Program Overview

Overview

The Ph.D. in Research, Measurement, and Evaluation (RME) is a doctoral program designed to provide students with the requisite training in the application of statistical and measurement methodologies to conduct original research in the fields of educational research and measurement methodology. The program aims to equip students with the skills to serve as experts in the areas of research design, data analysis, and measurement.

Program Structure

The curriculum of the Ph.D. in RME is structured around six components:

• A core set of 36 credits (12 courses of 3 credits each) of required coursework covering the fundamentals of research design, measurement, and statistical analysis.
• 6 credits of a research apprenticeship, in which students conduct mentored research under the supervision of RME faculty members.
• 6 credits of field experience in educational research, in which students play active roles in the design and analysis of an applied research or evaluation project.
• The doctoral qualifying exam.
• 12 credits of the doctoral dissertation.
• 6 credits of electives (12 credits for students without a master's degree).

Admission Requirements

Admission to the Ph.D. program in RME is based on the recommendation of the faculty. The admissions decisions are based on faculty review of the following general requirements:

• Achievable scores on the Graduate Record Exam (GRE) taken within the past five years.
• International applicants whose native language is not English or applicants whose degrees are from a non-U.S. University must pass the Test of English as a Foreign Language (TOEFL) or International English Language Testing Systems (IELTS) and the GRE.
• Official transcripts showing completion of a bachelor's degree from an accredited institution and an acceptable undergraduate grade point average (minimum 3.0 undergraduate GPA).
• Three letters of recommendation that address the issues and meet the criteria established by the program being applied to.
• A personal statement that addresses the mission and purpose of the program being applied to.
• Resume.
• Participation in an admissions interview (required by some programs).
• Exhibition of personal and professional experiences and characteristics that are relevant to the profession and/or field and/or degree program for which the application is being submitted.

Curriculum Requirements

The program requires the completion of the following courses:

• Core Courses (36 credits):
  • EPS 700: Quantitative Methods I
  • EPS 701: Introduction to Research Methods
  • EPS 702: Quantitative Methods II
  • EPS 703: Applied Multivariate Statistics
  • EPS 704: Computer Applications in Educational and Behavioral Science Research
  • EPS 705: Measurement and Psychometric Theory
  • EPS 706: Categorical Data Analysis
  • EPS 707: Item Response Theory
  • EPS 708: An Introduction to Structural Equation Modeling for Multivariable Data
  • EPS 709: Introduction to Multilevel Modeling
  • EPS 710: Meta-Analytic Methods for Research Synthesis
  • EPS 711: Advanced Topics in Research, Measurement, and Evaluation
• Research Apprenticeship (6 credits): EPS 799 Advanced Individual Study II
• Field Experience in Educational Research (6 credits): EPS 712 Field Experience in Educational Research
• Doctoral Qualifying Exam
• Dissertation Hours (12 credits): EPS 830 Pre-Candidacy Dissertation Research and EPS 840 Post-Candidacy Dissertation Research
• Electives (6-12 credits): Courses outside the program may be taken for a minimum of 6 credit hours, with examples including EPS 712, EPS 714, EPS 715, EPS 716, and EPS 799.

Sample Plan of Study

A sample plan of study is provided, outlining the course sequence for each year of the program. The actual course sequence may vary depending on previous academic experience and current course offerings.

Mission

The mission of the RME doctoral program is to provide students with the requisite training in the application of statistical and measurement methodologies to conduct original research in the fields of educational research and measurement methodology, and to serve as experts in the areas of research design, data analysis, and measurement.

Student Learning Outcomes

The program aims to achieve the following student learning outcomes:

• Students will demonstrate mastery of computer programming skills required for conducting research projects using computer simulation in R.
• Students will conduct original research in the field of statistical and measurement methodology.
• Students will demonstrate the ability to provide methodological consultation.