Teaching philosophy
Teaching has profoundly enriched my graduate school experience. Whether the topic is data science or climate science, I welcome the challenge of explaining complex topics to an academically diverse classroom and explicitly drawing connections between theory and application.
My teaching philosophy is grounded in the creation of a constructive atmosphere where all questions are welcome and all students are participants in empowering each other. The teaching process - developing lectures, fielding discussions, and breaking down and reassembling assumptions and concepts - factors as an essential component of my own education. I can only hope that my students learn as much from me as I learn from them!
Courses
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Invited lecturer. “The Economic Intersection of Climate Change and Public Health” for “A Sustainable World: Challenges and Opportunities” (PBHLTH 101). Fall 2020. Undergraduate course introducing linkages between the environment and human health.
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Graduate student instructor. “Climate Change Economics” (ENERES 276, ENERES 176). Fall 2017. Graduate and upper-level undergraduate course encompassing integrated assessment model development, climate policy, and economics.
Workshops
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Vásquez, V.N.; Martinez, C.; Stoudt, S. “Principles for data-intensive research workflows: Guidance for the classroom and the computational laboratory.” Presentation and discussion for the Academic Data Science Alliance (ADSA) 2020 Annual Meeting, October 2020.
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Vásquez, V.N.; Carvallo, J.P.; Sánchez, H.M.C. “Introducción a R y Git.” International Spanish-language workshop presented for Software Carpentries at the Berkeley Institute for Data Science, March 2019. [link]
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Das, D.; Vásquez, V.N.; Barnes, R. “Pedagogy and Support Systems for Non-Classroom Data Science Instruction.” Presentation and discussion for the Moore-Sloan Data Science Environments (MSDSE) Summit, October 2018.