Designing the Data Science Classroom Workshop
9:00 AM-5:00 PM
2 Day Workshop
Union Square 22
Success in data science and statistics is dependent on the development of both analytical and computational skills, and the demand for educators who are proficient at teaching both these skills is growing. The goal of this workshop is to equip educators with concrete information on content, workflows, and infrastructure for painlessly introducing modern computation with R and RStudio within a data science curriculum.
In addition to gaining technical knowledge, participants will engage in discussions around the decisions that go into developing a data science curriculum and choosing workflows and infrastructure that best support the curriculum and allow for scalability. Workshop attendees will work through several exercises from existing courses and get first-hand experience with using relevant tool-chains and techniques, including running a course on RStudio Cloud, and literate programming with R Markdown, and workflows for collaboration, version control, and automated feedback with Git/GitHub. We will also discuss best practices for configuring and deploying classroom infrastructures to support these tools.
This workshop is aimed primarily at participants teaching data science in an academic setting in semester-long courses, however much of the information and tooling we introduce is applicable for shorter teaching experiences like workshops and bootcamps as well. Basic knowledge of R is assumed and familiarity with Git is preferred.
If your answer to the following questions is "yes", then this is the right course for you.
- Do you want to learn / discuss curriculum, pedagogy, and computing infrastructure design for teaching data science with R and RStudio?
- Are you interested in setting up your class in RStudio Cloud?
- Do you want to integrate version control with git into your teaching and learn about tools and best practices for running your course on GitHub?
In this workshop you will wear two hats: the educator and the learner. At times I will be demoing workflows for instructors (whom I assume are familiar with R, RStudio, and the tidyverse and have taught with or are interested in teaching with RStudio Cloud, Git, and GitHub) and at other times you will be working through the student view (on RStudio Cloud, assuming you're not using your local setup).
For the former, you'll need to come prepared. For the latter, you can assume you're a student in an intro data science course and this is the first day of class (i.e. there's no expectation of prep).
So, let's focus on the former -- the instructor view. The list of items you should complete prior to the workshop can be found at rstd.io/design-ds-class. If you need help with any of the steps, please reply below.