Creating new materials for data science and programming workshops is time consuming. This has always been true, but when we switched to remote instruction in Spring 2020, the research data services team found ourselves having to recreate many of our materials to work more effectively for virtual workshops. During this change over, we developed a process and template for creating interactive data science and programming workshop materials that both work well remotely and will transition to in-person workshops in the future. We’ve learned the hard way how to deal with some of the challenges of teaching technical skills remotely.
We want to see more members of the Northwestern community confidently and effectively teaching the data science and programming skills they know to others. So we’ve created what we’ve been calling The Workshop Workshop, AKA Data Science and Programming Workshop Design.
This full-day workshop (9am-4pm) will guide participants through creating materials to teach a data science or programming workshop. You’ll focus your topic to create interactive materials that work well both virtually and in-person. The workshop will be useful for those who may be teaching or TAing a data science, statistics, or programming course in the future, as well as those who want to share their skills with others through data science nights, meetups, or other forums. Participants will also have a chance to submit their workshop to teach during our summer workshop series.
Takeaways:
- Draft of materials for a one-hour interactive data science or programming workshop
- Template and process for creating additional workshop materials in the future
This is a hands-on workshop focused on creating data science and programming tutorial/workshop materials. We will be focusing on creating teaching materials rather than on how to teach.
Schedule Overview
- Introduction: overview of the tutorial template, walk-though of examples (see Next Steps in Python and Tidyverse)
- Outline your Workshop: choose a topic and outline exercises/examples
- Data, Intro, and Technology: choose a dataset or running example, figure out the technology to teach, and write intro material
- Lunch break
- Work sessions: fill in your exercises and examples, get feedback
- Other details: description, preparation instructions, prerequisites
- Tips: teaching, getting the materials done