R4DS Data Science in Education Using R Book Club

Welcome to the R4DS Data Science in Education Using R Book Club!

We are working together to read Data Science in Education Using R by Ryan A. Estrellado, Emily A. Bovee, Jesse Mostipak, Joshua M. Rosenberg, and Isabella C. Velásquez. Join the #book_club-ds_in_education_using_r channel on the R4DS Slack to participate. As we read, we are producing notes about the book and saving them in this bookdown.

Meeting Schedule

If you would like to present, please add your name next to a chapter using the GitHub Web Editor!

Cohort 1: (starts 2021-02-10) - Wednesdays, 5pm EST/EDT

• 2021-02-10: Chapters 1-2: Introduction and How to Use this Book: Isabella Velásquez and Ryan Woodbury
• 2021-02-17: Chapter 03. What does Data Science in Education Look Like?: Rob Lucas
• 2021-02-24: Chapter 04. Special Considerations: Ryan Woodbury
• 2021-03-03: Chapter 05. Getting Started with R and RStudio & Chapter 06. Foundational Skills: Mark LaVenia
• 2021-03-10: Chapter 07. Walkthrough 1: The Education Data Science Pipeline With Online Science Class Data: Yukie Toyama
• 2021-03-17: Chapter 08. Walkthrough 2: Approaching Gradebook Data From a Data Science Perspective: Morgan Grovenburg
• 2021-03-24: Chapter 09. Walkthrough 3: Using School-Level Aggregate Data to Illuminate Educational Inequities: Alyssa Ibarra
• 2021-03-31: Chapter 10. Walkthrough 4: Longitudinal Analysis With Federal Students With Disabilities Data: Isabella Velásquez
• 2021-04-07: Chapter 11. Walkthrough 5: Text Analysis With Social Media Data: Layla Bouzoubaa
• 2021-04-14: Chapter 12. Walkthrough 6: Exploring Relationships Using Social Network Analysis With Social Media Data: Carlo Medina
• 2021-04-21: Chapter 13. Walkthrough 7: The Role (and Usefulness) of Multilevel Models: Presenter(s) Mike Haugen
• 2021-04-28: Chapter 14. Walkthrough 8: Predicting Students’ Final Grades Using Machine Learning Methods with Online Course Data: shamsuddeen
• 2021-05-05: Chapter 15. Introducing Data Science Tools To Your Education Job: Presenter(s)
• 2021-05-12: Chapter 16. Teaching Data Science: Presenter(s)
• 2021-05-19: Chapter 17. Learning More: Presenter(s)
• 2021-05-26: Chapter 18. Additional Resources: Presenter(s)
• 2021-06-02: Chapter 19. Conclusion: Where to Next?: Presenter(s)

How to Present

This repository is structured as a {bookdown} site. To present, follow these instructions:

1. Setup Github Locally
2. Fork this repository.
3. Create a New Project in RStudio using your fork.
4. Create a New Branch in your fork for your work.
5. Edit the appropriate chapter file. Use ## to indicate new slides (new sections).
6. If you use any packages that are not already in the DESCRIPTION, add them. You can use usethis::use_package("myCoolPackage") to add them quickly!
7. Commit your changes.
8. Push your changes to your branch.
9. Open a Pull Request (PR) to let us know that your slides are ready.

When your PR is checked into the main branch, the bookdown site will rebuild, adding your slides to this site.