Creating interactive R Problem Sets. Automatic hints and solution checks. (Shiny or RStudio)
R CSS
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
grading
inst
man
ps_app_skel
ps_pkg_skel
vignettes
www/highlightjs
.Rbuildignore First version Jul 25, 2013
.gitignore First version Jul 25, 2013
DESCRIPTION
NAMESPACE
NEWS.md
README.md
RTutor.Rproj Update Installation Instructions Jun 2, 2018
TODO.md

README.md

RTutor: Interactive R Problem Sets

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.

Trying out some problem sets

You can try out the Rmarkdown version of RTutor via RStudio Cloud:

https://rstudio.cloud/project/39040

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:

Public Procurement Auctions: Design, Outcomes and Adaption Costs (by Frederik Collin)

Poverty Reduction and Deforestation (by Katharina Kaufmann)

The Effect of Water Pollution on Cancer (by Brigitte Peter)

Assessing Free Trade Agreements (by Tobias Fischer)

How soap operas reduced fertility in Brazil (by Clara Ulmer)

CO2 Trading and Risk of Firm Relocation (by Benjamin Lux)

On the optimal taxation of top incomes (by Jonas Send)

The effect of the TseTse fly on African Development (by Vanessa Schöller)

Pollution Reduction by Wind Energy (by Anna Sophie Barann)

Wall Street and the Housing Bubble (by Marius Wentz)

Air pollution and house prices (by Moritz Sporer)

A macroeconomic study of credit booms and busts (by Thomas Clausing)

The impact of emmission trading on green innovation (by Arthur Schäfer)

Building Codes and Energy Efficiency (2 versions, by Simon Hertle and Lisa Eilts)

Technological Progress and Fuel Economy of Cars (by Marius Breitmayer)

How can Scandinavians tax so much? (by David Hertle)

An interesting case study of a bank run (by Joachim Plath)

Installation

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). I have created an own Github based R repository, from which you can install RTutor by using the following code:

install.packages("RTutor",repos = c("https://skranz-repo.github.io/drat/",getOption("repos")))

Note: If you want to create your own web-based RTutor problem sets and upload them on shinyapps.io, you need to install RTutor and required packages directly from Github and CRAN as explained below. That is because shinyapps.io only works with R packages directly installed from Github or CRAN.

Installing RTutor directly from Github

To install RTutor and required packages directly from Github and CRAN, you can use the small function in the following gist:

https://gist.github.com/skranz/fad6062e5462c9d0efe4

Copy the code in the link into your R console and then run:

install.rtutor(update.github=TRUE)

Depending on your devtools version, also the following code may work directly (yet source_gist is buggy in some devtools versions):

if (!require(devtools)) 
  install.packages("devtools")

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:

devtools::install_github("skranz/RTutor", upgrade_dependencies=FALSE)

(You may have to restart your R session / RStudio for the update to work.)

Installing and Running RTutor with Docker

If you already use Docker, you can also quickly use RTutor with the docker container skranz/rtutor. The container allows you to work with RTutor via RStudio server in your webbrowser. It already contains some example problem sets, but you can install other problem sets or create your own problem sets. Details are here:

https://hub.docker.com/r/skranz/rtutor/

Since the image contains R, shiny, rstudio and a lot of packages, it has quite some size, however.

Create your own problem sets

Take a look at the files in the vignette folder for documentation of how to create own problem sets.

Suggestions & Feedback

If you have suggestions or find bugs, please don't hesitate to open an issue on this github page. RTutor is still in a preliminary version and feedback is very appreciated.