Quantitative Methods and Evaluation
This program applies quantitative and computational methods to the problems of research, assessment, and program evaluation in education. We emphasize the study of measurement and evaluation in addition to applied statistics and computation. Combined with courses in substantive educational issues, students build a context for methodological applications that can inform education policy, practice, and curriculum.
Focus of Study
Our students learn advanced techniques in statistical, measurement, computational, and evaluation methods. At the same time, they develop substantive knowledge in education to apply these methods in the areas of learning theory and policy.
Doctoral candidates develop the capacity to:
teach courses in measurement, evaluation, assessment, psychometrics, research methods, applied statistics, and learning analytics in college/university departments of education;
direct research, data science, assessment development, and evaluation projects for educational and research organizations at the national, state, and local levels;
serve as consultants on research methodology; and
apply advanced techniques in quantitative methods to the study of educational problems.
The four components of this program are (1) psychometrics and assessment, (2) educational statistics, (3) computation, and (4) program evaluation. Students are required to take basic courses in all four components, advanced courses in at least one of the components, and advanced courses in one academic discipline involving substantive educational issues. Coursework can include the areas of education, psychology, economics, sociology, or other relevant areas. We also encourage students to work in evaluation, research, or measurement positions that complement their coursework and fulfill program requirements. Most QME students are employed in an evaluation, research, or measurement capacity in the BEAR Center, with an individual GSE faculty member, or in an R&D/testing/evaluation organization.
We seek applicants with a solid mathematical, statistical, and/or data science background and an interest in education. We also encourage applicants with an education focus who want to develop their methodological skills for quantitative research and evaluation. Ideally, you have some preparation in quantitative methods, but this is not required. Math and statistics experience for entering QME students ranges from high school to master's level in quantitative disciplines. Their academic backgrounds include math, biology, computer science, statistics, business, economics, psychology, and other social science disciplines.
Type of Program (PhD)
The course of study leads to a PhD in Education with an emphasis in Quantitative Measurement and Evaluation.
QME graduates go on to careers in university teaching, as methodological consultants, and directing research, assessment and evaluation projects for R&D organizations that specialize in psychometrics, program evaluation, education research and data analysis. They also work for testing organizations (ETS, CTB/McGraw Hill), consulting firms, as assessment/evaluation specialists at state and regional education offices, and in research positions in the public and private sectors.