Analyzing Education Data with Open Science Best Practices, R, and OSF

By Cynthia D'Angelo, Joshua Rosenberg.
Jan 1, 0001

Edit this page

Data Analysis Tools Education Research Open Data Open Science Open Science Framework OSF Osfr R for Researchers Rstats Statistical Programming

Abstract

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. Access the workshop slides and supplemental information at https://osf.io/vtcak/​.

Resources:

  1. Download R: https://www.r-project.org/​
  2. Download RStudio (a tool that makes R easier to use): https://rstudio.com/products/rstudio/…​
  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/​

Link to resource: https://www.youtube.com/watch?v=WxdWzTIzYmI&t=4s

Type of resources: Teaching/Learning Strategy

Education level(s): Graduate / Professional

Primary user(s):

Subject area(s): Computer Science, Education

Language(s): English