Teaching Approach and Evaluations
I have a strong passion for teaching. My experience as an undergraduate at a teaching-oriented university showed me the value of having a strong connection between professors and students and the value of classroom discussion. This experience informed my approach as an instructor. At Smith College, I have taught courses in American Politics, Public Policy, Political Methodology, and Statistics. I teach with active learning at the center of all instruction, and emphasize real world implications of course content in student life.
My teaching interests are in American Politics and Quantitative Methods. For American Politics, I teach courses related to American Institutions the Politics of US States, and Public Policy. For statistical analysis, I teach introduction to probability and statistics, and welcome the opportunity to teach courses in Network Analysis, Multi-level modeling, Bayesian statistics among other topics.
I have consistently received teaching evaluations above the department and college mean. (Samples of teaching evaluations 1, 2). Students have particularly noted my flexibility and openness to questions and discussion both inside and outside the classroom. I was honored to receive the teaching assistant of the year award while at the University of Iowa.
I have experience as an Instructor in the Following Course
- Introduction to Probability and Statistics (with accompanied lab teaching introduction to R and the Tidyverse)
- Introduction to American Politics
- Seminar in the Politics and Policy of US states
- Seminar in Political Networks
- Introduction to Public Policy
- Multiple Regression
As a consultant for the Iowa Social Science Research Center, I have led a series of quantitative methods workshops introducing undergraduates, graduate students, and faculty to the following methodological approaches:
- Introduction to Stata
- Introduction to R
- Data visualization in R and Stata
- Multi-level Modeling
- Introduction to Network Analysis
- Advanced Network Analysis
- Model Interpretation in R and Stata