This course gives students conceptual and philosophical frameworks for leading good instruction and creating conditions for teaching and learning in schools and districts. Students reflect on their own instructional filters and deepen understanding of what we know about effective teaching and learning. Considering various instructional issues, students learn to supervise and evaluate instruction, connecting supervision with professional growth.

This course equips educators with tools to lead continuous improvement aimed at advancing the academic success, engagement, and belonging of all children. Grounded in improvement science, the course introduces tools for systemic change and includes field-based application in P-12 teaching and leadership.

Examines how, as a team, school leaders analyze the relationship of the integration of technologies to teachers' beliefs & practices & to local school culture, structures, & policies. Students will evaluate factors critical for successful implementation of educational technology; identify & deconstruct the distributed leadership of educational technology in a school setting; & plan comprehensively for a system of practice to lead EdTech.

Leadership for Equity of Diverse Populations seeks to support special populations in schools. It proposes that effective leadership for all special student populations involves particular knowledge and requires a strong equity orientation.

Under close guidance of an individual faculty member, students work on areas of particular interest that cannot be met in regularly scheduled courses. Enrollment in this course is limited to three credits in a master's degree program.

The VEST proseminar is a set of activities designed around the speaker series. Students will read and critique academic articles, hear nationally renowned speakers present their recent work, and engage in conversation and dialogue with our visiting speakers. The primary goal of the proseminar is to improve your ability to critique research.

Focus is on the generalized linear model (GLM) for cases when variables have specific non-normal conditional distributions, with emphasis on common data analytic challenges that arise in real world settings. Topics include nonlinear relationships, nominal and ordinal outcomes, discrepant data, and bootstrapping methods. Course materials are grounded in applied examples from the social and health sciences.

This course is designed to familiarize students with the basics of multilevel modeling. Topics include random effects ANOVA models, means-as-outcomes models, random coefficients models, intercepts- and slopes-as-outcomes models, contextual models, random effects ANCOVA models, linear growth models, nonlinear growth models and cross-classified models. Prerequisite: EDLF 7420 or equivalent.

The major topics include exploratory/confirmatory factor analysis models, a variety of structural equation models, growth curve models, and multi-sample modeling analysis. The major focus of the course is both on the conceptual understanding of latent variable modeling and on practical application of these models in research and measurement. Students will work with data sets and computer programs to gain practical research experience.

We focus on problems of practice (POP) through systematic qualitative inquiry, specifically focusing on qualitative processes, questions, and strategies to conduce meaningful inquiry in educational systems. Specifically, the focus is on identifying a qualitative question to address POP and the creation of a qualitative design to address the POP. Co-requisite of EDLF 8384 Lab of practice.