Research and Evaluation Methods

Testing and assessment have become very prominent in today's society. They are used in instruction, diagnosis, placement, promotions, credentialing, and selection decisions, and in educational research and evaluation.  Furthermore, the No Child Left Behind legislation has led to a substantial increase in testing in the public school system. Persons trained to develop data collection instruments such as tests, assessments, and questionnaires, to use new models and methods for data collection and analysis (such as item response theory and structural equation models), design sampling frameworks, collect and analyze data, and conduct research and evaluation studies, play vital roles in education. 

The Research and Evaluation Methods Program (REMP) in the School of Education at the University of Massachusetts Amherst offers a graduate level program for the training of persons with specialized skills in the areas of psychometric methods (e.g., item response theory, classical test theory, and scaling), statistics, instrument development, and data analysis.  All students admitted into the Program are provided with full research assistantships and tuition waivers.  The assistantships provide students with opportunities to develop practical skills, and carry out research studies.  Summer internships too are a part of the graduate student training experience, and so the faculty work closely with students to create these important training opportunities.  The Program has close connections with many testing agencies around the country who provide these summer internship experiences.

Program Goals and Emphases

The Research and Evaluation Methods Program emphasizes the training of persons in the areas of (1) psychometric models, methods, and practices, (2) educational statistics, and (3) research and evaluation methods. Graduates of the Program are trained to carry out the design of research and evaluation studies, to apply modern psychometric models and methods (such as those associated with item response theory, structural equation modeling, and performance-based assessment), to develop and validate a wide variety of instruments, and to analyze data in such diverse settings as the public schools, state and federal agencies, industry, the armed services, and medical and allied-health organizations.  Our special focus is on the training of program graduates with both theoretical training as well as a wide range of practical experiences.  Students with such training have no difficulty finding suitable positions upon graduation.

Program Courses

The Research and Evaluation Methods Program offers the following courses:

EDUCATION 509  Fundamentals of Test Construction
EDUCATION 553  Modern Assessment Methods and Practices
EDUCATION 555  Introductions to Statistics & Computer Analysis I
EDUCATION 632  Principles of Testing
EDUCATION 656  Introductions to Statistics & Computer Analysis II
EDUCATION 661  Educational Research Methods
EDUCATION 731  Structural Equation Modeling
EDUCATION 735  Classical Test Models and Practices
EDUCATION 736  Introduction to Item Response Theory
EDUCATION 751  Scaling Methods for the Behavioral Sciences
EDUCATION 756  Advanced Measurement Seminar
EDUCATION 763  Advances in Item Response Theory
EDUCATION 771  Applied Multivariate Analyses I
EDUCATION 772  Applied Multivariate Analyses II
EDUCATION 794O Validity Theory and Validity Applications
EDUCATION 801  Advanced Psychometric Methods I
EDUCATION 803  Psychometric and Statistical Modeling
New Course:           Non-Parametric Statistics

In addition, students regularly take related graduate-level courses in the Schools of Education and Public Health, and Departments of Psychology and Statistics. 

Contact Information

Please visit the REMP site for more information.

Concentration Coordinator: Ronald K. Hambleton (Professor)
Email:

Associated Faculty

Lisa A. Keller (Assistant Professor), Jennifer Randall (Assistant Professor), Stephen G. Sireci (Professor), Craig Wells (Assistant Professor), Ronald K. Hambleton (Professor).