Teaching Philosophy
-
We are much more than a single course. Coursework should seek to educate more than just the intellectual dimension of a person. In order to grow in knowledge, we also must grow in virtue: fortitude in the face of a difficult exam, diligence in laborious study, temperance in the face of distractions, and faith in the abilities we have been given.
-
Practice of the rudiments and mechanics of an activity is key to success in any discipline, but the spark of intuition that connects the mechanical to the transcendent is what sticks with us long after the course is over.
-
The biggest course takeaways are often generalizations that must be abstracted from patterns of specific examples. The best balance comes from an insistence on particular, relevant, and insightful examples without losing the forest for the trees.
Courses
Undergraduate Thermodynamics II
I had the pleasure of working as a Teaching Assistant for Mark Stoykovich in spring 2019 for this course. He allowed me to guest lecture on Molecular Simulation and Flocculation/DLVO theory, and provided feedback on my topical lectures presented in weekly discussion section. Whenever possible, I tried to fill gaps in understanding with short crash course presentations and short concept questions. (Link to example problem on DLVO theory) ->
Undergraduate Thermodynamics II
I rejoined Mark Stoykovich in spring 2020 as a teaching assistant for Undergraduate Thermodynamics II. It was exciting to build on a course that we had already worked on together, and we shared discussions on the optimal topic selection and order. I was able to produce all the course homework assignments and exam problems. We also held final projects this year, and I proposed a molecular simulation project (#7) and mentored 4 students as they ran molecular dynamics simulations for the first time. At the end of the course, I evaluated the projects as a panelist with Professor Stoykovich. (link to full course materials) ->
Principles of Engineering Analysis II
Professor Stoykovich invited me to help with this large ~80 student course as the Chaitan Khosla teaching fellow in Winter 2021. I was responsible for teaching python content to follow the numerical methods curriculum of the course. In this capacity, I delivered weekly discussion lectures to teach introductory python from the ground up by implementing numerical algorithms. I was also responsible for organizing a team of three teaching assistants and communicating between the course instructor and TA team. (link to discussion section materials) ->
