Computing Infrastructure and Curriculum Design for Introductory Data Science

TMaterials for the “Computing Infrastructure and Curriculum Design for Introductory Data Science” workshop at SIGCSE 2019 in Minneapolis, MN.

See the GitHub repo here, and the RStudio Cloud space here.

When and where

7:00 PM - 10:00 PM
Wed Feb 27, 2019
Hyatt: Greenway F (2nd floor)


Interested in teaching introductory data science? running your course on GitHub, and doing so efficiently? what first exposure to computing with R might look like? what the tidyverse is? If your answer is yes to any of these, this workshop is for you! We will showcase and discuss the pedagogical considerations behind the introductory data science curriculum presented in Data Science in a Box (datasciencebox.org), get hands on practice with tooling, and share a complete set of open source course materials, including teacher facing documentation and student facing learning resources and assessments.


The goal of this workshop is to equip educators with concrete information on content and infrastructure for designing and painlessly running a modern data science course. This is a three-part workshop.

Workshop attendees will work through several exercises from the course and get first-hand experience with using the tool-chains and techniques described above. All workshop content, including teacher facing documentation and student facing course materials, will also be available to participants via datasciencebox.org.


Pre-workshop instructions

In this workshop we will be coding in R via the RStudio IDE. If the conference WiFi cooperates we will do this in the cloud via rstudio.cloud. I will purposefully hold off instructions for this so that you can experience students’ day one experience in the class.

However, the backup option, in case WiFi doesn’t cooperate, is running RStudio locally. Below are the instructions for the required local setup. Note that these instructions are a lot more detailed than what the students in the intro data science course are exposed to.

## [1] '3.5.2'
workshop_pkgs <- c("tidyverse", "openintro",  "infer", "broom")