Teaching R
Buy me a coffeeHere I added resources aimed exclusively for other people who are teaching R.
Data Science in a Box
What is it?
Excerpt from site: The core content of the course focuses on data acquisition and wrangling, exploratory data analysis, data visualization, inference, modelling, and effective communication of results. Time permitting, the course also introduces additional concepts and tools like interactive visualization and reporting, text analysis, and Bayesian inference. Data Science in a Box contains the materials required to teach (or learn from) the course described above, all of which are freely-available and open-source. They include course materials such as slide decks, homework assignments, guided labs, sample exams, a final project assignment, as well as materials for instructors such as pedagogical tips, information on computing infrastructure, technology stack, and course logistics.
- Link to site: https://datasciencebox.org/
- Link to repo: https://github.com/rstudio-education/datascience-box
How I Teach R Markdown
By Alison Hill
What is it?
Excerpt from blog: So without further ado, here are some of my guiding principles when introducing R Markdown to beginners, for those who are ready to go beyond casual knitter:
How to prepare and teach an R lesson
By Monica Thieu
What is it?
Excerpt from blog: This blog post contains a written version of my speaker notes for my 20-minute 2020 NYC R conference talk. Since the talk time is on the shorter side, I trimmed a few things out of the talk that I would have liked to include with more time. The speaker notes for the unabridged version are included here for your reference.
PsyTeachR
What is it?
Excerpt from website: The psyTeachR team at the University of Glasgow School of Psychology and Institute of Neuroscience and Psychology has successfully made the transition to teaching reproducible research using R across all undergraduate and postgraduate levels. Our curriculum now emphasizes essential ‘data science’ graduate skills that have been overlooked in traditional approaches to teaching, including programming skills, data visualisation, data wrangling and reproducible reports. Students learn about probability and inference through data simulation as well as by working with real datasets.
This website contains our open materials for teaching reproducible research. Levels of
- Level 1: Grassroot- https://psyteachr.github.io/ug1-practical/
- Level 2: Practical- https://psyteachr.github.io/ug2-practical/
rstudio4edu A Handbook for Teaching and Learning with R and RStudio
By Desirée De Leon & Alison Hill
What is it?
Excerpt from handbook: This handbook was inspired by the Handbook for Teaching and Learning with Jupyter- a book written by and for educators who teach data science. It is a thoughtful and inspiring resource for all educators, with a focus on the Python ecosystem. We aimed to create a similar resource for educators working with the R and RStudio ecosystem.
- Link to handbook: https://rstudio4edu.github.io/rstudio4edu-book/
Teaching Research Methods in R
What is it?
Excerpt from site: This is a crowd-sourced list of uses of R to teach research methods in Psychology, and a link to Creative Commons teaching materials, where these are available. The year teaching in R was adopted at undergraduate and postgraduate level is also recorded, where known. Where there are no materials, but the organization’s name has a link, this is a link to evidence that R is used.
- Link to list here: https://ajwills72.github.io/rminr/rminrinpsy.html
Tidy Data Tutor
Added Fri Feb18, 2022
What is it?
Tidy Data Tutor lets you write R and Tidyverse code in your browser and see how your data frame changes at each step of a data analysis pipeline. (If you use Python, check out Pandas Tutor.)
- Link to R tutor: https://tidydatatutor.com/
- Link to Python tutor: https://pandastutor.com/