This program is no longer accepting students pending approval by the Southern Association of Colleges and Schools Commission on Colleges.

The curriculum of the M.S. Ed. in RME is structured around three components: (A) a core set of 24 credits (8 courses of 3 credits each) of required coursework covering the fundamentals of research design, measurement, and statistical analysis; (B) 6 credits of elective course-work; and (C) a comprehensive exam occurring upon the completion of the 24 credits of required coursework. The specific details of the curriculum are given below.

Curriculum Requirements

Core Courses24
Quantitative Methods I
Introduction to Research Methods
Quantitative Methods II
Applied Multivariate Statistics
Computer Applications in Educational and Behavioral Science Research
Measurement and Psychometric Theory
Categorical Data Analysis
An Introduction to Structural Equation Modeling for Multivariable Data
Electives 1,26
Select 2 courses from the following for a total of 6 credit hours:
Advanced Individual Study I
Item Response Theory
Introduction to Multilevel Modeling
Meta-Analytic Methods for Research Synthesis
Advanced Topics in Research, Measurement, and Evaluation
Field Experience in Educational Research
Qualitative Methods I
Qualitative Methods II: Case Studies and Grounded Theory
Qualitative Methods II: Interviews and Content Analysis
Comprehensive Exam
Each student must successfully pass a comprehensive exam that covers the content of the core 24 credits. This exam assesses the student’s competency in these core areas of research methodology and use of statistical software, and is based on content that is aligned with the material covered in the core 24 credits.
Total Credit Hours30


The mission of the RME Master’s program is to provide students with the requisite training in the application of statistical and measurement methodologies to be a data analyst, research coordinator, or measurement advisor in a variety of professional (e.g., educational assessment) and/or academic (e.g., doctoral student in a related program) settings.


Student Learning Outcomes

  • Students will demonstrate adequate mastery in the advanced statistical and measurement methodology.
  • Students will demonstrate adequate mastery for conducting statistical analyses and database management using the R program.