Teaching Assistant: Intermediate Statistics

In the Fall, I was able to lead a weekly seminar for Master’s and PhD students in Dr. Henrik Singmann’s course Intermediate statistics: Data analysis and visualisation with R. This course is the psychology statistics course that I wish I’d have gotten when I was a graduate student, including a gentle introduction to R and the tidyverse, data cleaning and wrangling, analysis using ANOVAs and emmeans, and data visualization!

Each week for the 10-week course, I led students through their homework assignment. Rather than simply discussing the homework questions or providing the answers, I decided to go through the entire assignment by live-coding the solutions collaboratively with the students. Beyond giving me the opportunity to explain the solutions, the students loved this approach because it allowed me to (a) confront student’s understanding of why the code needed to look this way (as opposed to some other way), (b) outline that many solutions are usually sufficient, (c) zoom out from the technical details to the big picture to check understanding, and (d) pass on any of my hard-earned tips, tricks, and practices for developing in R.

One thing that I learned is that students often needed help with more rudimentary things like working directories (e.g., setwd) or figuring out how to use a function (i.e., ?... or help(...) in R). Another thing I learned is that in the modern era of LLM-assisted software development, students would often show up with working solutions to their assignments without understanding why those solutions were needed. Thankfully, because I coded the assignments live and collaboratively, I was able to make sure everyone was on the same page before moving forward.

And the students seemed to notice! Here are a couple comments from my end-of-term feedback form:

• “I really liked how we went through the homework. Kevin was so helpful and probably the biggest reason I understand what is going on. He explained things very well.”
• “Kevin was very welcoming and open about R, he also entertained many alternative answers to questions while explaining the pros and cons in understandable ways.”
• “He did a really good job explaining complicated topics in a way that made them very manageable. He also had so many short cuts and fun functions in R.”