This course is field based. The student will work with an educational institution (e.g., school, school district, higher education) or agency (e.g., Department of Education, educational center, higher education) with a cooperating administrator/appropriate educator and a university supervisor. The field project will address a problem of practice of an educational institution, serve as a pilot study, or consist of an action research project.

This course introduces students to simple and multiple regression analysis, specifically as the methods are applied to research questions in educational research. Students learn about the linear regression model and its assumptions, how to use SPSS to fit the model to data, and how to interpret results. Students will also learn how to: evaluate the tenability of the model's assumptions; conduct thoughtful model building; model the effects of categorical predictors and statistical interactions; and handle multi-collinearity. The use of statistical techniques are modeled in class and then students apply these new techniques to datasets of educational relevance from a variety of sources, including educational surveys, observational studies, and randomized experiments. Students learn how to interpret the outcomes of their analyses thoughtfully and meaningfully and are asked to communicate these interpretations clearly and concisely in writing.

Opportunity for intensive investigation of a special problem or issue in the field of education.

Doctoral Research.