Learning from MOOCs
MOOCs seem to be gathering a lot of media attention lately, particularly on the heels of the popularity of Stanford's AI class. But how do these new computer-scienc
MOOCs. They're all the rage these days, it seems -- so much so I'd make them an early pick for one of the major ed-tech (startup) trends for 2012. Of course, describing MOOCs as an "ed-tech startup trend" and associating it with 2012 overlooks the history of Massive Open Online Courses that's not associated with Silicon Valley startups -- heck, that's not associated with Silicon Valley at all.
But it's the story of the "success" of the Stanford Artificial Intelligence class last fall that seems to dominate the mainstream narrative surrounding MOOCs. The 160,000 students that enrolled in Peter Norvig and Sebastian Thrun's class was certainly a watershed moment -- most of all for Thrun, who announced at the DLD conference in Munich that he couldn't go back to teaching at Stanford and was founding his own online education startup, Udacity.
The "this changes everything!" excitement about MOOCs is echoed in the media, no doubt. Take the recent description in The New York Times, for example: "Welcome to the brave new world of Massive Open Online Courses -- known as MOOCs -- a tool for democratizing higher education. While the vast potential of free online courses has excited theoretical interest for decades, in the past few months hundreds of thousands of motivated students around the world who lack access to elite universities have been embracing them as a path toward sophisticated skills and high-paying jobs, without paying tuition or collecting a college degree."
So here are the ingredients for "democratizing higher education" according to the NYT: access to the Internet, a lack of access to elite universities, motivation. Then you're off and running on a "path toward sophisticated skills and high-paying jobs." Considering that the Stanford MOOCs and those offered by Udacity and now MITx all focus on computer science-related courses, that seems to be the focus.
For those that have participated in earlier MOOCs -- particularly those offered by professors outside Silicon Valley and outside the CS department -- the new MOOCs might feel like a different beast altogether. Indeed, at a recent SXSW panel on massive online learning communities, P2PU director Phillip Schmidt called this the "parallel reality" of MOOCs. There is a certain "through the looking glass feel" to the discussions of MOOCs when they focus just on the Stanford experiments, too. As George Siemens has argued in a recent post/presentation,
Our MOOCs value ontology first and epistemology second. We have an ideology of developing learners who create and share artifacts of their learning, control their own learning, and own their own spaces of learning. In the process, we emphasize social networked learning (connectivism). We make sense of complex knowledge by connecting to others, creating and making “stuff”, and engaging in discourse and interacting with the ideas of others. The Stanford MOOCs are more traditional as they emphasize knowledge development not ontological development. The primary innovation of these MOOCs relates to scale and economics: the numbers of learners that can take a course (currently for no fee, but I think that will be short-lived).
I'd classify myself as more of a lurker-learner than active participant in MOOCs right now (hey, I'm busy!). I am tracking on LAK12, Change11, and DS106, and I'm trying to stay up-to-date with Udacity's CS101. As such, I was interested in the analysis offered by Osvaldo Rodriguez, who compares participation and lurking in the Stanford AI class and in the EduMOOC. While both courses saw a massive drop-off in the number of original registrants and active participants, he contends that there are a significant amount of lurkers in the latter class -- those who follow along but don't necessarily post or participate. In the Stanford AI class, there wasn't the same sort of opportunity to really lurk as if you didn't do the weekly quizzes, you were effectively a drop-out.
Of course, a high number of students did complete the Stanford AI class. But what struck me in informal conversations (so yes, this is anecdotal) with various friends and colleagues who took it or the Stanford Machine Learning class, was that a number of them already knew the material. That is, they already had degrees (in some cases, advanced degrees) in the field, but were sitting in on the class for fun and out of curiosity. While that's awesome -- and these people were in many cases extraordinarily helpful in some of the online forums that sprouted up around the Stanford MOOCs -- it does raise some questions about who these courses see as learners.
That's not to say that there's not a fair amount of expertise and advanced knowledge in other MOOCs, something I'm reminded of every time I hear Dave Cormier talk about "rhizomatic learning." (But that's probably due to my own grad school wranglings with the works of Deleuze and Guattari).
I'm particularly interested in who my fellow students are in Udacity's introductory computer science class this term. CS101 said that no previous programming knowledge was required and that by the end of the class, one would know enough Python to build a search engine. But I get the sense from the forums that many of my fellow students in the class are programmers, if not Python developers already. That's fine (again, they can be helpful in answering questions for their peers). But as Udacity will be in the business of selling high-scorers' data to potential recruiters, I do wonder how much attention really will be paid to learners and how much the emphasis will be on knowers.
I wonder too about the question of motivation, one of the requirements that the NYT as well as MOOC instructors point to. What are the things that motivate learners? How do we support them when motivation falters?
The emphasis Siemens recently wrote that "It is important to realize that MOOCs are not (yet) an answer to any particular problem. They are an open and ongoing experiment." (Arguably Udacity hopes to be an answer to the problem of recruiting talented workers into the tech industry.) How will this "open and ongoing experiment" proceed now that alongside the institutional and cross-institutional MOOCs, we have a whole cadre of for-profit startups?
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