Analyzing Education Data with Open Science Best Practices, R, and OSF
This workshop demonstrates how using R can advance open science practices in education. We focus on R and RStudio because it is an increasingly widely-used programming language and software environment for data analysis with a large supportive community. We present: a) general strategies for using R to analyze educational data and b) accessing and using data on the Open Science Framework (OSF) with R via the osfr package. This session is for those both new to R and those with R experience looking to learn more about strategies and workflows that can help to make it possible to analyze data in a more transparent, reliable, and trustworthy way.
1) Download R: https://www.r-project.org/
2) Download RStudio (a tool that makes R easier to use): https://rstudio.com/products/rstudio/download/
3) R for Data Science (a free, digital book about how to do data science with R): https://r4ds.had.co.nz/
4) Tidyverse R packages for data science: https://www.tidyverse.org/
5) RMarkdown from RStudio (including info about R Notebooks): https://rmarkdown.rstudio.com/
6) Data Science in Education Using R: https://datascienceineducation.com/