Applied Quantitative Methods for the CPED Inquiry Cycle

Catalog description

This doctoral-level course, grounded in the Carnegie Project on the Education Doctorate (CPED) framework, prepares practitioner-scholars to leverage applied statistics in service of the Dissertation in Practice (DiP). Using authentic educational datasets and statistical software, students will apply descriptive, correlational, inferential, and nonparametric methods to address Problems of Practice (PoPs) in Educational Leadership, Curriculum & Instruction, and Higher Education. Emphasis is on meaning-making rather than mere computation, with students learning to interpret results in ways that drive real-world decision-making. The course is anchored in improvement science principles—particularly the Plan–Do–Study–Act (PDSA) cycles—to help students use data iteratively for testing and refining interventions. Above all, the course foregrounds a commitment to excellence for all learners, preparing practitioner-scholars to use data to uncover disparities and design practices that improve outcomes for all student populations.