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MOOCs: The Tacit Prerequisites

February 26, 2013

I was excited about MOOCs. I am excited about MOOCs. In fact, I have been gorging myself on MOOCs recently. I dabbled in some Udacity courses two semesters ago, checked out some free courses from Udemy’s Faculty Project, finished up a Coursera course on Social Network Analysis last semester, and have spent a few late nights recently hammering out Data Analysis assignments.

But I have reservations. Because MOOCs aren’t exactly the broad public service that I had expected they would be, nor are they necessarily headed in that direction.

These classes have a lot of tacit–or perhaps just unexamined–assumptions of the skills that students are coming in with. The pessimist (or realist) in me wants to say that, unless you’ve already got a pretty decent undergraduate foundation in whatever MOOC you’ve signed up for, you’re going to quickly fall through the cracks. As a MOOC student, the onus of getting from point A to point B in these classes has fallen squarely on my shoulders. And overall, that has been fine for me. I have dropped out of those courses I felt underqualified for, and have stuck to it with those that have felt closer to my “zone of proximal development”.

But I am a graduate student, and I have a pretty broad array of (physical classroom-based) courses already under my belt. If I were an English major hoping to expand my math skills, a high school student poking around to get exposure to college-level work, a GED-earner trying to decide if college is right for me, or a late-career professional looking to shift my field of work, I would likely be somewhat lost in the MOOC jungle. Because MOOCs help you get better at the stuff you already sort of know.

Currently, the MOOC platforms I’ve seen very much replicate a lecture hall style of content delivery. Some have bells and whistles for auto-correcting assignments (which may break on occasion *cough* Udacity *cough*), some have peer assessments, but most are simply a set of video lectures and a set of associated quizzes. The main “constructivist” moment of most of these courses is the discussion forums. The MOOC discussion forums I’ve experienced offer some handy “how-to” support on occasion, but they currently read more like online user forums and are not the same kind of agile “give-and-take” that a face-to-face discussion section or study group offers. The students who end up contributing to the forums I’ve been involved in seem to be a small subset of more advanced participants, and their manners are mixed: some are sympathetic and have a decently pedagogical sense of how to frame advice and hints for others who aren’t as experienced in the topic. Some are more advanced in the subject at interest and will brook no fools: they often treat the discussion boards more like user forums (i.e. getting irrationally upset when someone posts in the “wrong” thread). It’s an interesting culture clash, to say the least.

So, you wanna make it through a MOOC? The tacit prerequisites for succeeding in MOOCs, as I’ve experienced them so far:

  • Know how to Google, and be proactive about doing it. The MOOCs I’ve looked at aren’t exactly “self-contained”: they’re often just a vehicle to point you towards concepts you should Google and explore on your own. It also helps to understand the structure and etiquette of large-scale discussion forums–something which will likely be familiar to MOOC students with a strong technology background, but may be unfamiliar to those who haven’t perused or participated in online user forums before.
  • Have copious prereqs. In the MOOCs I’ve worked on, I can pinpoint what has led me to drop out or stick with it–and it usually comes down to the match or disconnect between the MOOC content and my prior experience with the subject. In Udacity’s Web Development course, for example, I stopped showing up to watch the video lectures when I got frustrated for not knowing enough about Python programming to keep up. In Coursera’s Computing for Data Analysis and Data Analysis, on the other hand, I’ve stuck around, but relied heavily on prior knowledge I gleaned from Intro to Computer Science and a pretty rigorous Economics class I took as an undergrad, as well as a doctoral-level stats class I’ve taken as a master’s student. Not exactly a low barrier to entry, if you ask me…
  • Expect content, not pedagogy. Some of the video lectures have read more like a text book–spouting off terms and definitions before we have any context through which to process it. Problem-based learning is rare, and instructors don’t always give sufficient context to frame the topic for more general audiences. So for now, expect a content-driven approach, and expect to spend time on your own filling in the gaps through your own support network, or via good ol’ Google.
  • Get a kick out of small incentives. The tangible rewards for MOOCs are minimal–unless you’re a huge sucker for a PDF certificate at the end of a class (which, admittedly, I am). Also, most MOOCs are currently set up to require a relatively consistent (usually weekly) time commitment. So, if you’re the kind of person where weekly quizzes help keep you on track, you’re good to go!

So you want to teach a MOOC? Here are my suggestions–or rather, my humble plea–from my own perspective as a MOOC learner:

  • Design for mixed audiences. Structure the course around “conceptual knowledge” that is necessary for all students and that is central to the topic/field at hand. Then be sure to ground these conceptual discussions in copious real-world examples and problem scenarios that will be familiar to nearly everyone. Any good MOOC needs to ask itself: “What would I want students to get from this course in order to become more informed citizens in this world?” And then teach to that! Because, if MOOCs are going to serve a broader societal purpose, they need to speak to a “general interest” audience rather than a group of geeky graduate and post-doc students with too much free time on their hands. For a positive example of a course that balances the demands of geekdom while also focusing on “big picture” real-world examples that help non-specialists still get at the meat of the subject, I’d recommend having a look at Lada Adamic’s Social Network Analysis .
  • Build in flexibility. In line with designing for mixed audiences, instructors can offer occasional challenge problems or assignments for students who want to delve into more advanced skills. In this respect, Jennifer Windom’s Introduction to Databases is a decent model, offering additional quizzes and challenge exercises to Stanford students who are taking the class for credit, as well as those (masochistically-minded?) MOOC students who simply get a kick out of mastering increasingly complex types of database queries.
  • Feature instructors who cannot only talk, but explain. I would argue that MOOCs demand a pretty high level of cognitive complexity from their “expert” instructors. A good MOOC instructor has to distill their subject into what “non-experts” should walk away with, and gain new language for how to present their subject to a more general audience. All in all, not a bad cognitive challenge for academics! The problem? Nearly every professor already thinks they can pull this off. A good test? Have your potential MOOC professor head to a 7th-grade classroom and try to pitch her first few lectures there. If it works and the students learn–sign her up to teach a MOOC! Jeff Leek’s Data Analysis is a good example of an instructor who knows how to frame the “narrative arc” of a course effectively. Although I’d argue that his videos run a little long, and the technical requirements of the course aim too high to be of much use to a non-technical audience, Leek is smart about explaining his subject systematically, and making consistent use of real-world examples.
  • Leverage the power of peers. I’ll admit I was a little skeptical when I first learned of MOOCs incorporating peer grading into assignments. It seemed like an awkward solution to get around the MOOC reality of having a professor who is massively outnumbered by her students. But as it turns out, one of the most powerful learning experiences I’ve had in a MOOC so far was the opportunity to get graded by a group of my peers. The structure was key: we first had to submit our assignments, then we had a week-long period where we were asked to review work from at least 4 fellow students. Only after looking at our peers’ work were we asked to go back and self-assess our own work. The result? I noticed loads of things I’d overlooked in my original assignment and left with clear ideas of how I could improve in the future. And in the end, I was shocked to discover that my self-assessment scores only differed from my peers’ ratings of my work by about .5 points on any given rubric item! All in all, a humblingly awesome educational moment.

In the end, I believe MOOCs are making it painfully apparent that “good teaching is good teaching”–regardless of whether it’s happening online or in a physical classroom. Knowing where students are starting from, and pushing them to new levels of complexity is a perpetual pedagogical challenge, and no MOOC “magic” will resolve that.

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