Teaching
My Approach to Teaching and Mentorship
My teaching and mentorship emphasize the integration of theory, analysis, and practice. I aim to help students think critically about the relationship between evidence, policy, and governance, and to apply rigorous, creative problem-solving to real-world challenges.
Teaching is a natural extension of my research, allowing me to bring lessons from collaborations with government agencies, national laboratories, and interdisciplinary teams into the classroom in accessible, applied ways. My goal is to help students build confidence and technical skill by connecting abstract concepts to real policy questions and by engaging directly with practitioners and policymakers.
I see teaching and mentorship as collaborative processes that build capacity and strengthen the link between research and practice—values that align closely with IPPRA’s mission of interdisciplinary, evidence-based policy education.
Recent Courses
My teaching focuses on graduate-level courses in public policy and research methods. I have taught Foundations of Public Policy, which introduces core theories of the policy process and their application to real-world research, as well as two doctoral statistics courses—Introduction to and Intermediate Analysis of Political and Administrative Data—that build skills in statistical reasoning, programming, and analysis.
To assist with my statistics courses, I co-wrote an open-source textbook and lab guide that integrate R-based exercises, reproducible code, and applied examples to help students develop both conceptual understanding and technical proficiency. The textbook and lab guide are freely available online:
- Quantitative Research Methods for Political Science, Public Policy & Public Administration
- Lab Guide to Quantitative Research Methods in Political Science, Public Policy & Public Administration
More recently, I have focused on advanced methods courses in Data Visualization and Survey Research Methods, which connect research design with communication and application. Data Visualization teaches students to create clear, accessible graphics that convey complex evidence to both scholarly and practitioner audiences. Survey Research Methodology provides hands-on experience with survey design, implementation, and analysis, with attention to sampling, measurement, and total survey quality.