Stress is given to practical problems and the intuitive understanding of applied statistics. This course is intended for people carrying out graduate level research in Human Factors. It covers a variety of techniques for recording and analyzing empirical data. Topics to be covered include psychophysical methods, subjective scaling, questionnaires, signal detection theory, information theory, physiological monitoring, spectral analysis, tracking, and manual control modeling. There is no textbook for the course.
Evaluation is based on a series of assignments related to the topics covered in class.
This course covers current topics such as software engineering, hypertext, and information retrieval in applied cognitive science and the design of interfaces in information systems. The focus of this course is on human supervisory control of semi-automated systems, with application to a broad range of systems, including aircraft, automobiles, teleoperated vehicles and robotic arms, manufacturing, medical applications, etc. The emphasis is on the generic concept of human supervisory control. Different human performance. The latter half of the course deals with human factors issues associated with trends in technology, including telepresence, virtual environments, augmented reality, telerobotic control, and display and communication technologies. .