Teaching
Teaching Philosophy
I designed and taught a three-session “Introduction to Stata” workshop for researchers at the Vietnam Institute of Economics. The moment I knew it was working came near the end, when a participant sat there debugging her own do-file out loud, trying one fix at a time instead of turning to me to fix it for her. I teach for that, for students who can ask sharper questions, reason with evidence, and act on it without waiting for permission. In applied economics that means fluency in models, causal thinking, and data, enough that theory actually touches the messy reality it is supposed to explain. I approach a classroom the way I approach a research question. I form a hypothesis about what will help students learn, look for quick evidence (a poll, a problem set, a puzzled face in the third row), and revise before the next session. What I want from students is real conceptual understanding, quantitative and communication skills that hold up under questioning, a clear sense of how theory connects to policy and practice, and a room where high standards and honesty do not come at the cost of who feels welcome to speak.
Teaching Experience
Graduate Teaching Assistant, AAEC 5525: Applied Microeconomics (master’s level) Department of Agricultural and Applied Economics, Virginia Tech Assignment grading and student support.
Field Supervisor and Enumerator Trainer International Center for Tropical Agriculture (CIAT), 2019 to 2022 Led roughly three-day trainings for teams of about 12 enumerators on the questionnaire and CSPro data-entry application before each of two household surveys, then supervised fieldwork.
Workshop Instructor, Introduction to Stata for Economic Analysis Vietnam Institute of Economics Designed and delivered a three-session workshop for researchers, including lecture material and applied exercises.
Courses I Am Prepared to Teach
- Introduction to Microeconomics and Macroeconomics
- Environmental and Resource Economics
- Econometrics
- Data Science for Applied Economics and Policy, a course I would especially like to build out
My working knowledge of Stata, R, Python, and machine learning, including Stanford’s Machine Learning Specialization, lets me teach coding and economic reasoning together rather than as two separate things bolted side by side. My research on climate risk, water scarcity, and land-use decisions in agricultural systems also puts me in a good position to develop applied modules or short courses for Extension and stakeholder audiences, so that classroom econometrics stays connected to decisions real farmers and land managers have to make.