Becoming Part of a MOOC's Solar System

Last summer I started producing my own videos on artificial intelligence (AI) topics. These were low tech, voice-over Powerpoint slideshow presentations, with post-production with iMovie on my Mac. I posted the videos to supplement videos by other people that I was using for my Fall 2012 AI course -- mostly videos by Thrun and Norvig, Daphne Koller, and a few others. My videos often adapted the slides accompanying the free textbook I use by Poole and Mackworth (http://artint.info/html/ArtInt.html) under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 license.

Shortly into the Fall semester,  comments started being left by students of a UC Berkeley AI MOOC that was being offered through edX (https://www.edx.org/). The first views were for a constraint satisfaction video, then later my biggest hit of all, for a video on iterative deepening depth first search! After getting favorable comments for the first of these by students who commented that my video had helped them with the Berkeley MOOC, I went to the MOOC's discussion board and verified that students had left a link there, which had been endorsed by others.

Since then I've posted a few other videos for my database course in Spring 2013. The B+ tree videos are a "hit", though still small potatoes by MOOC standards.

I haven't been able to produce many videos, but I have been getting a high proportion of likes and followers. It's neat.

This experience has made me conscious that there are many resources that students access outside the recognized boundaries of a course, be it online or a good old-fashioned face-to-face class. I can remember finding some astoundingly good videos, each with many thousands of views, mainly in math, produced by "amateurs", including high school and college students, as well as faculty members at various places. I remember watching quite a few good calculus videos one day in 2008 from the Arlington library. The experience was eye-opening -- there were great educational resources on the Web that students were using, and I wanted to add to these resources! There are sites like TeachingTree (http://www.teachingtree.co/), that co-locate educational video resources of based on shared concepts, allowing "the crowd" to vet quality.

I'm most intrigued by the ad hoc community that grows around a course, notably a MOOC. This isn't a stable long-term community like the collection of my Facebook friends, or a Facebook group. Rather, the participants come together because of the MOOC, participating in a shared activity. Moreover -- and this is the most interesting part, I think -- the ad hoc community extends beyond the boundaries of the MOOC itself. By virtue of my videos, for example, I was part of the larger community of the Berkeley AI MOOC. (I've used the expression "ad hoc" communities because the communities that grow around a MOOC seem analogous to what Larry Barsalou called "ad hoc concepts/categories")

I like the metaphor of a solar system, with the MOOC as a center of gravity, and other resources, like YouTube videos, brought into orbit around the MOOC. I could actually make this a truer metaphor by very strategically examining the MOOC (e.g., the Berkeley AI MOOC and/or the Udacity AI MOOC that I just signed up for), with an eye towards identifying those sections of the MOOC(s) that I am sure that some students will have trouble with or those sections that students actually identify as difficult on the MOOC discussion board, and producing remedial videos on those topics. Such strategically-produced videos would be very much in the MOOC's orbit, left there very deliberately by me.

Longitudinal studies for understanding the nature, extent, and evolution of ad hoc communities, typically MOOC centered but not restricted to a single MOOC, undoubtedly require data mining across larger spheres of Web interactions than is currently easy to do (for anyone other than Google and a few others, that is). Nonetheless, the possibilities for understanding and leveraging student patterns in seeking remedial and advanced material, instructor incentives for creating and posting material, and the movement of people between student and teacher roles, are exciting and probably within current technical abilities – if only the data could be accessed. Currently, data mining of student behavior within a MOOC is the norm, but behavior that extends outside the MOOC isn't tracked.