My #mri13 keynote panel talk last week was on “the post-MOOC-hype landscape.” It was supposed to be about what I think we can do in the current “we have a lousy product” hype gulch before it all gears up again to bend the ear of NYT readers all over academia. And Silicon Valley.

The short version (see slide 4) is this: there are currently two solitudes in the MOOC conversation, and it’s not a cMOOC/xMOOC divide. One solitude – the mainstream media discourse – is essentially a unicorn, in the sense that its promises are fantasies of salvation and solutionism that have very little to do with the actual practice of higher education. The other – the practitioners’ discourse(s), broadly represented by the various interests around the table at #mri13 – is a Tower of Babel. Still, this solitude, loosely and cacophonously affiliated as it is, nonetheless leans towards discussing MOOCs in terms of learning. And in the wake of twenty-odd months of hype in which the dominant public narratives about higher ed have been all glorious revolution or ghastly spectre, I think it’s time to seize this (likely momentary) lull in unicorn sales and try to talk about MOOCs as learning. We need to make ourselves familiar with what the post-hype landscape of higher ed looks like, and address the issues and opportunities it’s left us with. In learning terms. On as many public platforms as we can. In stereo.

In other words, challenge the empty narratives that your administrators or your faculty have been sold. Find ways to talk about why what you’re doing matters. Change the narrative from unicorns back to what education is about: learning. End story.
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Maybe I got it wrong, though.

In the revisionist history of my own mind, the “post-MOOC-hype landscape” is now forever linked to the unplowed freeways of the post-apocalyptic ice-storm-in-Texas landscape that stormstayed plenty of conference attendees in Arlington for the weekend. I got out, though dramatically. I pretty much hopped off the panel stage and into a taxi van with Dave, Mike Caulfield, Emily Schneider, two gregarious business dudes from Montreal, and a most intrepid driver, who happened to have grown up in India and had never seen snow in his life. The seven of us, strapped into our seatbelts over a set of summer tires that God never intended for ice, bumped steadily over a barren landscape of exit bridges and frozen plains speaking – at one point in the drive – in English, French, and Urdu all at once.

One of the Montreal business dudes managed to educate us all about bee death while also inquiring which language Dave & I make love in. (Apparently, folks, French comes highly recommended.) The other Montrealer, born on the subcontinent, sat in front and instructed the driver in their mother tongue on how to keep us the hell out of the ditch. A giant flashing billboard along the way proclaimed TRAVEL NOT RECOMMENDED. It reminded me of nothing so much as a scene from Mad Max.

But there we were, squished together.

It seems to me as good a metaphor as any for where we are with MOOCs and higher ed.

That second solitude – those of us whose research and practice focus on MOOCs right now – are like the seven of us in that little van. We’re a random collection. We don’t all know each other. We speak different languages and have different ideas about which ones are good for what. And we’re all of us inching forward in a space rendered unfamiliar by a freak storm – in one case ice, in the other, hype – that nobody’d expected in that particular context.

I got it wrong in the sense that the real ‘what’s next?’ may not be grappling with the unicorn narratives.

I think ‘what’s next?’ is working out the conversation IN the metaphorical van. Some who see MOOCs as learning focus on the pursuit of its ever-more-finely-honed measurement. Others are more inclined to dismiss measurement as irrelevant to the networked synthesis of ideas that forms the backbone of their approach to education. A hundred more do something in between. We don’t necessarily know how to talk to each other. It became evident around the Arlington bar tables last week that the chasms between practitioners’ varying versions of learning and knowledge are so deep some aren’t even really aware that the rest of us are IN the van.

That blindness – which we all, me included, probably suffer from to some extent – is dangerous. It’s dangerous because people keep trying to shove the future of education as a public enterprise into the van, without asking questions of what counts as education and of who benefits – and loses – if it becomes seen as a consumer commodity.

I don’t believe data has the sole answers to these questions. Conversations about theory and Big Data being post-theory kept emerging in Arlington, and have flowered further in the blog-to-blog flurry of discussion that’s circulated since we all escaped the Texas ice (Martin Weller & Mike Caulfield have written posts that make great bookends on the issues the End of Theory raises; Tanya Joosten & Jim Groom, among others, held court on the issue at the bar). But the elite university data scientists are notably absent from this networked conversation.

There are more solitudes here than my slide deck lets on. And like the unicorn narratives, Big Data tends towards being a totalizing vision.

Ontologically, the networked approach to MOOC learning and the AI-rooted machine learning approach are very different animals. They always have been, and the fact that we’re even all in this little van together bumbling through the post-hype landscape is as much a linguistic accident as anything: one NYT article and two very different conceptions of the Internet happening to education got hitched together on one wild ride.

I think there’s potential in that: there’s a lot about what analytics can tell us that interests me. But algorithms are not neutral, in my worldview. The Big Data researchers bring institutional clout and status to the conversation along with what struck me, in many cases, as an almost entirely un-self-conscious absolutism in their approach to knowledge and learning and the capacities of correlative data. And that raises issues about the future and direction of higher education and learning, far more than unicorn narratives ever did. When I say the MOOC narrative needs changing, I don’t mean it needs to become a monolith – it won’t. Part of its power is that many new stories of learning and education can nest themselves within it. Nor do I particularly expect to change the data scientists’ narrative on MOOCs and learning – except when they try to argue knowledge as truth over my prime rib dinner. But in the post-apocalyptic, supposedly post-hype landscape that was Texas, the biggest ‘what’s next?’ I actually came away with was the question of whether those of us most deeply invested in MOOCs at the moment can learn to live and work together in any real way.

As George Siemens said in the opening to the very first #mri13 session, these are issues of power. Educationally, ideologically…hopefully not apocalyptically.

Hang on tight, kids. The next van ride’s aimed for Charlottetown, for #mri14. It almost NEVER snows here in July, I promise. ;)