The joint Harvard-MIT venture announced today has significant money ($60m), reputational credibility, and a coherent argument that has been missing from other massive online open course (MOOC) systems: that aggregation of thousands of students in a course can speed up research in higher education learning.
Disruptiness heaven? Not quite: It is not entirely clear what MOOCs are good or bad for. Many observers have seen what appears to be a novelty effect with the first MOOCs from high-status institutions: often, it’s the professionals who know an area who are most visible in a MOOC, not the novices–professionals who may be “taking” the course as much from curiosity as a desire to learn additional material. Other observers have noted the typical problem with the MOOC as correspondence course: it rewards the effective autodidact rather than making effective autodidacts. Even with all the bells and whistles of machine-learning assessment, you have to be motivated without deadlines or peer pressure to finish the next problem set on your own. Yesterday and today, Chronicle of Higher Ed reporter Jeff Selingo has been providing a reality-check on
Ooh-da-city’s Udacity’s utopian dreams (as well as the dreams of other MOOC advocates), and the structure of attending class and being pushed to develop discipline are key themes for the students Selingo interviewed. And I fully expect the bulk of MOOCs to attract not-so-M numbers: I believe Margaret Soltan’s poetry course on Udemy has all of 400-500 “enrollees” — which is far more than can take her George Washington University courses in a semester, but not the 100,000+ enrollments that the MOOC model promises.
Yet I would be careful in separating the obvious hype from the fact that experimentation with MOOCs is going to lead to a great deal of information on what works well in this format, what is possible but tricky, and what is truly horrible. Better yet, this experimentation is happening when all the
guinea pigs participants are giving up is their time and energy, not thousands of dollars. Audrey Watters may have quit Udacity’s computer science course halfway through, but she didn’t go $30,000 into debt for that experience.
My best guess is that the MOOC model will work well in three cases:
- Courses that become a cultural experience, such as Jim Groom’s Digital Storytelling 106 (or DS106 as taken over by students). These will be idiosyncratic, fairly rare, and quite wonderful if DS106 is any indication of the possibility.
- Technical/technique-oriented courses where there are sufficient enrollments to drive some interesting experiments in online education (i.e., random controlled experiments in tweaking an online course). Computer science and programming are early courses in MOOC systems not only because the developers are … er, in programming but also because you can create auto-graders for code problems more easily than for, say, poetry analysis. Imagine the introductory lecture class on steroids, and you’re fairly close.
- Courses that never make the M (massive) in MOOC but provide presentation material that is interesting and valuable in its own right, as in Margaret Soltan’s lectures for her poetry class. In this last category, MOOCs will be just another source of lecture material, alongside Youtube and iTunes U.
There is also the likelihood of some real dogs in the world of MOOC, probably the majority of courses. That’s life with experimentation. And it leaves plenty of room for standard face-to-face classes. It will be very interesting to watch the development…