The doctoral program in Industrial/Organizational psychology provides a broad training in both Industrial and Organizational topics, while fostering integration with psychology in general. Likewise, the program follows the scientist/practitioner model that is the hallmark of the discipline. Our goal is to prepare the student for both academic and applied positions, but the program emphasizes the training of scholars, with particular prominence given to research. Both independent and collaborative research projects with faculty members are required.
To these ends, students are expected to complete courses in statistics, research methods, and basic and advanced seminars in I/O and other areas of psychology. These psychology and I/O courses provide substantial training in the psychology of human resource management (i.e., personnel) and organizational behavior. A supervised practicum is encouraged after students complete their comprehensive exams.
Students may pursue personal interests through seminars, other courses in the Department of Psychology, and courses elsewhere in the university, including the College of Business. Students may also specialize in applied quantitative psychology. A master's thesis and doctoral dissertation, both substantive research projects, are required. The master's degree is not intended to be a terminal degree but only a step toward the Ph.D. degree. We do not usually accept students who have a master's degree in I/O or related disciplines from another university, although exceptions may be made on a case-by-case basis. It is anticipated that students will complete the Ph. D. program in four to six years.
For additional information on our I/O program, please visit our website:
- Rodger W. Griffeth, Ph.D. University of South Carolina (1981),
Professor and Byham Chair of Industrial/Organizational Psychology - Research interests include organizational turnover and human resource systems.
- Jeffrey B. Vancouver, Ph.D., Michigan State University (1989),
Professor - Current research involves developing and testing computational models of human/environment interactions, focusing on the role of goals and feedback in motivation and learning.