In the attempt to make organizations more efficient with their resources, industrial organizational (I-O) psychology uses a variety of methods and techniques to make organizations perform at an optimal level. Most research within the field is centered around personnel selection, but recognizing there are many other topics within this field such as: academic admissions, judgments in hiring, biodata and personality in the workplace, and many more themes.
Purpose
My colleagues and I focus on understanding what makes people successful at school and at work. To date, my most visible research has examined the predictive power of a number of standardized tests that are used for admissions decisions. My colleagues and I have conducted large-scale meta-analyses of the validity of the Graduate Record Examination (GRE), the Miller Analogies Test (MAT), the Graduate Management Admission Test (GMAT), the Pharmacy College Admissions Test (PCAT) and the SAT, as well as high school and college grade point averages. We have investigated the validity of these tests for different aspects of academic performance in an effort to examine performance beyond grade point averages. We have found overwhelming evidence that these measures are related to important aspects of student success. Our current research is attempting to expand our understanding of non-cognitive predictors of student success including study skills, personality, and interests.
Our research on predictors is supported by efforts to create taxonomies of the major dimensions of student performance in college and graduate school. Performance in graduate school or on the job is not one thing. Performance is the function of many complex sets of behaviors. A more complete understanding of what constitutes effective work or school performance can only be obtained by measuring different aspects of performance. Creating broad taxonomies of performance behaviors is a good place to start understanding performance and the individual difference characteristics that determine effective performance.