I have taught in and out of academia for over a decade, spanning a wide variety of subjects and contexts: chemistry labs and tutoring as an undergraduate, English as a foreign language in South Korea, preparation for the writing section of the medical school admissions test, and a small-group research-project course during my master’s.
As a PhD student, I have TAed network analysis and applied Bayesian statistics classes, and I have developed and taught courses on computational research skills, both individually for UC Davis and as part of the Software Carpentry and Data Carpentry collectives. I am excited to be the instructor of record for UC Davis’ large undergradaute course on current issues in the environment in the first quarter of 2017. If you’d like to know more about my teaching philosophy, check out my talk at the 2016 R User Conference.
Current Issues in the Environment
This class (Winter 2017) will introduce students to physical and social science perspectives on current environmental issues and explore challenges associated with implementing policy to address local, national, and international environmental problems.
Software and Data Carpentry
These international non-profits offer intensive two-day workshops on best practices for scientific software development and data analysis. I was first exposed to them as a participant in 2013, I became an instructor in 2015, and I am currently developing and piloting a social sciences curriculum for Data Carpentry. Their pedogogical training is excellent and has made me a consistently better teacher both in computing and other subjects. I have taught workshops at Davis (twice) and Stanford, and will be further refining and piloting the social science material in late 2016 and early 2017.
Richard McElreath says he developed this course to be the statistics class he wishes he had as a graduate student, and it certainly is the statistics class that I didn’t know I had been wanting. Designed for PhD students, it starts with probability theory and builds to information criteria, Hamiltonian Monte Carlo, data imputation, and multilevel models. By taking a Bayesian framework from the beginning and leveraging scripting and computational techniques, it manages to be conceptually clear, rigorous, and highly practical for applied researchers.
I TAed this class in winter 2016, after Richard moved to Leipzig to run a wing of a Max Planck Institute. His lectures were pre-recorded, and I was the sole in-person contact for the students. I developed an online home for the course at piazza.com and hosted review sessions and office hours for students. The “class notes” have now been published as a textbook by CRC Press, and I look forward to developing my own class based on this someday.
Each UC Davis Professors for the Future fellow develops a project to serve the Davis graduate and postdoctoral communities. Mine was a week-long “bootcamp” in the statistical programming language R. It was attended by 200 people (nearly 400 registered!) and employed a lot of Software and Data Carpentry techniques. After the course, I wrote a blog post reflecting on the experience, which eventually became a conference talk, endorsed by none other than the man himself:
In summer 2015, I TAed Lorien Jasny’s Interuniversity Consortium for Political and Social Research course on social network analysis at Berkeley.
Also in the network-analysis vein, I gave a talk to the UC Davis Network Science group on exponential random graph models, which I subsequently developed into this extensive tutorial.
Total Science Experience
During my master’s, I led sessions of WVU Biology’s capstone undergradaute course, in which I mentored small groups of students through the design, proposal, execution, and presentation of an ecological research project. I also taught environmental biology and introductory biology laboratories.
Before my master’s I lived South Korea and taught English for two years, one in an after-school academy in a big city and one in a rural public elementry school. Before that, I worked for The Princeton Review, teaching writing for the MCAT and developing practice tests for the GRE, GMAT, and SAT. As an undergraduate, I tutored and worked as a chemistry laboratory assistant.