Education Core

This course will examine issues relevant to diversity and equity in education. Prominent sociological and anthropological works on race, class, gender and their intersectionality in educational contexts will be discussed. Discussions will center on how these constructs impact equality and equity in educational environments. Extant research and theoretical frameworks specific to diversity and equity in education will be examined and critiqued.

This course will provide candidates with an introduction to different types of quantitative research methods and statistical techniques. The course will be divided into two sections: 1) methods for quantitative research and, 2) quantitative statistical techniques for analyzing data. The course begins with a focus on defining research problems, theory testing, data identification and classification, causal inference, and designing research instruments. Then, the class will explore a range of statistical techniques and methods that are available for empirical research. Candidates will work in teams to explore research methods that may be applicable to their individual dissertation including: Primary and Secondary Data Analysis, Sampling, Survey Design, and Experimental Designs. Topics in quantitative techniques include Descriptive and Inferential statistics. Emphasis is placed on practical usage of quantitative methods and the acquisition of sufficient theoretical knowledge needed for data interpretation.

This course focuses on the application of advanced qualitative research methods. Course topics may be related to data collection (e.g., interviews, focus-groups, observations, field logs, document analysis), sampling (e.g., maximum variation, snowball, convenience, quota), validity (e.g., member checks, intercoder reliability, auditing, bracketing, triangulation), and other important topics (e.g., rapport, ethical considerations, epistemology, ontology, coding techniques). Emphasis is placed on practical usage of qualitative methods and sufficient theoretical knowledge needed for data interpretation.

This course focuses on the identification and classification of data and the application of quantitative research methods designed to answer specific questions of interest identified by the candidates as applicable to the development of their dissertation. Candidates will have the opportunity to identify a research problem, develop appropriate question(s), select the methodology for answering the question(s), conduct the analysis on dummy data, and interpret the results. Course topics may include: correlation, regression, effect size, analysis of variance, analysis of covariance, and multiple analyses of variance. In this course, candidates will run and interpret quantitative research using various software applications. Emphasis is placed on practical usage of quantitative methods and the acquisition of sufficient theoretical knowledge needed for data interpretation.

This course provides the foundation for the understanding of various types of qualitative research, including ethnography, case study, grounded theory, narrative analysis, and phenomenology. This course also focuses on the development, implementation, and evaluation of public policy at the national, state, and local level. The course is designed for candidates to learn about the craft of interpretive policy analysis as conducted by educational researchers. Frameworks and methods for analyzing policy are presented. The course is organized to help one understand and discuss current thinking about the nature of policy analysis, analyze one or more actual policy issues, and produce and present policy recommendations based on evidence produced through systematic research. Critical thinking methods regarding the interpretation of educational policies will also be presented.

This course is designed to provide a springboard from which candidates will successfully plan, write, defend, and complete an EdD dissertation. The instructor will guide candidates through the construction of research questions, the theoretical framework, and the problem statement sections of their dissertations. The instructor will also teach candidates dissertation format standards, psychological and time management demands, committee formation, Institutional Review Board (IRB) process, and project management.