Teaching statistics for the future: the MOOC revolution and beyond

1. Who am I?
2. A brief taxonomy and history of online educational models
3. Massive Open Online Courses (MOOCs)
4. JHU Biostat involvement in Coursera
5. Novel moving target directions of the field of statistics
6. Data Science Specialization
7. swirl

• HTML5 using Rstudio presenter
• Appear on github at (https://github.com/bcaffo/MOOCtalk) fork if you'd like
• Jointly written with my collaborators Jeff Leek and Roger Peng
• CC licensed by-nc-sa

• Department of Biostatistics
• Center for Teaching and Learning
• Bloomberg School of Public Health
• Johns Hopkins University
• Coursera
• Team swirl
• Lauren and Ethan (Brian's 2013 interns)
• Contributions from github pull requests
• Tolerant families!
• Over a million intrepid self-learners

SMART (www.smart-stats.org)

resting state fMRI

Primary characteristics are open access, low cost, scalable, online

(every letter is negotiable, from Wikipedia citing Mathieu Plorde)

Important number: production time per hour of video time

• Example from data science inference
• Recent better work

• Portable green screen with lights
• Cintiq 22inch display
• Yeti usb microphone
• Camtasia

Main source for student interaction

(Forums can be brutal)

Original three

• Brian Caffo, Roger Peng, Jeff Leek
• Run 09/2012, 09/2012, 01/2013
  

• Students participate in MOOCs for a variety of reasons
• Numerous students sign up for a course, but do not actively participate
• Recent MBBC 1
  • 17K students
  • 10K accessed the course site ever
  • 7K watched any video ever
  • 2K submitted any quiz
  • 196 earned a SOA
  • 129 signature track ($6k in gross revenue)
  • 128 posted to the forums

• A total of 1,656,654 enrollments
• A total of 92,812 SOAs issued
• 16 Unique classes
• 56 class offerings
• Average of 29,583 students per class.
• Minimum class size of 6,139
• Maximum class size of 101,747

• 2,533,399 enrollmends for Biostat MOOCs
• 138,974 SOAs
• 224,385 Sc
• 85,411 VCs

• Verification based on typing patterns (highly unique according to Coursera)
  • Secondary verification via webcams
• Coursera gives student aid
• Revenue distribution via agreement between Coursera and partner institution
• Much higher retention and completion rates for signature track

Codirected and taught by Roger Peng, Jeff Leek and Brian Caffo

• Everything done on Coursera
• All programming in R
• All lecture notes done in Slidify (common theme)
• Version control through git and github
  • All content open source
  • (Students will learn and use git)
  • All code and data available in slides
• RStudio as an IDE
• knitr for reproducible documents and report writing