Try R:

A Gentle Introduction to Using R for Learning Analytics


R is one of the fastest growing open-source programming languages in data science. The growing community of researchers contributing to R has put it in the forefront as a tool for statistical and data science. However, many researchers in learning analytics come from non-programming backgrounds and may find using a programming language such as R to do their research a little intimidating.


This workshop is designed to break down that barrier. Researchers from all backgrounds are welcomed to try R and see if R can make your research even more powerful and efficient than it is right now. The focus of this workshop is not going to be to teach you the fundamentals of R, but rather to give you the tools to decide if learning R is right for you.


We will be exploring the powerful capabilities of R in a learning analytics context by walking you through some of our own completed projects. We'll then let you get your hands dirty working in R on a real-world learning analytics project that will give you a sense of what it is like to do research using R. We will also talk about the amazing resources that are available to learn R so that you can put yourself on the fast-track to using this amazing tool.


This workshop is right for you if:

  • You have been using a GUI based statistical packages such as SPSS, SAS, or STATA, but are wondering if using a programming language such as R can take your research to the next level.
  • You have always been curious about what R can do for your research
  • You would like to explore the advantages of using R.
  • You want guidance regarding the best resources for learning R.
  • You want to get your hands dirty playing with R.


List of Planned Activities (Subject to change):

  • Download and Installation of R and R Studio software
  • We will talk a little about our own research and how we use R to solve our own problems in learning analytics.
  • The workshop will break up into small groups to run prewritten scripts in R on the computers of workshop participants to simulate working through a real-world projects in R.
  • Groups will present their projects and what they learned about R in the process.

About Dr. Jim Cunningham


Dr. Cunningham taught himself R during his PhD program in education at Arizona State University. He uses R to analyze data that students generate when working in online mathematics courses. He currently works as a data analyst at the Action Lab in the online education segment of ASU, EdPlus.



About William Morgan


William is a Research Analyst Associate at the Action Lab and analyzes course design and implementation using learning analytics. He currently studies discussion forum interaction, rubric design, and student activity in online courses. He has also spent time researching the efficacy of online courses.