This is Part IV of our Causal Impact @ Coursera series. (Part III is here)

At Coursera we use data to power strategic decision making, leveraging a variety of causal inference techniques to inform our product and business roadmaps. In this causal inference series, we will show how we utilize the following techniques to understand the stories in our data:

(1) controlled regression

(2) instrumental variables

(3) regression discontinuity

(4) difference in difference

This fourth and final post in the series covers an application of difference in difference to understand the impact of course updates on completion rate.

Since 2012, Coursera has enabled access to open and online courses that help learners from around the world learn without limits. As we’ve grown, technology has too, and new tools and skills emerge everyday. With over 75 million registered learners and over 5,000 pieces of content, it’s important for us to support our instructors and partners in incorporating job-relevant skills and the best pedagogical practices into their courses. …

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