What Is A Cognitive Engineer

[Narkis Eatman]

Cognitiveengineering 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."

Research in 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.

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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.

We have found this approach to be very useful. For example, during the FP7 VALCRI research project, we used it to help us define the requirements that drive the design of tools and interfaces for criminal intelligence analysts and investigators to design functions that augment human intelligence. Cognitive engineering methods make it possible to identify the needed complementarity between human cognition and machine algorithms to create better human-machine teams.

The Department of Cognitive Science is committed to transcending theoretical boundaries rooted in traditional disciplines in pursuit of a scientific account of cognition. We promote the study of learning, perception, action, and interaction in the physical, social, and cultural world. Our inter-disciplinary vision draws from a number of disciplines, including anthropology, computer science, ethology, electrical engineering, linguistics, neurology, neurosciences, philosophy, psychology, and sociology in order to contribute to theory and apply what we learn to design.

Steven Dow. Associate Professor, SSRB 100, sp...@ucsd.edu, website. Research: Human-computer interaction, social computing, and design. Understanding and creating tools to support creativity for individuals, groups, and crowds.

Scott Klemmer. Professor, Atkinson 1601B, s...@ucsd.edu, website. Research: Human-computer interaction and design. Empowering more people to design, program, learn, and create: example and data-driven design tools; unearthing ingredients of creative excellence; fostering social learning online.

COGS 10. Cognitive Consequences of Technology (4)

This course examines the interrelationships of cognition and technology from the perspective of cognitive science. We address questions of importance for our increasingly technological society: How does technology shape our minds? How should what we know about our minds shape technology?

COGS 100. Cyborgs Now and in the Future (4)

Covers the theories of situated, distributed, enactive, and embodied cognition. Explains how cyborgs are a natural consequence of our current understanding of embodied minds embedded in culturally shaped niches; how mental systems can be distributed over other people and things. Prerequisites: COGS 1 or COGS 10.

COGS 102A. Cognitive Perspectives (4)

Explores current theoretical frameworks of high-level human cognition that emphasize how we interact with the material, social, and cultural world. Themes include the philosophy and history of cognitive science, the role of artifacts, and how cognition extends beyond the individual. Prerequisites: COGS 1 or COGS 10.

COGS 102B. Cognitive Ethnography (4)

Examines memory, reasoning, language, culture, planning, and interaction directly in everyday, real-world settings. Focuses on ethnographic methods, their history, and their application. The course work includes projects in which students make observations of real-world activity and analyze their cognitive significance. Prerequisites: COGS 102A.

COGS 102C. Cognitive Design Studio (6)

This project-based course focuses on learning and applying the process of human-centered cognitive design. Students work in teams to design and evaluate a prototype application or redesign an existing system. Emphasizes contextual inquiry, user research, ideation, iterative design, and evaluation. Prerequisites: COGS 102B.

COGS 122. Startup Studio (4)

Explores tools and processes for innovating novel business concepts to solve problems involving the interaction between humans and technology. Students will work with an interdisciplinary team to understand unmet user needs and to create a value proposition that balances technical feasibility, financial viability, and desirability. Prerequisites: (DSGN 100 or COGS 187B or COGS 187A or COGS 120 or CSE 170).

COGS 124. HCI Technical Systems Research (4)

In this advanced project-based course, we study the state-of-the-art in research on technical systems for human-computer interaction (HCI). Students will deconstruct the systems described in top-tier HCI papers and work in teams to create novel technical systems of their own. Prerequisites: COGS 120 and COGS 121.

COGS 128. Information Visualization (4)

Frames information visualization as a quintessential cognitive science problem within our interdisciplinary field. Students learn conceptual and practical aspects of creating high-quality, interactive information displays to support a variety of cognitive tasks and then apply them to real-world data. Prerequisites: (COGS 10 or DSGN 1) and COGS 108.

COGS 187B. Practicum in Professional Web Design (4)

This course follows up on the basics of multimedia design taught in Cognitive Science 187A. Students will probe more deeply into selective topics, such as animation, navigation, graphical display of information, and narrative coherence. Prerequisites: COGS 187A or consent of instructor.

DSGN 118. Design for Future Creativity and Productivity (4)

This course covers fundamentals of the design of creativity support tools for various types of digital content, including images, videos, animations, information visualization, augmented/mixed/virtual reality. We will also explore how novel interaction techniques, such as gestural interaction, speech input, and artificial intelligence can be used to support people's creativity and productivity. Prerequisites: (COGS 18 or CSE 11 or CSE 8B or DSC 30) and (COGS 1 or COGS 187A or DSGN 1).

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