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Doctoral students in research, educational measurement, and psychometrics focus on educational test development, psychometric models, methods, and practices, educational statistics, and research and evaluation methods. Through the coursework, they develop depth and breath in the areas of response theory, classical test theory, structural equation modeling, test development and validation, scaling methods, statistical courses (such as multivariate statistics), non-parametric methods, and regression analysis, and simulation methods.
We provide extensive support for students publishing their work and presenting at regional and national professional meetings and offer seminars to introduce them to leaders in the assessment field. Our students also benefit from interactions with visiting faculty and students from across the world. Visit our Center for Educational Assessment to see the amazing research our faculty and students do! All full-time students accepted into the academic program receive full financial support including stipend, tuition, and medical insurance for three years.
Graduates have accepted research and teaching positions at universities and colleges, research positions with projects at universities and private foundations, and positions in research organizations, the armed services, government and credentialing agencies, medical boards, school systems, educational consulting firms, and private industry. Among many other places, our graduates have held positions at universities in California, Florida, Kansas, and Massachusetts, as well as Educational Testing Service, the National Board of Medical Examiners, the American Institute of Certified Public Accountants, the Connecticut, Maine, and New Jersey state departments of education, and the Graduate Management Admissions Council.
Course of Study
Research, Educational Measurement, and Psychometrics doctoral students are required to take 42 class credits and 10 dissertation credits.
Prerequisites:
* denotes prerequisite: EDUC 555
** denotes prerequisite: EDUC 656
*** denotes prerequisite: EDUC 771
**** denotes prerequisite: EDUC 736
Required Courses
| Course | Description | Credits |
|---|---|---|
| Core Required Courses: 12 | 36 | |
|
EDUC 632A |
Fundamentals of Test Construction or Principles of Educational & Psychological Testing or Classroom Assessment |
3 |
| EDUC 656* | Introduction to Statistics and Computer Analysis II | 3 |
| EDUC 661 or EDUC 664 |
Educational Research Methods I or Group Design |
3 |
| EDUC 731** | Structural Equation Modeling | 3 |
| EDUC 735 | Advanced Theory of Practice and Testing I: Classical Test Theory I | 3 |
| EDUC 736* | Advanced Theory of Practice and Testing II: IRT I | 3 |
| EDUC 771** | Applied Multivariate Statistics I | 3 |
| EDUC 821 | Advanced Validity Theory and Test Validation | 3 |
| Diversity Course (Specific) | 3 | |
| Qualitative Course (Specific) | 3 | |
| Elective Courses: 4 | 12 | |
| EDUC 625 | Classroom Assessment | 3 |
| EDUC 632 | Principles of Educational and Psychological Testing | 3 |
| EDUC 632A | Test Construction | 3 |
| EDUC 633 | Education and Public Policy | 3 |
| EDUC 637** | Nonparametric Statistical Analysis in Education and Psychology** | 3 |
| EDUC 650 | Regression Analysis | 3 |
| EDUC 707 | Generalizability Theory: Principles and Applictions | 3 |
| EDUC 727 | Scale Instrument Development | 3 |
| EDUC 751 | Scaling Models for Behavioral Sciences | 3 |
| EDUC 756 | Advanced Measurement Seminar | 3 |
| EDUC 794E**** | Advances in Item Measurement Seminar | 3 |
| EDUC 881 | Comparative Education | 3 |
| EDUC 871 | Design and Evaluation of Education Programs | 3 |
| EDUC 891N | Advanced Psychometric Methods I | 3 |
| Electives from Psychology or Statistics (or other departments and concentrations) |
3 | |
| Dissertation Credits | 10 | |
| Minimum Total Credits | 52 |
Summer internships are a required part of the graduate student training experience, and faculty work closely with students to create these important opportunities for students.
EDUC 632A Fundamentals of Test Construction
Enables students to construct educational assessments using a variety of item formats such as multiple-choice and performance-based items. The entire development process, including item writing and item review are covered
EDUC 735 Advanced Theory of Practice and Testing I
Theory of mental tests beginning with the classical test theory model and including such topics as reliability, validity, item analysis and test development.
EDUC 736 Advanced Theory of Practice and Testing II
Introduction to modern test theory, often called item response theory. Topics include shortcomings of classical models and methods, basic concepts and item response theory models, parameter estimation, goodness of fit procedures, and specific applications including test development, detection of biased test items, test score equating, large-scale assessment, score reporting, and computer-adaptive testing. Prerequisite: Educ 735.
EDUC 771 Applied Multivariate Statistics I
Matrix algebra, nature of multivariate distributions, tests of hypothesis on mean vectors, regression analysis including multivariate regression models, correlation techniques, application to issues in educational research. Computers used extensively to analyze data taken from existing research studies.
EDUC 821 Advanced Validity Theory and Test Validation
This course presents and discusses the major theories regarding the concept of "test validity" and the major practices involved in test validation. The skills taught in this course will enable students to be experts in testing tests.
EDUC 637 Nonparametric Statistical Analysis in Education & Psychology
In this course, we examine inferential procedures that do not assume normality. Procedures are introduced that allow analysis in designs that involve more than two categorical variables or that involve repeated, unordered qualitative variables. Prerequisites: EDUC 555 and 656.
EDUC 727 Scale and Instrument Development
An introduction to the major steps necessary for the construction of new measures. This course will provide a framework based on modern measurement theory (item response theory with a focus on the Rasch models) for the construction and evaluation of new measures and scales.
EDUC 751 Scaling Models for Behavioral Science
The purpose of this course is to introduce and explore scaling methods essential for research in the social sciences. This course covers techniques of unidimensional scaling, multidimensional scaling, and classification. Prerequisite: Students should have basic understanding of univariate and multivariate statistics.
Social Justice Requirement
The purpose of the Social Justice (SJ) requirement is to provide a learning opportunity to critically interrogate one's self, group, and historically constructed social identities, and each identity's location in relationship to power. As students navigate their doctoral educations, SJ courses are intended to aid students- through knowledge, awareness, and skills (analytical, communicative, leadership)- in recognizing the ways in which power, oppression and difference (POD) create injustice interpersonally and institutionally. This requirement is designed to provide students with the experiences needed to meet the following learning outcomes:
Students will
- Critically engage with theories of oppression, privilege and social justice; and understand how all theory shapes knowledge production.
- Critically analyze their own perspectives and identities, develop an awareness of implicit biases, and understand how these perspectives and biases have historically been shaped by power relations within social and institutional contexts.
- Gain knowledge of structural and cultural forces (both historical and contemporary) that shape discrimination based on factors such as race, ethnicity, language, religion, class, ability, nationality, sexuality or gender.
- Demonstrate the capacity to engage in active listening (voicing, speaking, & inquiring into each other's perspectives) while being mindful of the ways that power, privilege, oppression, and difference shape meaningful communication.
- Explore and construct questions that critique dominant narratives to develop a complex understanding of the world.
- Demonstrate an understanding of historical legacies that bridge past and contemporary manifestations of power, oppression, and difference.
For a list for currently acceptable Social Justice courses that meet the Research, Educational Measurement, and Psychometrics PhD degree requirement, please contact the concentration coordinator.
Research Methods Courses
Students are required to take four research methods courses. Two of those four courses must be quantitative and one must be a (qualitative) research methods course. View our Research Methods Courses page for more information.
Comprehensive Exams
The purpose of the comprehensive exam is to ensure students have sufficient knowledge of the fields of research design, educational statistics, and psychometric methods, to proceed toward candidacy for the Ph.D. degree. Successful completion of the Comprehensive Exam is an important milestone for Psychometrics students because it indicates mastery of the important knowledge and skills taught in our concentration and that are important for success in the fields of educational research and psychometrics. Students typically take their comprehensive exam during the spring of their third year, and the exam consists of both written and oral sections. View our Student Resources page for exam policies, content, and sample questions.
Admissions
Applications to the Assessment and Policy Studies master's program can be submitted through the Graduate School.
Admissions Requirements
Applications for admittance to the Research, Educational Measurement, and Psychometrics master’s and doctoral programs are due by January 2nd. You will need the following in order to apply:
- Transcripts
- 3 letters of recommendation
- Cover Letter outlining interest in the field and previous experience
- GRE Scores - *waived for fall 2023 applicants, due to COVID-19*
- English Proficiency Language Test (if first language is not English) - information about accepted tests and minimum scores required is available on the Graduate School website
Diversity among student backgrounds and experiences is desired (see Diversity and Inclusion Statement here). To this end, REMP faculty consider the totality of the applicants as reflected in their application materials. Your cover letter is an opportunity for you to convey to the faculty a more holistic view of your strengths and potential contributions to the program. Similarly, letters of recommendation are reviewed carefully for each applicant. There are no minimum GRE cut scores for admission to REMP. We encourage all students, particularly those from underrepresented and historically marginalized groups, to apply regardless of test scores.
Application Process
The application for admission and specific information on graduate application processes is located on the University of Massachusetts Graduate School website.
University of Massachusetts Anti-Discrimination Statement
The University prohibits unlawful discrimination, harassment (including sexual harassment), and retaliation against anyone based on religion or religious belief, color, race, marital status, veteran or military status, age, sex, gender identity or expression, sexual orientation, national origin, ethnicity, disability, genetic information, or any other legally protected class, in education, admission, access to or treatment in, its programs, services, benefits, activities, and terms and conditions of employment at the University.
Contact
Please address specific inquiries about admission, financial support, and the program to Jennie Southgate, jsouthgate@educ.umass.edu.
The Center for Educational Assessment (CEA) conducts research and provides training in the areas of psychometrics, research methods, and educational statistics to promote fair, useful, and efficient educational assessment practices. The Center provides technical expertise in areas such as test development, item response theory applications, equating, standard setting, test selection and evaluation, and program evaluation.
