This is a repository for:
An Introduction to Data Science in Education in Education Using R Thursday, 9/4, 9:30 - 11:30
R is a freely-available, cross-platform, open-source programming language and statistical software environment that is well-suited to data analysis and data science, but, can have an high barrier to entry. This workshop provides an introduction to R in education, with a focus on developing a foundation in capabilities (and confidence!) that can be applied in a variety of data analysis contexts. Most of the time will be spent on developing the following skills: a) Getting started with R Studio, b) Visualizing (with the ggplot2 R package), processing (with dplyr), and modeling data and presenting results (using a regression model and apatables), c) Creating reproducible reports using R Markdown and papaja. There are not prerequisites, though, to get the most from the workshop, please bring your own laptop computer with you with R and R Studio installed (instructions below).
If you have issues with any of the installations below (and don’t worry, they’re all very small and won’t take up much space on your computer) please contact me (jmrosenberg@utk.edu) and I can try to work with you to get it resolved before the workshop. If we’re unsuccessful, at least we know from the start of the workshop that we’ll need to work with you to get up to speed.
To download R:
- Visit this page to download R: https://cran.r-project.org/
- Find your operating system (Mac, Windows, or Linux)
- Download the 'latest release' on the page for your operating system and download and install the application
To download R Studio:
- Visit this page to download R studio: https://www.rstudio.com/products/rstudio/download/
- Find your operating system (Mac, Windows, or Linux)
- Download the 'latest release' on the page for your operating system and download and install the application
The slides are here: https://jrosen48.github.io/mtsu-workshop/
demo-doc.Rmd is an interactive R Markdown file that accompanies the presentation.
An R Studio Cloud workspace/environment for the demo-doc.Rmd document in this repository is availabile here: https://rstudio.cloud/project/486640
This may be especially helpful if you do not yet have R and R Studio installed on your computer. It does require you to create an account or to use a Google (or GitHub) account to sign-in.
Thank you to Emily Bovee for developing the workshop this workshop is adapted from: https://github.com/jrosen48/MTSU-workshop
Parts of the content for this workshop are adapted from:
- The (in-development) Data Science in Education book
- An American Educational Research Association 2019 annual meeting workshop on Reproducible and transparent research with R
Parts of the content for this workshop are inspired from content associated with the Data Science Specialization for UO COE (led by Daniel Anderson)