The discussion on what is a MOOC or how do we classify MOOCs is gaining momentum. First we had George explaining the difference by saying that there are xMOOCs and cMOOCs. Now Lisa Lane has come with a different taxonomy (network/task/content based) with some interesting distinctions. Dominic came up his own understanding of the “features” of a MOOC. See also Gordon Lockhart’s Super-MOOC, A MOOC by Another Name and a brilliant post by Doug Holton, where he makes many insightful remarks including what could be necessary and sufficient conditions for learning to occur or to be “caused” (don’t particularly like that last word).
Taking Doug’s cue, we should perhaps be talking of massive in the sense of the quantum of connected-ness or connection-richness, or in terms of the widespread nature of the learning need or motivation, rather than looking at it from the point of view of number of learner enrolments.
That said, I would reiterate that we are comparing apples with oranges, and despite the “mania”, there is no reason why we should be forced to compare these different initiatives in the first place. MOOCs (cMOOCs) will have a plethora of possible implementation strategies and techniques. For example, I love what the folks at the Mechanical MOOC are doing (Audrey covered them here).
In my opinion, it makes more sense to focus on the platform rather than the tool, the rubric rather than the assessment and the DNA rather than the you or me.
A video, by Prof. John Holland (University of Michigan) speaking on Modelling Complex Adaptive Systems, is a must view (rather long, but worth it) for a large number of reasons. I find this CAS video (and generally the complex systems area) appealing because it makes more sense to me than engineered closed systems like we have in education today.
I am intrigued by the emphasis in the talk of building blocks, signals, interactions and boundaries within an overall approach of risk taking innovation. I think that fundamentally describes the platform I am referring to. Let us look at that process.
When a learner first starts out, certain pre-conditions exist. These pre-conditions are what makes a person a learner – whether it be out of curiosity, awareness, context, a need and/or some other kind of motivation trigger. At this point, the learner understands little of the network of knowledge, and perhaps may also have a sense or purpose or general idea of outcomes from the forthcoming experience. The platform will have to recognize this initial state.
Next comes a series of interactions in and with the network. This is where the accessibility, quality and depth of the network (in terms of coverage, accuracy, engagement, open-ness) and the contained boundaries play a big role in facilitating or obstructing discovery, experimentation and conjecture – viz. sense-making.
The network really is two things – one, an explicitly curated or visible set of people, content and tools, and two, a vast hidden implicit network intimately connected with the first but not explicitly visible at first.
Interaction in the network will be governed by signals – actions by the learner, actions by others and changes in the network itself as it evolves and adapts. The learner will interact to implicitly or explicitly “produce” or “engineer” make visible or personal, a set of connected nodes in the network (which shall be her curation arising out of her discovery, experimentation and conjecture).
The visible and invisble impact of her sense-making and of others will generate fresh signals in a non-linear manner. Over time, some of the network constellations will get broken to form new bonds (or connections) as the process will be usually far from equilibrium. Visible parts will become a part of the network thus changing the network maps of sense-making of others and in turn generating new innovations and experimentation.
Again over time, feedback from these interactions or signals will reinforce collections or patterns of these nodes of sense-making and new building blocks of comprehension and sense making will emerge. This is turn will affect boundaries of interaction and reduce impedance caused by them, so that new constellations are created.
The platform will have to recognize this elaborate dance of sense-making, the signals, interactions, boundaries and complex adaptation. It will have to provide for this complexity and it will need to allow for contextual influence to align towards certain constellations (and it will do so in many ways, giving us the agency).
The platform will have to recognize and help resolve multiple trails that coalesce into a conception, parallelisms or multiple patterns of building blocks that converge into a model (a thought, an idea). And the system will have to recognize transition or inflection points, when existing models are questioned and new trains of thoughts emerge, just like in this post.
The platform has to provide for this emergence, chaos, self-organization and adaptation. Something that is spectacularly different from what Khan Academy or Coursera or other non-MOOCs are attempting to do. And in doing so, it will forge a new understanding of what an educational system ought to be.