Facilitating Active Learning in Data Science Lectures: Embedding Editable and Executable R Code into Slides

In data science education, competency is built through hands-on manipulation of code and data. Traditional lecture slides often lack this kind of active learning, presenting static lines of code alongside their output instead. When live coding is needed, instructors often need to switch between the slides and a separate environment such as RStudio — one that students may need to install themselves just to reproduce the demonstration. This presentation demonstrates a workflow for creating slides that embed live, editable R code students can modify and execute directly within the slide itself, removing the friction of switching between lecture material and a separate coding environment. We use Quarto, the live-revealjs extension, and GitHub Pages to build a simple, reproducible example course website that instructors can clone and adapt for their own use.

To join this seminar virtually, please request Zoom connection details from hr.ops@stat.ubc.ca.

This talk is one of the Statistics Teaching and Learning in Statistics and Data Science Seminar Series.