The Educational Psychology (EPSY) PhD with a concentration in Research Methodology, Measurement, and Statistics (RMS) is designed to prepare scholars and researchers in both quantitative and qualitative methodology that prepares professional data scientists in education and psychology.
How is the Program Structured?
Students are initially exposed to the same foundational courses in intermediate statistics, research methods, and Qualitative inquiry that all other doctoral students acquire in the College of Education. A copy of our degree plan is here.
Your PhD will be in “Educational Psychology” with a concentration in Research Methodology, Measurement, and Statistics.
All Educational Psychology doctoral students are exposed to foundational courses in Educational Psychology (Learning Theory, Foundations of Educational Psychology, and Human Development, Research Methods, and Intermediate Statistics) as part of the Core portion of the EPSY PhD, similar to doctoral students in the other two concentrations (Human Development and Family Science, and Gifted/Talented).
Beyond these foundational experiences, RMS students will receive more advanced training, primarily in quantitative methods, however additional coursework includes advanced data analysis in qualitative investigations. Our goal is for students to pursue careers in data analytics and data science for education and psychology. Entry to advanced training begins with a course in Multiple Regression. A two-course sequence is usually required in measurement and psychometrics, and students also receive additional training in latent variable modeling through coursework in multivariate statistics and structural equation models. Training is provided in courses such as Multi-level Modeling, Simulation and the use of advanced software (R) for statistical analysis. Coursework is followed by a comprehensive examination prior to completion of a dissertation under a faculty member of the RMS program.
Is there a deadline to apply?
Applications should be complete by March 30th to begin the program in Fall.
For the current year, the application deadline has been extended, as we are presently accepting applications.
How do I enter the program?
Admission to the program occurs through a standard application process, and once admitted students are assigned an initial advisor to guide them through coursework. We encourage you to reach out to the RMS faculty through email with any additional questions you may have or to let us know about your areas of interest or to set up a virtual meeting to discuss your interests (see faculty profiles below for contact information). These meetings and communication can be important, as faculty may advocate for you in the department admissions process.
After you are admitted, you will be assigned a faculty member as an advisor. It is possible to change the initial advisor as students become more familiar with their research interests and how those interests align with faculty.
What is involved in the application/admissions process?
Students are admitted to the RMS program through a departmental process.
First, complete all application materials for the Toulouse Graduate School, and for the Department.
After all your application materials are complete, the Department’s Doctoral Policies Committee will review your application and ask for input from RMS faculty to make their decision about your application.
How does the committee decide?
The Doctoral Policies Committee considers each applicant wholistically. Your written statement in your application should say a lot about who you are, and why you are interested in the RMS program, as well as why you feel the program content is relevant to your interests, and if possible, how you think the program would benefit you or your career interests.
There is no minimum GRE score required. We generally like to see GRE scores around the 50th percentile – particularly on the quantitative portion, but many successful students have been admitted with lower GRE scores based on aptitude, experience, and interest in the program (this can be communicated in your written statement or through recommendation letters).
Because the program is focused on research, we are looking for students that have potential and interest in doing research in education and psychology; as well as contributing to research methods – how research is conducted – methodologically.
Your recommendation letters should be from individuals that can speak to your potential as a researcher. Letters from experienced researchers/scholars are usually preferred, as these are the individuals that can speak to your suitability and potential.
The committee strongly considers input from RMS faculty, so reaching out and making contact can be very beneficial in the decision-making process. If you like, try setting up a visit to explore the department and program further.
How much math/statistics background do I need?
We take students with a sound background in Algebra. You do not need to have an abundance of statistics training to enter the program, as this can be provided in the foundational coursework. If you have a desire and interest in learning statistics, that is really all that is required. Often, students with applied research interests find that they are some of the most adept at bridging the gap between applied researchers and methodological investigations that support applied researchers to do what they do better.
That said, it is possible for students to enter the program with considerable training in statistics or mathematics and pursue a more advanced course of study. Some students will benefit from courses in probability provided by the Math department.
Is it necessary for me to have a research agenda or know what I want to do before I start the program?
Many, if not most students, enter the program with no research agenda, but an interest in learning methods that will improve understanding about learning, education, or educational programs. Some students are more interested in psychology, but most students begin to develop new interests after being exposed to the Core portion of the Educational Psychology PhD program as they interact with faculty and other students, including students in other concentrations. Some students opt to pursue interests in areas they would never have known about until their exposure to the program, for example, we have some students that have gone on to pursue successful careers as psychometricians. Prior to their exposure to the program, they didn’t have an idea about that area of work or what it entails.
What options are available for the RMS PhD program?
We have four different ways that students can participate in the program.
(1) Students may enter the program with a Master’s degree and complete the program with 66 hours (minimum) of coursework which includes a dissertation. This is the traditional route.
(2) Students may enter the program with a Bachelor’s degree and complete the program with 78 hours (minimum) of coursework which includes a dissertation. This is referred to as our “passthrough” program, as students do not earn a Master’s degree and pass directly to a terminal doctorate degree. This is becoming a popular option for many students.
(3) Students pursuing a PhD in other programs at UNT may receive a Minor in RMS that appears on your transcript. This option involves coursework only.
(4) PhD students at UNT can opt to obtain a 2nd PhD in RMS with 36 hours beyond the first PhD.
How long does it take to finish?
For students that wish to pursue the program full time, it is possible to complete the coursework in approximately three years (depending on course sequencing and timing related to when the student begins).
For many students that have full-time jobs, it may take longer to complete the program. This is perfectly acceptable, as long as students adhere to the graduate school requirements. All work to be credited toward the doctoral degree beyond the master’s degree must be completed within a period of 8 years from the date doctoral credit is first earned.
We encourage applications from part-time, working students. All course instruction is provided in the evening hours since UNT serves a large local DFW population, and many students opt to pursue the program in addition to holding a full-time job elsewhere. Flexibility in course
scheduling is provided to accelerate students through the program or permit students to take courses at a pace that allows the program to fit with busy family and/or work lives.
What are the options for attending full-time vs. part-time?
Our doctoral program is designed to accommodate full time and part-time students. Full-time students benefit from the opportunity to work in the department as Graduate Assistants on a paid assistantship that includes additional tuition support. This makes obtaining a doctoral degree very attractive from a cost perspective. In addition, full-time students, through their assistantships, work closely with faculty in the department and have access to mentorship in teaching and scholarship. However, some students have good-paying full-time jobs in the local area or need to support a family while obtaining their degree. All coursework in the program is offered in the evening, and students can take a reduced course load over a longer period of time to obtain their degree if they choose.
For full-time students, there are competitive opportunities for Graduate Assistantships (Research or Teaching). Assistantships usually require students to work 20 hours per week and provide tuition compensation in addition to a stipend for the work performed. These positions allow students to gain additional experience working alongside faculty on research projects, providing consulting in the College’s Office of Research Consulting (ORC), on grant-related activities, and experience in teaching.
What can I do when I complete the degree?
This preparation supplies most of the necessary skills for pursuing an academic career, although approximately half of our graduates opt to pursue careers in corporations conducting research or in development (such as in test development) or in school districts directing assessment, evaluation, or accountability functions.
Applying to a graduate program at UNT is a two-step process.
Second, you will need to complete a departmental application. The departmental application for doctoral students includes three recommendation letters (signed/on letterhead), a resume/CV, and a personal statement. You can view the details of these requirements at http://www.coe.unt.edu/educational-psychology/graduate-admissions. Our department requires all items and scores within two months of the submitted application.
1. 36 hour minimum beyond the 1st PhD at UNT. Plus 9 hour EPSY Core courses if needed (5550, 6040, 5123).
2. If students have had Core equivalents (see below), these hours do not need to be made up.
3. If students have had RMS concentration area equivalents, these hours do need to be made up to get to the 36 hour minimum. It is up to the advisor and student to determine whether the courses should be retaken in our program (e.g., to deepen understanding or to learn from a different perspective in an area) or whether other RMS-related courses should be substituted (e.g., to expand content and experience).
4. No courses that are included on another degree plan can be applied to the 2nd PhD degree plan. Courses that are not on another degree plan can be transferred in and counted for equivalents as determined by the advisor. No more than 9 hours of RMS-related courses that are not included on another degree plan can be transferred in.
5. Students must take and pass the written and oral portions of the qualifying exam like all RMS students. This exam can be taken within the last 9 hours in the final semester of coursework.
6. Students are expected to engage in research with faculty and other graduate students and contribute to the academic culture of the program and department.
Degree Plan
Leveling and Core Courses, if Needed: Required leveling (9 hours), only if not previously taken. These do not count toward the 36 hour minimum and do not need to be taken if students have had equivalents, per advisor approval. It is generally assumed that students will have this content in the first PhD.
5210 – educational statistics (introductory; prerequisite to 6010)
6010 – statistics for educational research (intermediate)
6020 – research methods in education
Core courses (9 hours). These do not need to be taken if students have had equivalents, per advisor approval.
5550 – learning theories in education
6040 – foundations of educational psychology
5123 – human development across the lifespan
Required Courses: Concentration area (27 hours)
6005 – statistical theory and simulation
6210 – multiple regression and related methods
6220 – classical and modern measurement theory
6230 – theory and application of hierarchical linear modeling
6240 – technology in research
6250 – item response theory
6270 – structural equation modeling
6280 – qualitative research in education
6290 – multivariate statistics
Dissertation (9 hours)
6950 – dissertation
The doctoral program in educational psychology requires a minimum of 63 (78 hours if admitted without a Master’s degree) hours of course work and research experience.
Those entering the program without a master’s degree are expected to fulfill the following requirements, plus two core courses in the MS with a major in educational psychology, and a minimum of three additional graduate-level courses with the advisor’s approval.
Note: The following requirements are for students entering the program having completed a related master’s degree.
Minor in Research Methodology, Measurement, and Statistics (RMS)
Prerequisites
Beginning the minor assumes students have taken the equivalents of EPSY 6010 and 6020 in their own program or elsewhere.
12 hour minor
Required:
EPSY 6210 – Multiple Regression and Related Methods
EPSY 6290 – Multivariate Statistics
And select 6 hours from the following:
EPSY 6005 – Statistical Theory and Simulation
EPSY 6220 – Classical and Modern Measurement Theory
EPSY 6230 – Theory and Application of Hierarchical Linear Modeling
EPSY 6250 – Item Response Theory
EPSY 6270 – Structural Equation Modeling
All courses are 3 hours.
Substitutions
All courses are to be taken through the Department of Educational Psychology.
Transcript
The minor will officially appear on students’ transcripts if the minor is designated on their degree plans and posting of the minor is requested of the Registrar’s office.
Dr. Chen engages in doing research and teaching in the area of quantitative methods. Her primary quantitative research interests include Growth Mixture Modeling (GMM), Hierarchical Linear Modeling (HLM), and Structural Equation Modeling (SEM), and the application of these methods in longitudinal data analyses and mediation analysis. She is also interested in the application of these methods in educational and family-based data. Her interested substantive areas include children’s psychosocial functioning and self-regulation, school-based prevention, teacher-student relationship and peer relations, and the intersection of family and cultural contexts in shaping Asian American adolescent development.
Robin’s background is a bit of winding road, but one he considers divinely guided by God. His early background was in youth ministry with undergraduate majors in Biblical studies and psychology from Evangel University (Springfield, MO). This evolved into a focus on counseling and masters degrees in general and clinical psychology, and eventually LPC licensure. Robin then earned a PhD in educational psychology at Texas A&M University, and this led to his current research and teaching focus on statistics, measurement, and research methodology. The LPC licensure was latter allowed to lapse due to a focus on methodology, but Robin still periodically works with counseling applications. More recently, Robin has completed a doctor of ministry (DMin) degree from Liberty University with a cognate in expository preaching and teaching. Robin is married to an incredible woman and has two awesome, young adult kids. In his spare time, Robin enjoys outdoor activities and being involved at Midway Church.
Darrell Hull received his PhD in Educational Psychology from Baylor University. He has been involved in STEM and STEM education for more than 20 years, as principal investigator for several NSF and U.S. Department of Education programs. During the last 10 years he has conducted research on positive youth development in the Caribbean, working in the Bahamas, Trinidad and Tobago, Jamaica, and Belize were he has directed randomized trial studies and quasi-experimental trials focused on adolescents. Based on his work with Item Response Theory and Generalizability Theory, Dr. Hull teaches measurement in the Educational Research PhD program and is a frequent psychometric consultant to assessment organizations in the DFW area.
Jihyun Lee is an assistant professor in the Research, Measurement and Statistics program in the Department of Educational Psychology at the University of North Texas. She earned her Ph.D. in 2022 in the Quantitative Methods program in the Educational Psychology department at the University of Texas at Austin.
Her research has been anchored in the overarching question, "How can we conduct valid quantitative research to investigate psychological and behavioral phenomena?" To address this question, she studies quantitative methods and statistical modeling used for research within the behavioral and social sciences, including education and psychology. Her specialized work in quantitative methods includes meta-analysis, missing data analysis, and latent variable modeling.
In addition, she has actively collaborated with applied researchers in various research fields. Her work is intended to further enhance the quantitative research that investigates educational, psychological, clinical, and social issues.
Nicole Sankofa is an Assistant Professor of Educational Psychology at the University of North Texas. She graduated from Spelman College with a double major in Psychology and Women's Studies and earned a PhD in Educational Psychology from The Ohio State University. She uses a transformativist paradigm and qualitative methodologies to examine the role of self-determination on adolescent/adult development, psychological well-being, and academic outcomes across school, work, and juvenile detention settings. Dr. Sankofa is the course steward for the sequence of qualitative doctoral courses in the Department of Educational Psychology.
James Uanhoro is an assistant professor in the Research, Measurement and Statistics program in the Department of Educational Psychology at the University of North Texas. He received his Ph.D. in 2021 in the Quantitative, Research, Evaluation and Measurement program in the Department of Educational Studies at Ohio State University.
Uanhoro's work focuses on the similarities between multilevel regression models and commonplace measurement models — structural equation models, classical test theory and item response models. Specifically, he attempts to leverage insights from both groups of models to better understand patterns in complex data analysis contexts. Underlying much of this work is Bayesian data analysis, which he also applies in research collaborations with social scientists. Finally, James has an interest in building easy-to-use statistical tools that allow researchers better understand patterns in their data, and better communicate insights from their studies.
