Interactivity and immediate feedback with learnr

rstudio::conf(2022)
Designing the data science classroom

Maria Tackett

What?

Parts of a tutorial

Link to tutorial: minecr.shinyapps.io/dsbox-01-edibnb

Why?

Within a course

• In a flipped classroom
  • Assign a learnr tutorial that students can practice with before introducing a concept in class
  • Cover the concept in class (quicker)
  • Allocate the time saved to hands on exercises in class
• As lecture follow-up
  • Provide the same content from the lecture as follow-up exercises
• Provide immediate and meaningful feedback at scale

Self learning

• Learn by doing
• Tutorials in R packages
• Workshop follow-ups

How?

Topics

• Question types

• gradethis for automated feedback

• Recording student responses using minute papers and learnrhash

• Sharing tutorials with students

Getting started: Qmd ➡️ Rmd

• Learnr tutorials are written in an R Markdown document (.Rmd)

• The syntax and structure is very similar to a Quarto document (.qmd)

• These documents primarily differ in some arguments in the YAML

YAML for learnr tutorial

---
title: "Learnr Demo"
output: 
  learnr::tutorial:
    progressive: true
    allow_skip: true
    css: "css/style.css" 
runtime: shiny_prerendered
---

• runtime: shiny_prerendered: Turns R Markdown into interactive app
• progressive: true: Display one subsection at a time
• allow_skip: true: Able to skip exercises in a section
• css: "css/style.css": Apply custom formatting

Demo

Follow along

Follow along options:

• Local:

  • In RStudio, install and load the learnr, gradethis, sortable, and learnrhash packages
  • Access the source file for the tutorial on GitHub: https://github.com/rstudio-conf-2022/teach-ds-learnr

• Cloud: Go to the workspace for this course and start the assignment called 04 - Learnr.

• Deployed tutorial: https://minecr.shinyapps.io/learnr-demo

Writing questions

• Question types
  • Multiple choice
  • Coding exercises
  • Sorting questions
• Automated feedback

Your turn: Writing exercises

RStudio Cloud > “Module 4 - Learnr” > learnr-demo.Rmd > Part 2: Your turn!

Add three questions to the tutorial:

• one multiple choice
• one coding exercise
• one sortable question

Stretch goal: Add hints to the coding exercise.

You can write your questions in Part 2: Your turn! section of learnr-demo.Rmd.

Compare your answer with your neighbor. Then type the code for one of your exercises.

15:00

gradethis

The gradethis package makes it feasible to check coding exercises in a learnr tutorial. There are two basic methods for checking:

• grade_this_code(): Compare student code to model code (strict check)

• grade_this(): Compare student result to model result (flexible check)

devtools::install_github("rstudio/gradethis")

Your turn: Writing automated feedback

RStudio Cloud > “Module 4 - Learnr” > learnr-demo.Rmd > Part 4: Your turn!

Add automated feedback to your coding exercise.

Stretch goal: Consider 2 -3 common errors students may make. Write specific feedback for those errors.

You can write your responses in Part 4: Your turn! section or modify the code in Part 2 of learnr-demo.Rmd.

Compare your answer with your neighbor. Then type the code for one of your exericses.

10:00

Recording student responses

“Minute paper”

Add a link to a form at the end of the tutorial for a “minute paper”

• Write about one or two questions you didn’t get right initially but were able to solve after a few tries. What was difficult about them? What did you ultimately learn?

  OR

• If you got every single question correct on the first try, write one question you would still like clarified on the topics covered in this quiz.

learnrhash

• Use the learnrhash package to collect student responses from learnr tutorials.

• Students submit responses using a “hash” submitted in an online form.

remotes::install_github("rundel/learnrhash")

Sharing with students

• Deploy on

  • shinyapps.io
  • RStudio Connect (free for academic use)

• Distribute tutorials as a package

  • Example: dsbox R package includes a set of learnr tutorials

  • More about developing packages in a later session

Learn more!

Creating learnr tutorials

• Teaching with learnr: a powerful tool for remote teaching by Allison Horst
• Building interactive tutorials in R by Mine Çetinkaya-Rundel
• Feedback at scale by Mine Çetinkaya-Rundel
  • Click here for video

Learn more!

Sharing tutorials

• Publishing learnr tutorials on shinyapps.io by Angela Li
• How to deliver learnr tutorials in a package by Desirée De Leon

Workshop check in

We have completed Day 01! Please answer the following using your sticky notes:

• Purple sticky note: What is going well / what has been your favorite part of the workshop so far?

• Orange sticky note: What is still unclear or confusing?