install.packages("tidyverse")
install.packages("palmerpenguins")
install.packages("usethis")
install.packages("credentials")
install.packages("devtools")
install.packages("scales")Teaching statistics and data science with R and GitHub
useR 2025
🗓️ August 8, 2025
⏰ 13:00 - 16:30
📍 Gross Hall 270
Overview
In this tutorial, participants will learn about teaching R and GitHub in statistics and data science courses. We will discuss pedagogy and curriculum design for effectively teaching computing alongside statistical concepts. Participants will explore example in-class activities and assignments that demonstrate the student experience, while discussing strategies for implementing such activities from the instructor perspective. We will also discuss computing infrastructure options that enable students to use R and RStudio from a web browser with minimal set up. Lastly, we will show how instructors can use R and Quarto to make course materials and streamline their workflow in a reproducible way using GitHub. The tutorial will focus on teaching introductory-level undergraduate students with no previous computing experience, but the tutorial content is applicable for instructors teaching high school courses and courses throughout the undergraduate statistics and data science curriculum.
Learning goals
- Learn pedagogical strategies for teaching R and GitHub in a statistics or data science course
- Identify how computing can be integrated alongside statistical concepts in a course curriculum
- Experience computing activities and assignments from both the student and instructor perspective
- Consider the computing infrastructure that may be the best fit for your student population
- Learn how to develop course materials with R and Quarto and develop a reproducible workflow with GitHub
Target audience
This workshop is for instructors interested in teaching R in their statistics and data science courses. The workshop will be presented from the perspective of teaching at the undergraduate level;; however, the contents of this workshop will also be beneficial to instructors teaching high school statistics and data science.
Computing
RStudio Docker containers
RStudio with available through Docker containers provided by Duke Office of Information Technology. You will be able to access RStudio through a web browser. The link to access RStudio will be provided at the workshop.
All you need is a laptop or any other device that has internet access and a keyboard. No set up is necessary!
R packages and installations (optional)
We will use the following packages during the tutorial. If you are using RStudio installed directly on your laptop, please install the following prior to the tutorial:
We will also work with GitHub, so you will need git installed on your machine. To do so, follow these instructions from Happy Git and GitHub for the useR. (Note: you do not need to do this if you are using RStudio through the Docker containers).
GitHub
You will work with GitHub during this workshop. There will be time during our scheduled break to create an account. However, if you’d like to do this before the workshop starts, please do so! See the steps below.
Go to github.com, and create an account (unless you already have one).
Create a username. Some tips on creating a username from Happy Git and GitHub for the useR include…
Incorporate your actual name!
Reuse your username from other contexts if you can, e. g., Twitter or Slack.
Be as unique as possible in as few characters as possible. Shorter is better than longer.
Avoid words with special meaning in programming (e.g. NA).
Instructors
Dr. Elijah Meyer is a teaching assistant professor at North Carolina State University with 12+ years of experience in both developing and instructing in-person and online courses in statistics and data science. Prior to becoming faculty at NC State, Elijah earned his Ph.D. is Statistics, with a focus in Education, from Montana State University. After this, Elijah completed a two-year post-doc position at Duke University where he was responsible for teaching introductory data science courses, and various research projects in statistics/data science education. His current research focuses on how to better the teaching and learning experiences for those involved. Elijah developed the first introductory data science course at NC State, and has re-designed other graduate level courses to incorporate R and GitHub.
Dr. Maria Tackett is an Associate Professor of the Practice at Duke University. Prior to joining the faculty at Duke in 2018, Maria earned a Ph.D. in Statistics from the University of Virginia and worked as a statistician (now called a “data scientist”) at Capital One. Her research focuses on students’ sense of belonging and inclusive teaching practices in introductory math and statistics courses. She teaches using R and GitHub in multiple courses in the undergraduate curriculum, from introductory-level to upper-level electives. She is an RStudio certified trainer in Tidyverse and is active in the statistics and data science education community.
Acknowledgements
The materials in this tutorial were inspired by the Designing the data science classroom workshop taught by Mine Çetinkaya-Rundel and Maria Tackett at rstudio::conf(2022).
Thank you to Mark McCahill and Duke Office of Information Technology for providing RStudio Docker containers for this tutorial.