PhD MESA Focus Area Faculty

The following faculty in the Department of Educational Psychology teach most of the MESA courses. In addition to the courses taught within the MESA program, students in MESA PhD program can take MESA related courses outside the Department of Educational Psychology, even outside the College of Education. Please check with your advisor before enrolling to make sure the credits will be acceptable to transfer to the MESA PhD.

Ting Dai, PhD

Assistant Professor of Educational Psychology

Ting Dai is an Assistant Professor in the Department of Educational Psychology.  Her research centers on measurement of student motivation, epistemic cognition, and achievement in STEM.  Dr. Dai also studies methodological issues with educational and psychological research, such as validity and measurement invariance of motivational measures, missing data, and measurement of treatment effects.  She is co-Principal Investigator on funded research projects by the Institute of Education Sciences and the National Institutes of Health.  Her work is published in a number of peer-reviewed journals, and she is on the editorial board of the Journal of Experimental Education.  Dr. Dai teaches courses in statistics (e.g., Structural Equation Modeling) and assessment.


PhD Educational Psychology, Temple University
MEd Educational Psychology, Temple University

MESA Courses

  • Assessment for Measurement Professionals
  • Special Topics in Educational Psychology: Structural Equation Modeling

George Karabatsos, PhD

George Karabatsos Headshot

Professor of Educational Psychology

George Karabatsos is a Professor of Educational Psychology, and by courtesy, Professor at the Department of Mathematics, Statistics, and Computer Science. Karabatsos research deals with the development, improvement, and application of statistical models, especially for complex data sets. His inquiry deals with Bayesian models and related computational methods, for regression analysis, psychometric item-response analysis, causal inference, meta-analysis including publication bias analysis, and order-restricted statistical inference.
Karabatsos’ work has been published in various peer-reviewed journals including Psychometrika, Journal of Statistical Planning and Inference, Electronic Journal of Statistics, British Journal of Mathematical and Statistical Psychology, Computational Statistics and Data Analysis, Communication in Statistics: Simulation and Computation, Behavior Research Methods, and Research Synthesis Methods.

He has also published chapters in various books, including Handbook Of Item Response Theory: Models, Statistical Tools, and Applications, Statistical Models for Equating, Scaling, and Linking, Nonparametric Bayesian Methods in Biostatistics, Bayesian Evaluation of Informative Hypotheses, and Bayesian Theory and Applications.

Karabatsos is also an author of a menu-based statistical software package, which can perform data analysis using any one of more than 100 statistical models.

Karabatsos’ work as Principal Investigator has been supported by grants from the National Science Foundation, The Spencer Foundation, and the National Institutes for Health. Karabatsos also served as an Associate Editor for the journals Psychometrika and Computational Statistics and Data Analysis.


1998 – PhD, University of Chicago, Department of Education, Program in Measurement, Evaluation, and Statistical Analysis (MESA)

MESA Courses

  • Hierarchical Linear Models
  • Item Response Theory
  • Nonparametric Statistics
  • Educational Measurement
  • Theory of Statistics

Everett V. Smith, PhD

Everett Smith Headshot

Professor of Educational Psychology

Everett Smith specializes in psychometrics, specifically Rasch measurement, and his research interests and expertise include test and rating scale design and analysis for the measurement of latent constructs and testing model robustness.

He studies applications of Rasch measurement in the social, behavioral, health, rehabilitation, and medical sciences for both criterion and norm-reference assessments. Among these applications include studies of dimensionality, DIF, cross-cultural equivalence, equating, item banking, rating scale optimization and standard setting. Smith is the co-editor of Introduction to Rasch Measurement: Theory, Models, and Applications (2004), Rasch Measurement: Advanced and Specialized Applications (2007), and Criterion-Reference Testing: Practice Analysis to Score Reporting Using Rasch Measurement Models (2009). He serves as the associate editor for the Journal of Applied Measurement, and is on the editorial board of Educational and Psychological Measurement.


PhD, University of Connecticut

MESA Courses

  • Essentials of Quantitative Inquiry in Education
  • Rating Scale and Questionnaire Design and Analysis

Rebecca Teasdale, PhD

Rebecca Teasdale PhD

Rebecca Teasdale is an evaluation methodologist who examines the valuing process in evaluation: the activities of defining program success, specifying evaluative criteria, and applying criteria to reach conclusions. Her methodological research builds an empirically supported, descriptive theory of valuing and develops methods for specifying endogenous and individualized evaluative criteria. This work informs Dr. Teasdale’s substantive research on science and technology learning in adulthood in informal contexts. Currently, she is investigating women’s engagement with digital fabrication and how makerspaces and making experiences align with and support their definitions of success.

Dr. Teasdale’s research agenda is grounded in her previous work in science, technology, engineering, and mathematics (STEM) research, evaluation, and education. Prior to joining the UIC faculty, she was a research associate investigating the molecular basis of specific human diseases; a science and math librarian in public libraries; and a professional evaluator focusing on informal and formal STEM education.

Michael K. Thomas

Michael Thomas Headshot

Associate Professor of Educational Psychology

Michael K. Thomas is an associate professor in the Department of Educational Psychology at the University of Illinois at Chicago. His research focuses the cultural dimensions of technology implementation in learning contexts and what this means for the design of technology-rich innovations for learning. Three key questions with respect to this are (a) What are the central concerns of teachers, trainers, and other stakeholders regarding the implementation of technology in learning contexts? (b) What do they do to continually resolve these concerns? and (c) In what ways does culture play a role in the design and implementation of technology-rich innovations? He is particularly interested in video games and gameification in learning environments. He is currently PI on an NSF funded project on games for teaching and learning computer science and cybersecurity. He has expertise in qualitative research in general and grounded theory in particular. Before joining, UIC, he taught instructional technology and research methodology at the University of Oklahoma, the University of Wisconsin-Madison, and the University of North Carolina, Charlotte. He has also been an ESL/EFL teacher in New York City Public Schools and has taught overseas.


Ph.D. in Instructional Systems Technology and Language Education, Indiana University, Bloomington.

MESA Courses

  • Essentials of Qualitative Inquiry in Education
  • Qualitative Data Analysis
  • Grounded Theory

Terri Thorkildsen, PhD

Terri Thorkildsen Headshot

Professor of Education and Psychology

Theresa (Terri) Thorkildsen is a professor of Education and Psychology. Thorkildsen’s expertise in research design and methods is evident in her book, Fundamentals of Measurement in Applied Research. Thorkildsen’s current research highlights how individuals incorporate their understanding of the fairness of institutional practices into their motivation to achieve academic goals. Findings from these studies illustrate how individuals formulate and enact intentions. Thorkildsen seeks to understand how youth come to understand the structure of civil engagement, and how this type of engagement differs from personal and civic engagement. This programmatic attempt to understand why some individuals become highly committed to school while others avoid such commitments is disseminated in a wide range of outlets. As a fellow of the American Psychological Association and of the American Educational Research Association, Thorkildsen is also an active citizen in a number of professional organizations as well as in the UIC community.


1988 – PhD, Purdue University, Humanities, Social Science, & Education
1985 – MS, Purdue University, Humanities, Social Science, & Education
1982 – BS, University of Washington, Department of Psychology

MESA Courses

  • Introduction to Educational Research: Designs and Analyses

Yue Yin, PhD

Yue Yin Headshot

Associate Professor of Educational Psychology

Yue Yin is an Associate Professor in the Department of Educational Psychology.  Her research interests and expertise include assessments, science education, research design, survey design, and applied measurement/statistics. Dr. Yin is particularly interested in classroom assessment and applied measurement. She has conducted research on performance assessment, concept mapping assessment, formative assessment, concept inventory development and validation, and computational thinking assessment. The subject contents in her research have involved physics, chemistry, biology, mathematics, and statistics, ranging from K-12 to higher education. In her research, she used learning theory as a foundation, measurement and statistics as tools, to explore and examine ways of using assessments to improve students’ learning.


2005 – PhD, Stanford University, Science Education and Assessment
2003 – MA, Stanford University, Psychology
2000 – MA, Peking University, Educational Management
1997 – BS, Peking University, Applied Chemistry

MESA Courses

  • Advanced Analysis of Variance in Educational Research
  • Multiple Regression in Educational Research
  • Multivariate Analysis of Educational Data
  • Educational Measurement
  • Hierarchical Linear Models