So the reality is, very few lecturers are going to create a course that will be delivered to 155K students, and if they succeed in going viral, the drop out rate is likely to be very high. The course Google ran issued 22K certificates, indicating a drop out rate of 85%. Its still an impressive number when many campuses are no where near that size however, most institutions would not survive with that level of drop out and all would be looking at ways of reducing it. Institutions invest more in their students and so need lower levels of drop out. As a result, their courses are smaller, they don’t have the economies of scale and can’t invest as much in the delivery of each individual course. All is not lost however, the opportunity that Googles CourseBuilder represents could be utilized if there was a small reduction in effort associated with course creation and course delivery.
The video attached to this blog post shows how that might be achieved. This is a modified version of Google CourseBuilder that allows a single Google App Engine to host more than one course. It could easily host a course catalogue from an small institution or medium size faculty. That course catalogue is uploaded via a spreadsheet. Individual courses containing units and lessons are also uploaded via seperate spreadsheets.
Students sign in using their Google ID, Google Apps for Education ID, or OpenID. They then register with the the courses they want to take. If you want to give it a try there is a App Engine Instance running at http://cbmultidemo.appspot.com/, bear in mind its a free instance so may become unavailable.
At the moment the administrative interface is very basic, but the intention is to build that up to allow courses to be created without needing to resort to technical resources. So far I have spent about 4h eliminating most of the code base editing and adding multi course capability. The code base is available as a fork of the Google CourseBuilder project and can be deployed by anyone with a Google ID. Since the original code was written in Python, using a modern variant of the GAE framework porting to Django would be trivial with those who have concern about running on Google infrastructure. Obviously in doing so, you will have to work out how to do the scaling, see Instagram for pointers on that.