Data Science in Education Using R Book Club
Welcome
Book club meetings
1
Introduction and How to Use this Book
1.1
Slides
1.2
Meeting Videos
1.2.1
Cohort 1
2
What does Data Science in Education Look Like?
2.1
Slides
2.2
Meeting Videos
2.2.1
Cohort 1
3
Special Considerations
3.1
Slides
3.1.1
Resources Shared
3.2
Meeting Videos
3.2.1
Cohort 1
4
Getting Started with R and RStudio & Foundational Skills
4.1
Slides
4.2
Meeting Videos
4.2.1
Cohort 1
5
Walkthrough 1: The Education Data Science Pipeline
5.1
Slides
5.2
Meeting Videos
5.2.1
Cohort 1
6
Walkthrough 2: Approaching Gradebook Data From a Data Science Perspective
6.1
Slides
6.2
Meeting Videos
6.2.1
Cohort 1
7
Walkthrough 3: Using School-Level Aggregate Data to Illuminate Educational Inequities
7.1
Slides
7.2
Meeting Videos
7.2.1
Cohort 1
8
Walkthrough 4: Longitudinal Analysis With Federal Students With Disabilities Data
8.1
Slides
8.2
Meeting Videos
8.2.1
Cohort 1
9
Walkthrough 5: Text Analysis With Social Media Data
9.1
Slides
9.2
Meeting Videos
9.2.1
Cohort 1
10
Walkthrough 6: Exploring Relationships Using Social Network Analysis With Social Media Data
10.1
Slides
10.2
Meeting Videos
10.2.1
Cohort 1
11
Walkthrough 7: The Role (and Usefulness) of Multilevel Models
11.1
Slides
11.2
Meeting Videos
11.2.1
Cohort 1
12
Walkthrough 8: Predicting Students’ Final Grades Using Machine Learning Methods with Online Course Data
12.1
Slides
12.2
Meeting Videos
12.2.1
Cohort 1
13
Teaching Data Science
13.1
Slides
13.2
Meeting Videos
13.2.1
Cohort 1
14
Introducing Data Science Tools To Your Education Job
14.1
Slides
14.2
Meeting Videos
14.2.1
Cohort 1
15
Learning More, Additional Resources, and Conclusion: Where to Next?
15.1
Slides
15.2
Meeting Videos
15.2.1
Cohort 1
Published with bookdown
Data Science in Education Using R Book Club
Chapter 13
Teaching Data Science
Learning objectives:
Pedagogical features embedded within the book
Teaching data science
Overcoming barriers to doing data science