gapdata/rtutor

Creating R exercises with automatic assement of student's solutions

Tutorial for Developing Interactive R Problem Sets with RTutor

**Date: 2015-01-23

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

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)

• Github: https://github.com/Fcolli/RTutorProcurementAuction
• shinyapps.io: https://fcolli.shinyapps.io/RTutorProcurementAuction

Assessing Free Trade Agreements (by Tobias Fischer)

• Github: https://github.com/fischeruu/RTutorNAFTAfreetrade
• shinyapps.io: https://fischeruu.shinyapps.io/RTutorNAFTAfreetrade/

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

• Github: https://github.com/ClaraUlmer/RTutorSoapOperas
• shinyapps.io: https://claraulmer.shinyapps.io/RTutorSoapOperas

CO2 Trading and Risk of Firm Relocation

• Github: https://github.com/b-lux/RTutorCarbonLeakage
• shinyapps.io: https://b-lux.shinyapps.io/RTutorCarbonLeakage/

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

• Github: https://github.com/JonasSend/RTutorTopIncomeTaxation
• shinyapps.io: https://jonassend.shinyapps.io/RTutorTopIncomeTaxation/

Air pollution and house prices (by Moritz Sporer)

• Github: https://github.com/msporer/RTutorEnvironmentalRegulation
• shinyapps.io: https://msporer.shinyapps.io/RTutorEnvironmentalRegulations/

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

• Github: https://github.com/tcl89/creditboomsgonebust
• shinyapps.io: https://tcl89.shinyapps.io/creditboomsgonebust

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

• Github: https://github.com/MariusBreitmayer/RTutorAttributeTradeOffs
• shinyapps.io: https://mariusbreitmayer.shinyapps.io/RTutorAttributeTradeOffs

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

• Github: https://github.com/skranz/RTutorBankRuns

Installing the newest version of RTutor

Since RTutor uses a lot of packages from Github that are not on CRAN, I have written a small install function, that can be found in this 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")
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.)

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.