Stanford Class2Go

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.

[1] http://news.ycombinator.com/item?id=4880112

Also of interest is the urls.py which shows you all the different aspects of the web application. https://github.com/Stanford-Online/class2go/blob/master/main...

Good stuff.

It would be nice if you could separate out the ops infrastructure from the actual application, to suit a wider variety of deployment scenarios.