Feedback at scale

As enrolments in statistics and data science courses grow and as these courses become more computational, educators are faced with an interesting challenge -- providing timely and meaningful feedback, particularly with online delivery of courses. The simplest solution is using assignments that are easier to auto-grade, e.g. multiple-choice questions, simplistic coding exercises, but it is impossible to assess mastery of the entire data science cycle using only these types of exercises. In this talk I will discuss writing effective learnr exercises, providing useful and motivating feedback with gradethis, distributing them at scale online and as an R package, and collecting student data for formative assessment with learnrhash.

Talk materials

• Slides
• learnr tutorial

You can find the source code for the learnr tutorial here as well as on RStudio Cloud.

Learn more

• Packages:

  • learnr
  • gradethis
  • dsbox
  • learnrhash

• Workshop: Building interactive tutorials in R

• Blog posts:

  • How to deliver learnr tutorials in a package by Desirée De Leon
  • Teach R with learnr: a powerful tool for remote teaching by Allison Horst
  • Publishing learnr Tutorials on shinyapps.io by Angela Li