Author: Sebastian Kranz, Ulm University
RTutor is an R package that allows to develop interactive R exercises. Problem sets can be solved off-line or can be hosted in the web with shinyapps.io. Problem sets can be designed as a Markdown .rmd file (to be solved directly in RStudio) or use a browser-based interface powered by RStudio’s Shiny. While the web interface looks nicer, I personally use problem sets in the Markdown format when teaching advanced economic classes.
RTutor and some required packages are not hosted on CRAN (while CRAN is great it takes a lot of time to maintain several packages there). You can install it from my r-universe repository by using the following code:
options(repos = c(skranz = 'https://skranz.r-universe.dev', CRAN = 'https://cloud.r-project.org')) install.packages("RTutor")
Take a look at the manuals for documentation of how to create own problem sets. Also look at the examples below.
You can try out the Rmarkdown version of RTutor via RStudio Cloud:
For the web-based interface, several students at Ulm University have created very nice problem sets that allow to interactively replicate the main insights of interesting economic articles and to learn a bit about R and econometrics. Before developing your own problem sets, you may want to try out some of these examples:
If you a have course that uses RTutor that you want to share, just send me an email and I add your course to the list!
Two courses from me: Empirical Economics with R and Market Analysis with Econometrics and Machine Learning. Both consists of online shiny apps with videos and quizzes and many RTutor problem sets.
Jade Benjamin-Chung from UC Berkeley School of Public Health has created with RTutor online tutorials for an introductory R course for epidemiologists. If you click on a tutorial the corresponding RTutor problem set can be directly solved on shinyapps.io. There is no need to log in.
RTutor is also used in a compulsory data science project course taught by Alex Rieber for business and economics students at Ulm University. The problem sets teach basic skills in R, including tidyverse data wrangling, as well as econometric and machine learning basic with economic applications. Alex published the problem sets and other course material here on Github. You find on the Github pages also links that allow you to test the problem sets on the rstudio cloud. The course is in German but Alex already started to make an English version of the problem sets, which will be added once finished.
To install RTutor and required packages directly from Github and CRAN, you can use the small function in the following gist:
Copy the code in the link into your R console and then run:
Depending on your devtools version, also the following code may work directly (yet source_gist is buggy in some devtools versions):
if (!require(devtools)) "devtools") install.packages( devtools::source_gist("gist.github.com/skranz/fad6062e5462c9d0efe4", filename="install_rtutor.r") install.rtutor(update.github=TRUE)library(RTutor)
If you only want to update the RTutor package (and have the other packages already installed). You can just type:
(You may have to restart your R session / RStudio for the update to work.)
If you have suggestions or find bugs, please don’t hesitate to open an issue on the Github page.