This is intriguing: Professors have access to the classes' data to learn how their students learn. We will facilitate experiments. For example, we intend this

This is intriguing: Professors have access to the classes' data to learn how their students learn. We will facilitate experiments. For example, we intend this to be the best plaform for running A/B/N tests to measure the impact of different teaching methods on student outcomes That they're giving data driven decision making such a prominent place is great. I would like to know more, though. Having taught before at the University level I know it's a ton of work. It's even more work if you're developing parallel versions of a course for testing purposes. So the A/B feature had better be really easy to use. There is also the ethical issue of giving students a worse performing variant of the class. The solution here is to use a bandit algorithm or an early stopping method to find the best variant as quickly as possible. Finally, I think the Coursera model where everyone runs through the course on the same schedule is not optimal for experimentation. It doesn't allow for a tight feedback loop, because you have to wait N weeks before you can experiment with changes on the next cohort.