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.
Research, Educational Measurement, and Psychometrics doctoral students are required to take 42 class credits and 10 dissertation credits. Listed below are the required courses, and courses that are “highly recommended” (♦) for students who want to emphasize a more statistically-oriented track or a more policy-oriented track. Students do not need to choose statistics track or policy track. Rather, these are just suggestions to guide student/faculty discussion to put together each student’s program of study.
* denotes prerequisite: EDUC 555
** denotes prerequisite: EDUC 656
*** denotes perquisite: EDUC 771
**** denotes prerequisite: EDUC 736
|EDUC 661||Educational Research Methods I||3|
|EDUC 656*||Introduction to Statistics and Computer Analysis II||3|
|Fundamentals of Test Construction
Principles of Educational & Psychological Testing
|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|
|EDUC 731**||Structural Equation Modeling||3|
|Diversity course reqirement||3|
|Qualitative course requirement||3|
Suggested for Statistics Track
|EDUC 772***||Applied Multivariate Statistics II (♦)||3|
|EDUC 794E****||Advances in Item Response Theory: IRT II (♦)||3|
|EDUC 891N||Advanced Psychometric Methods I: Classical Test Theory II (♦)||3|
|EDUC 747||Programming for Psychometrics and Statistical Modeling (♦)||3|
|EDUC 756||Advanced Measurement Seminar (♦)||3|
|EDUC 637**||Nonparametric Statistical Analysis in Education & Psychology||3|
|EDUC 650||Regression Analysis||3|
|EDUC 751||Scaling Methods for Behavioral Science||3|
|EDUC 707||Generalizability Theory: Principles and Applications||3|
|EDUC 727||Scale and Instrument Development||3|
|EDUC 757||Advanced Statistical Theory Using R||3|
Suggested for Policy Track
|EDUC||Educational Assessment Policy||3|
|EDUC 633||Education and Public Policy||3|
|Fundamentals of Test Construction (♦)
Principles of Educational & Psychological Testing (♦)
Classroom Assessment (♦)
|EDUC 727||Scale and Instrument Development (♦)||3|
|EDUC 756||Advanced Measurement Seminar (♦)||3|
|EDUC 753||Professional Seminar in Educational Research and Evaluation Methods||3|
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.
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
Theory of mental tests beginning with the classical test theory model and including such topics as reliability, validity, item analysis and test development.
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.
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.
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.
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.
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.
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:
- 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.
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 Ed.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.
Applications to the Assessment and Policy Studies master's program can be submitted through the Graduate School.
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:
- 3 letters of recommendation
- Cover Letter outlining interest in the field and previous experience
- GRE Scores
- TOEFL (if first language is not English)
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.
The application for admission and specific information on graduate application processes is located on the University of Massachusetts Graduate School website here.
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