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Last Fall, three Stanford classes were “offered online” for free: Andrew Ng’s machine learning class, Sebastian Thrun’s AI class, and Jennifer Widom’s data base class. There had been interest and experiments in online free education for a long time, with the MITx initiative being a particularly significant one, but there were a few innovations in last year’s Stanford classes, and they probably contributed to their runaway success and six-digit enrollment.

One difference was that they did not post videos of the in-class lectures. There was, in fact, no in-class lecture. Instead, they taped short videos, rehearsed and edited, with the content of a standard 90-minute class broken down in 4 ten-minutes video or so. This is about the difference between taping a play and making a movie. Then the videos came with some forms of “interactivity” (quizzes that had to be answered to continue), and they were released at the rate in which the class progressed, so that there was a community of students watching the videos at the same time and able to answer each other’s questions in forums. Finally, the videos were used in the Stanford offerings of the classes: the students were instructed to watch the videos by themselves, and during the lecture time they would solve problems, or have discussions or have guest lectures and so on. (In K-12 education, this is called the “flipped classroom” model, in which students take lectures at home and solve homeworks in class, instead of the traditional other way around.)

In the past few months, there has been a lot of thinking, and a lot of acting, about the success of this experiment. Sebastian Thrun started a company called udacity to offer online courses “branded” by the company itself, and Daphne Koller and Andrew Ng started a company called coursera to provide a platform for universities to put their courses online, and, meanwhile, Harvard and Berkeley joined MIT to create edX.

At a time when the growth of higher education costs in the United States appear unsustainable, particularly in second-tier universities, and when the demand for high-quality higher education is exploding in the developing world, these projects have attracted a lot of interest.

While the discussion has been focused on the “summer blockbusters” of higher education, and what they should be like, who is going to produce them, how to make money from them, and so on, I would like to start a discussion on the “art house” side of things.

In universities all over the world, tens of thousands of my colleagues, after they have “served” their departments teaching a large undergraduate classes and maybe a required graduate class, get to have fun teaching a research-oriented graduate class. Their hard-earned insights into problems about which they are the world’s leading expert, be it a particular organ of the fruit fly or a certain corner of the Langlands program, are distilled into a series of lectures featuring content that cannot be found anywhere else. All for the benefit of half a dozen or a dozen students.

If these research-oriented, hyper-specialized courses were available online, those courses might have an audience of 20 or 30 students, instead of 100,000+, but their aggregate effect on their research communities would be, I believe, very significant.

One could also imagine such courses being co-taught by people at different universities. For example, imagine James Lee and Assaf Naor co-teaching a course on metric embeddings and approximation algorithms: they would devise a lesson plan together, each would produce half of the videos, and then at both NYU and UW the students would watch the videos and meet in class for discussions and working on problems; meanwhile study groups would probably pop up in many theory groups, of students watching the videos and working on the problem sets together.

So someone should put a research-oriented graduate course online, and see what happens. This is all to say that I plan to teach my class on graph partitioning, expander graphs, and random walks online in Winter 2013. Wish me luck!



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