BD2K-funded MOOC and how it influenced classroom instruction

Rafael A. Irizarry@rafalab

http://rafalab.org

Motivation• I have been teaching data analysis for genomics since

early 2000s

• Course filled with mostly experimental biology postdocs

• These postdocs were becoming data analysts not necessarily by choice

• No formal training and not much time for formal education

Version 1• Data Analysis Launched

April 2014• Lessons learned

– Interest well beyond Genomics

– Too long– Difficulty too varied– Avoid multiple choice– Course centers on

assessments, not videos– More educators than

expected– Use GitHub to organize

material

Curriculum Structure

• Two XSeries:– Data analysis for Life Sciences– Genomics Data Analysis

• Basic module is a 10 minute video followed by 5-10 assessments

• A section has between 3 and 10 modules• Most weeks have 2-3 sections• A course has 4 weeks• A series has 3-4 courses

Screen shot of course 1

Book

Available on Leanpub (free electronic) and Amazon (hard copy)

R markdown on GitHub

Book chapter in RStudio

We are using this approach in residential course

• Lectures are in R markdowns or Rpresorganized on GitHub

• Presented in Rstudio

• Assessments provided every ~15 minutes

• We use google polls to keep track of answers

Data Analysis for Life Sciences XSeries

Genomics Data Analysis Xseries

Enrollment

Total: 235,939

V1 (April 2014 - Dec 2014) 23,512V2 (Jan 2015 - September 2015) 121,908V3 (October 2015 - current) 90,519

~9,000 certificates earned

Multiplicative Effect: Many of our learners are teachers

7700 survey responsesAre you currently, or have

you ever identified yourself as, an instructor/teacher?

37%Are you, or have you ever, taught material related to this course?

20%

Example

Gary and I would like to use your data analysis book as preparatory material for instructional modules for our BD2K grant Curriculum Development and Training for Systems Genetics.

https://projectreporter.nih.gov/project_info_description.cfm?aid=9146069&icde=0

We’ll develop advanced training modules in high throughput sequence analysis, linear mixed models, and genetic mapping/GWAS.

Jeff Chuang has a second BD2K grant to the Jackson Lab that targets faculty at under-resourced undergraduate institutions. He is also interested in using your book in teaching his short course.

https://projectreporter.nih.gov/project_info_description.cfm?aid=9150587&icde=0

-Sue McClatchy Bioinformatician & Research Program Manager, The Jackson Laboratory

Example

This course is amazing, and I use the book and protocols almost every day to work in my hospital, the National Cancer Institute in Mexico. I am teaching all my students based on this course. Thank you so so so so so much for this.

Diddier Prada

Example

I have used the data analysis material in my classes at the Federal University of Pernambuco, Brazil. It has been useful to students in getting degrees, passing exams and qualifying for professional work.

Department of statistics Federal University of Pernambuco Brazil

Example

I'm learning how to make faster and a lot of tricks in your courses. That one is the second one I'm following and I appreciate a lot the training. I'm not using in the university, I'm not a teacher, but I'm using some of the approaches to teach my team in my company and to teach veterinarians using statistics. I'm a supporter of R! With all my best regards, and thanks a lot for this marvellous materials.

Acknowledgements

• Heather Sternshein (HarvardX)• Mike Love (UNC)• Vince Carey (Harvard)• Stephanie Hicks (Harvard)• Jeff Leek, Roger Peng, Brian Caffo (JHU)• NIH R25 HG008275

http://rafalab.org@rafalab

HarvardX MOOC

Example Enrollment Breakdown6/21/16 - 11/17/16

Total for this time period: 42,351R and Statistics: 19,977Linear Algebra: 5,768Inference & Modeling for high-throughput 3,671High-dimensional data analysis: 4,755

Introduction to Bioconductor: 4,030High performance computing: 1,875Case studies: 2,275