Education Policy and Leadership Courses

EDST 691 Education Policy for Multilingual Students
3 Credits
This course critically interrogates historical and current approaches to meeting the needs of multilingual and immigrant-origin students in the US. The focus is how schools structure.

EDST 692 Educational Policy Analysis
3 Credits
The purpose of this course is to introduce graduate students to the craft of education policy analysis. In the course, students will learn frameworks and employ tools to conduct education policy analysis, as well as conduct an analysis of an education policy issue of their choosing. Further, students will develop policy analysis writing skills for key education policy stakeholders.

EDST 693 Educational Governance and Policy Process
3 Credits
This graduate level course introduces students to the education governance structures and policy- and law-making processes at the federal, state and local levels. The course is designed for students who seek to become more sophisticated in their ability to read critically about, understand, and interpret the roles of various educational bodies and actors as well as the policy process and policy environment.

EDST 694 Survey of United States Education Policy
3 Credits
This is a graduate-level class designed to facilitate students’ understanding of the major policy areas and debates in contemporary U.S. public K-12 education systems. It is designed for graduate students who seek to become education policymakers, school and system leaders, policy analysts, and researchers.

EDST 695 Foundations of Education Policy and Leadership
3 Credits
Required course for the Master of Science in Education Policy and Leadership (MS-EPL) to introduce students into the program, build community within the cohort, develop a shared sense of purpose and direction in the program, and learn foundational core concepts of education policy and leadership.

EDST 696 Education Policy and Leadership Master’s Project
3 Credits
The purpose of this course is to scaffold students through the development and completion of their Educational Policy and Leadership master's capstone project. The capstone project is a discrete empirical examination of a problem of practice. The course also covers career planning and presentation skills.

EDST 697 Higher Education Policy
3 credits
This course provides a comprehensive introduction to the realm of public policy in higher education. It delves into relevant research, theoretical frameworks, and areas of debate within the field.

EDST 698 Education Law
3 credits
This course is designed to increase students’ understanding of the legal framework that governs schools and educational policy, focused primarily on US K-12 issues, though we will touch on some higher education issues as well. It examines the basics of the US legal system; the legal rights of students to a high-quality education; educational equity (including desegregation and affirmative action); students’ and faculty’s rights of free expression; student discipline and school choice.

EDST 699 Higher Education Leadership
3 credits
This course will analyze the structures and systems-level composition of higher education in the United States; deconstruct the concentric systems of higher education administration and the interrelated leadership roles within those systems; and, examine and classify the subdivisions of possible career paths in higher education administration.


EDLD 643 Evidence-based decision-making
3 Credits
Introduces basic concepts of evidence-based decision making.

EDLD 651 Introductory Educational Data Science
3 Credits
Introduces students to the fundamentals of statistical computing for data science. Introductory programming, data wrangling, data visualization, reproducible research.

EDLD 652 Data Visualization
3 Credits - Prerequisites: EDLD 651 with a grade of C- or better
Best practices in data visualization for social data science communication. Visual perception, color, uncertainty, and communication mediums.

EDLD 653 Functional Programming for Educational Data Science
3 credits - Prerequisites: EDLD 651 with a grade of C- or better
Foundations of functional programming for data science. Function writing and iteration emphasized.

EDLD 654 Machine Learning for Educational Data Science
3 credits - Prerequisites: EDLD 651 with a grade of C- or better
Statistical models for prediction. Bias-variance tradeoff, cross-validation methods, model evaluation, and a variety of models used in data science.

EDLD 640 Educational Data Science Capstone Project
3 Credits - Prerequisites: EDLD 651, EDLE 652, EDLD 653, EDLD 654
The final course of the Educational Data Science specialization, this course is an applied capstone where students tackle an applied data problem.


EDUC 612 Social Science Research Design
3 Credits
Overview of qualitative, quantitative, and single-subject research methods. Emphasis on introducing students to considerations, issues, and techniques of social science research design.

EDUC 620 Program Evaluation I
3 credits
Introduction to program evaluation design and methods.

EDUC 621 Program Evaluation II
3 credits - Prerequisite EDUC 620
Implementation and completion of the evaluation design defined in Program Evaluation I.

EDUC 641 Applied Statistics in Education and Human Services I
3 credits
This course provides a first introduction to quantitative data analysis in education and the social sciences. It is part of a three course sequence intended to provide a toolkit of statistical concepts, methods and their implementation to producers of applied research in education and other social sciences. The course is organized around the principle that research design depends in part on researchers’ substantive questions and their quantitative data available to answer these question. In this introductory course, we will focus on describing categorical and continuous data and quantifying the relationship between categorical and continuous data. Students will form a solid foundation for frequentist, inferential statistics (and some of critiques of this model). The course seeks to blend a conceptual, mathematical and applied understanding of basic statistical concepts. At the core of our pedagogical approach is the belief that students learn statistical analysis by doing statistical analysis. This course (or substitute) is a pre-requisite for EDUC 643.

EDUC 643 Applied Statistics in Education and Human Services II
3 credits
How closely linked are students’ scores on standardized tests to their socio-economic status? Do individuals with disordered eating behaviors have lower self esteem? Applied data analysis can answer these and other sorts of questions in educational, social and behavior research. This course is the second in a three course sequence intended to provide a toolkit of statistical concepts, methods and their implementation to producers of applied research in education and other social sciences. The course is organized around the principle that research design depends in part on researchers’ substantive questions and their quantitative data available to answer these question. In this intermediate course, we will focus on applying the General Linear Model to Ordinary Least Squares regression analysis. Students will progress from bivariate to multiple regression, developing an understanding of the associated assumptions of these models and tools to solve instances in which those assumptions are unmet. The course seeks to blend a conceptual, mathematical and applied understanding of basic statistical concepts. At the core of our pedagogical approach is the belief that students learn statistical analysis by doing statistical analysis. EDUC 641 (or a similar introductory statistics course) is a pre-requisite as is a basic familiarity with a statistical programming language (preferably R). This course (or substitute) is a pre-requisite for EDUC 645.