Current Courses
Use and Misuse of Standardized Testing
In this undergraduate course we examine the principles underlying effective or valid educational and psychological testing. Topics include test development, administration, and evaluation, common uses and misuses of test results, and critiques of fairness, accessibility, and bias in operational tests such as PISA and the SAT.
Educational Testing and Evaluation
This is an introductory graduate course in the theory and practice of measurement in education and psychology more broadly. We discuss common applications of measurement and debates surrounding their interpretation and use. We also review procedures for test development and scoring as well as statistical methods for evaluating reliability, validity, dimensionality, and test fairness.
Advanced Measurement
This is an advanced graduate course that surveys some of the more common psychometric methods used in test development and evaluation, including models of reliability, dimensionality, and longitudinal change, measurement invariance, equating, and applications of machine learning and educational data analytics.
R for Data Science
This is a graduate course that introduces R via the book R for Data Science by Hadley Wickham and Garrett Grolemund. We use RStudio and the tidyverse to cover the basics of manipulating, analyzing, modeling, and visualizing data. Advanced topics such as functional programming, simulation, and R package development may also be addressed for students who are interested. More info here.
Data Driven Decision Making for Change
This course is designed for graduate students in educational leadership. The course reviews strategies for incorporating, analyzing, and evaluating information from multiple data sources to improve decision-making and problem-solving in P-12/community college settings.
Previous Courses
Statistical Methods
This is a graduate-level introductory course in descriptive and inferential statistics in the social sciences, covering topics such as central tendency, variability, correlation, regression, sampling, probability, and hypothesis testing.
Intro to Educational and Psychological Measurement
This is a course in the theory and applications of educational and psychological measurement, taught in the spring and summer semesters. Topics include measurement applications in research and practice, reliability and validity, item writing and test design, and statistical analysis of test data. This course assumes that students have taken or are concurrently enrolled in a course in introductory statistics.
Equating
This is an advanced graduate-level course providing an overview of statistical equating, scaling, and linking, with a focus on applications and recent research. Topics include test development and equating design, traditional equating methods, IRT methods, smoothing, scaling, and linking. Class meetings consist of lecture, class discussion, and student presentations. Students are required to have taken intermediate statistics and measurement courses. Courses in IRT and multivariate methods are recommended but not required.