application deadline is the last day of classes for that semester according to the MIT Academic Calendar. Decisions are typically sent out 2-3 weeks after the grade deadline as those grades will be considered in the application review process.

Departmental funding for the MEng program is not guaranteed. However, students may apply for funding from two sources: teaching assistantships and research assistantships. Students will have the opportunity to apply for funding before they begin the MEng program. Full-time TA or RA assistantships pay a monthly stipend, full tuition and health insurance. Students with TAships should expect to work approximately 20 hours a week on teaching. Students may request funding as a research assistant from their thesis supervisor, however, RA support for MEng students can be difficult to secure and advanced planning with research advisors is recommended.

Students with a full-time TAship or RAship may only register for two 12 unit subjects in addition to 12 units of thesis credit and 12 units of assistantship credit. Students holding a half TAship or half RAship may register for an additional class. Because students receive credit for their thesis work as well as TAships and RAships, they are registered for 48 to 60 units each term.

MEng students are only eligible for RAships and TAships during their first three regular semesters (summers are excepted) as a graduate student. If a student has been a graduate TA at least once or has unusual circumstances that have delayed progress on the thesis or classes, the student may request one additional term (a fourth term) of support eligibility.

For more detailed information regarding the cost of attendance, including specific costs for tuition and fees, books and supplies, housing and food as well as transportation, please visit the SFS website.

The Department of Psychology and Human Factors at Michigan Tech offers MS and PhD degrees in Applied Cognitive Science and Human Factors. This research-intensive program unites the expertise of multiple disciplines toward optimizing performance, health, and safety at the interface of humans and technology. Participating scholars include both human experts and built-systems experts, including psychologists, engineers, computer scientists, and usability specialists.

Departmental research pursues practical solutions to real-world problems. The human factors component of the program is concerned with the design and evaluation of technological systems, products, and work processes from the perspective of human characteristics, needs, abilities, and limitations; and applied cognitive science focuses on understanding and enhancing information processing within both human cognition and machines.

There is a growing need for experts trained in human factors. Opportunities are expanding in all employment sectors, including industry, government, and academia. Nonprofits and consulting firms also employ human factors specialists. Common job titles in the area of human factors include:

Specialization courses provide students with a more comprehensive understanding of a research domain and prepare the student to engage in research and apply those findings. Students are required to take 6 credits selected from courses specified as specialization courses. Although the specialization courses offered change each year, courses designated as such in past have included:

Tools courses focus on specific methodologies that may apply across research domains and have broad applications beyond the core statistical competency requirements. Tools course expose students to advanced methodological skills that should apply both within their chosen specialization and others. Tools classes provide training in topics such as advanced cognitive modeling, cognitive task analysis, usability analysis, advanced statistics, survey methods, performance assessment, physiological measurement, or other methods used in ACSHF.

Students are required to take an advanced RCR course within the first year of their enrollment. The university and department offer several courses that may satisfy the RCR requirements. A complete listing can be found at the Graduate School.

This option requires a minimum of 30 credits be earned through coursework. A limited number of research credits may be used with the approval of the advisor, department, and Graduate School. See degree requirements for more information.

Individual programs may have higher standards and students are expected to know their program's requirements. See the Doctor of Philosophy Requirements website for more information about PhD milestones and related timelines.

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Cognitive engineering is a user-centred approach to systems design that emphasises the study of how users think and reason rather than just what they do when using systems or tools to perform tasks such as controlling a process.

The aim of this approach is to develop systems that will have the range of capabilities needed by a human operator to control and manage the variety of demands that the controlled system can present the user.

Cognitive engineering draws from fields such as psychology, human factors, human-computer interaction, and socio-technical systems, using methods such as cognitive task analysis and cognitive work analysis. Cognitive engineers first seek to understand the nature of the problems and identifying how human expertise is applied to these problems. Such expertise can be described in terms of cognitive strategies. Cognitive engineers also seek to model the cognitive work encountered in complex dynamic work domains using methods such as cognitive work analysis. Using this knowledge, designers can then apply principles from representation design (e.g. Bennett & Flach, 2011) to create user interfaces and visual representations that are compatible with the work and strategies that enables users to maximise the application of their expertise in that particular domain.

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