Human Systems Engineering – User Experience (BS)

Introduces the biological basis of human behavior and implications for human systems engineering. Structure and function of the nervous system as well as the behavioral effects of the physiological processes outside the brain (for example, hormones secreted by glands). Biological processes involved in many aspects of our behavior such as eating, sleeping, sexual behavior, emotional responses, sensory perception, learning and memory, language and cognitive functions, mental illness and drug abuses. Introduces a wide range of techniques and methods used to investigate the biological foundations of behavior. Prepares students for advanced courses in neuroscience, psychology or related fields.

Covers social behaviors, social cognition and emotion critical for engineered systems that interact with humans (artificial intelligence, robots). Students learn how human beings behave, think and feel in daily social situations and think about how that information can be used to create effective human systems.

Reviews human systems integration (HSI), which is basically systems engineering from a human-centered perspective. Research, theory and methodological approach as applied to a variety of systems ranging from transportation systems to medical and military systems. Discusses handbook chapters and specific examples of human systems integration.

Basic methods of exploratory data analysis (including graphics) and statistical computing methods, including a detailed look at hypothesis testing, effect size and power analysis, as well as some methods for dealing with categorical and discrete data. Introduces both correlation/regression and analysis of variance (ANOVA), as well as common statistical software.

Introduces the basics of research methodology as applied in human systems engineering. Quantitative and experimental design from an applied perspective. Guided study of the process of conducting research within human systems engineering. Project topics range from research question generation and literature review to reporting of results.

Human cognition and how it bears on the design of technological and social systems. Although focuses on applications, requires student to delve into the basic literature that informs these applications and produce a literature review that draws on both applied and theoretical work. Many weeks involve a hands-on experience with a method or technique, and weekly quizzes emphasize critical thinking about these examples.

Theories, methods, and findings concerning the usability of computer systems and the design of effective user interfaces.

Reviews basics of qualitative research with applications to human systems engineering. Covers fundamental concepts of reliability and validity, and considers best practices in survey, questionnaire, interview and observation methods. Introduces and applies content analysis and grounded theory approaches for analyzing and interpreting qualitative data (e.g., interview transcripts and open-ended survey responses). All concepts are taught with an applied focus and real-world examples.

Statistical methods commonly used in human systems engineering research. Emphasizes (1) connecting research designs and statistical analysis, (2) interpreting and breaking down significant effects, (3) addressing practical problems associated with doing research in applied contexts, (4) using statistical methods to understand the connection between variables in a complex system, and (5) the use of statistical software. Primarily focuses on analysis of variance (ANOVA) but introduces other techniques (including mediation analysis, structural equation modeling and cluster analysis). Recommended for preparation for both graduate study and careers in related industry.

Introduces basic principles, methods and theories of psychology and applications to engineering problems relevant to human systems. Gives particular attention to the intersection of psychology and engineering. Students learn brain anatomy and physiology, sensation and perception, cognition, social systems and research methods so that they are able to design systems consistent with human capabilities and limitations.

In-depth exploration of methods by which humans receive and interpret information from the world by vision, audition, taste, smell, touch and movement. Emphasizes the integration of behavioral and neural research with potential applications to engineering practice. Topics cover a wide range from the biological basis of sensory information processing to the behavioral aspects of perception, and to the applications of perceptual theories to disciplines like computer vision, display technologies, graphic design and sound processing. Solid foundation for further coursework and research in neuroscience or psychology; students also gain knowledge that could be useful in various professions.