Autograding R data science assignments in CodeGrade

Autograding R scripts

It is also possible to autograde entire R scripts using CodeGrade, either using standard input or by specifying exactly what the scripts should produce (without input). In our example, we tell the students to create a script `fibonacci.R` that prints the first 10 numbers of the fibonacci sequence. 

Grading the correctness of this script can be done with a very simple I/O Test in CodeGrade again. This time, we just have to run `Rscript fibonacci.R`. This runs the R script the student has uploaded. Since we do not need to give any input, we can leave the input arguments and input fields empty and just define an expected output, which is [1] 1 1 2 3 5 8 13 21 34 55 in our case.

Installing R packages in CodeGrade

In the examples above we discussed a very basic R assignment, but most advanced data analysis assignments will require students to make use of the various useful R libraries available. It is possible to install these packages in CodeGrade very easily. Packages can be installed directly by the student in their uploaded R script or beforehand by you in the configuration of AutoTest.

For both these methods, it is required to set up a directory for the user library (in R that is the `R_LIBS_USER` environment variable). After creating this directory correctly, you can install packages to this user in the regular way (and you do not need to run code with `sudo`). You can upload the following script called `setup.R` as a fixture and run it in the Global Setup Script using `Rscript $FIXTURES/setup.R`. Optionally, you can also already install required packages in this script:

-!- CODE language-r -!-UserLib=Sys.getenv("R_LIBS_USER")
dir.create(UserLib, recursive=TRUE)
install.packages(c("tidyr"), lib=UserLib)

After running at least the first two lines of the above script, students can also install R libraries directly in their scripts uploaded to CodeGrade using the regular `install.packages("PACKAGE")` line. Please note that if you want to allow students to install packages themselves using this method, you need to enable internet access for them in the categories you test their code in. Optionally, you may also increase the timeout of the steps, as installing R packages can take quite some time.

Both of these methods have their pros and cons. Letting your students install their own libraries allows for more freedom, but results in a longer wait before students get their automatic feedback (as we have to wait for the libraries to install). Installing these libraries up front moves that waiting time up front and will remove this for most instant feedback runs, however, you will need to know exactly which libraries students will use.

Checking R code plagiarism in CodeGrade

With the increasing popularity of data science courses, it is also more and more important to check for plagiarism in R programming assignments. Checking plagiarism in R scripts is easy and straightforward using CodeGrade. After your students have handed in their files, simply navigate to the plagiarism checker tab and select R as your language. You now even get the option to include previous assignments or upload base code that you have provided to your students.