Measurement, Evaluation, Statistics & Assessment (MESA) emphasis
The PhD program in Educational Psychology with an emphasis in Measurement, Evaluation, Statistics and Assessment (MESA) combines training with research experiences gained from participation in research projects. In Measurement, specific areas of study include measurement theory, Rasch measurement, Item Response Theory, true score theory, generalizability theory, test score equating, standard setting, and instrument design. In Evaluation, areas of study include evaluation methods, evaluation theory, the role of values in evaluation practice, specifying and applying evaluative criteria, partnering with stakeholders and communities, and evaluation use and influence. In Statistics, areas of study includes statistical theory, hierarchical linear modeling, nonparametric modeling, regression analysis, multivariate analysis, structural equation modeling, factor analysis, causal analysis, categorical data analysis, research synthesis and meta-analysis, exploratory data analysis, model estimation, model goodness-of-fit analysis, model selection, robust analysis, missing-data analysis, and research methods. In Assessment, study areas include qualitative methods, testing for licensure and certification, computer adaptive testing, large-scale testing and classroom-based assessment.
The other area of emphasis for the PhD in Educational Psychology is Human Development & Learning (HDL).
Academic Themes & Perspectives Heading link
PhD students can specialize in a particular MESA focus area, but all are encouraged to take courses in each of four areas. Available areas of expertise change as the composition of the faculty and the field change. Students are advised to look at the research interests of current MESA faculty to determine which topical interests to focus on during their program of study. Our current faculty members specialize in four areas:
- Measurement: Measurement courses cover a range of theories, models, and methods for measuring variables of aptitude, achievement, and attitudes. They include test, questionnaire, rating scale, and survey construction for data collection, and include contemporary measurement models for data analysis. These courses are designed to prepare researchers and practitioners to meet measurement challenges they will encounter when conducting research and applying measurement models in a variety of settings.
- Evaluation: Evaluation courses deal with the systematic collection of information about the activities, characteristics, and outcomes of programs and how this information can be used to make judgments about program quality, improve program effectiveness, and/or inform decisions about future program development. Students learn about evaluation theory and methods in coursework emphasizing the processes associated with planning and conducting evaluations. They become informed, critical evaluation stakeholders.
- Statistics: This area of emphasis enables students to conduct evidence-based research, to rigorously answer questions that are important to the educational and social sciences. Statistics courses cover a broad range of statistical models that are useful for the analysis of many types of data sets. They include models that discover the relationship between one variable with and a set of other variables, and models that describe causal relationships between variables (for example, the causal effects of educational treatments on academic achievement). Students who take statistics courses will gain the knowledge, skills, and abilities to analyze, interpret, and draw accurate conclusions from data.
- Assessment: Assessment courses focus on the process of collecting, synthesizing, analyzing, and interpreting quantitative and qualitative information to aid in decision-making. Assessment training allows students to design, administer, score, and interpret results from various types of assessments that measure simple and complex learning outcomes. Students learn how to design paper-and-pencil tests, performance assessments, and product assessments that are aligned with those standards that are to be evaluated as well as how to interpret various statistical findings. These skills can be used for a variety of purposes including the interpretation of score reports, determining appropriate modifications or accommodations when using a tool to assess the performance of students with disabilities or language limitations, the development and defense of grading procedures, and important legal purposes associated with education and employment.