- to create a how to as a way of introducing ourselves, and
- to create a list.
So I read first Dillenbourg’s introductory chapter What do you mean by ‘collaborative learning’? in his book Collaborative-learning: Cognitive and Computational Approaches (1999). Keep in mind that MOOCs did not exist in 1999, so Dillenbourg cannot be held accountable for them; still, I hoped that he might provide a useful approach to studying online, collaborative courses such as Rhizo14 and CLMOOC. I am particularly interested in wrapping my head around an auto-ethnographic study that is emerging in the Rhizo14 community. In his introduction, Dillenbourg explores collaborative learning “along three dimensions: the scale of the collaborative situation (group size and time span), what is referred to as ‘learning’ and what is referred to as ‘collaboration’. This seemed promising to me, so I want to see if his experience and insights can inform the Rhizo14 auto-ethnography (AE).
The variety of scales: Dillenbourg insists that different scales of collaborative learning require “different theoretical tools in order to grasp phenomena on various scales” and that we should not generalize the results from studying a handful of people collaborating in one location for an hour to 40 or 50 people (he seems not to have imagined hundreds or even thousands of collaborators back in 1999) collaborating in different locations over the course of a year, and vice versa. Moreover, scale is not so much a property of the object as it is “a property of the observer, who selects the most appropriate unit of analysis.” Likewise, the observer defines the agents, or “functional units”, within a collaborative learning, which can include devices and systems as well as humans.
I like that Dillenbourg begins with scale issues, as I believe that online, collaborative learning is a function of complex, multi-scale networks, or what Deleuze and Guattari call rhizomes. (Networks and rhizomes are not synonymous, but they share some characteristics, and I find it easy to shift between the terms, using networks when I want a more precise model and rhizomes when I want a more expansive metaphor.) For instance, Rhizo14 has generated an auto-ethnographic study that begins with a collection of stories from Rhizo14 participants about how and why they engaged Rhizo14. The raw material for the study, then, is a collection of discursive snapshots taken of Rhizo14 from the different angles and perspectives of each of the story tellers. At one scale, these snapshots can be aggregated and merged into a more complete image of whatever Rhizo14 is. This is something similar to what Blaise Agüera y Arcas does with Microsoft's Photosynth, which collects images, say of the Eiffel Tower, from around the Net, aggregates those images, and produces one multi-dimensional image that is far richer and more informative than any single image. Thus, the multiplicity of the network produces an image that exceeds the sum of all the parts.
But this resulting, single image is just one scale. Fortunately, the Rhizo14 auto-ethnography is conducted by a group of scholars, each of whom can explore the snapshots at different scales and from different points of view with different critical methods. For instance, Rhizo14 featured a wealth of creative responses (poems, animations, stories, etc), and I see no reason why the auto-ethnography should be limited to typical, scholarly papers. Some aspects of Rhizo14 are better and more accurately captured in poetry. Others of the group might tie the auto ethnographic stories to Facebook discussions or Twitter streams. Some might focus on a single participant’s story. Another might analyze the narrative structures of the various stories to explore how people construct their participation within a cMOOC. My point here is that there are more scales and points of view than there are researchers in Rhizo14, and we can preserve the multiplicity of Rhizo14 by looking at it from different scales and different angles.
I’m also pleased that Dillenbourg emphasizes the role of the observer in his analyses of collaborative learning. According to him, the observer defines both the scale of the network and the characteristics of the agents within the network. This positions the observer within the system observed instead of privileging the observer with some objective, godlike view outside the observed system. Thus, the Rhizo14 auto-ethnography group must recognize its position within Rhizo14 and account for its presence and interactions there as an integral part of the effects and processes that it is studying. Said another way, the auto-ethnography group must recognize its own considerable gravitational impact in the solar system that it is studying. While it is easy and natural to define the various Rhizo14 human participants as agents within the Rhizo14 system, the auto-ethnography group is still responsible for its characterizations of those agents and even more so for the configurations and groupings of those agents into Facebook, Twitter, and Google+ cohorts, bloggers, lurkers, the auto-ethnography group itself, and whatever other large-scale agents they may devise. The AE group must accept its creative, imaginative role in defining a particular Twitter stream or blog conversation, say, as an agent in Rhizo14, and though the AE group did not create Facebook, they do create Facebook as an agent in Rhizo14, in large part, by choosing to treat it as an agent, or not.
In sum, the study of a complex, online, collaborative learning system starts, as Dillenbourg suggests, by positioning the researcher within the system studied and forcing the researcher to account for her own role within and impact on the system, accepting that the system is different than it would have been had the researcher been someone else or had there been no researcher at all. This repositioning of the observer from outside the observed system to inside challenges the traditional notion about the stability of reality. If the characteristics and behaviors of the observed cMOOC depend at least in part upon the presence and imagination of the observers, then can we say anything stable and lasting about the cMOOC? Probably not. But stability is likely a problematic expectation anyway. The more promising aim of research, I think, is to say something useful about cMOOCs. We should aim to provide actionable knowledge, not absolute knowledge. The absolute, even if it exists, has always been beyond our abilities. Einstein tried to give us our last absolute when he said that nothing could exceed the speed of light, and then quantum physics came along with its spooky action at a distance to suggest that something is moving faster than light. Damn!
And even actionable knowledge may exceed necessity. Maybe what the AE group should aim for is an expansion of the field of education to include the possibility of courses such as cMOOCs. In her post Reflections on the value of MOOCs, Rhizo14 participant Tanya Lau says:
What I get out of the cMOOC experience is not necessarily practical strategies, ideas or actions that I can apply directly to my workplace (which I might get from say, an industry event, workshop, conference targeted to the field of corporate L&D that I work – or indeed, an xMOOC targeted to a domain of knowledge or skill I have a need to develop). Yet it’s something that actually has greater value than practical application: it’s the shift in mindset that results from engaging with people who are driven to continually question, experiment, explore and improve -> it’s that you start to adopt this mindset yourself too. Start to see challenges as opportunities to explore possibilities, become a little braver, make the leap from thinking about experimenting to actually doing it. No longer (as) afraid of being challenged, but open to it – inviting challenge rather than being defensive. It’s more than just being inspired. It’s inspiration + action to = change. Change in the way you think, learn and act – about life, work, learning, and yourself. It is the personal, human connections and inspiration that Clarissa speaks eloquently of in her posts on #CLMOOC and #Rhizo14.This is brilliant, and I thank Tanya for saying it just so. You don’t finish a rhizome, you engage it, and when the rhizome has reterritorialized within you and you within it, then you are never free of it, even after its intensity has faded. You certainly can’t study it without becoming part of it. Like gardening, the dirt gets under your nails.
It’s the type of engagement that most conventional courses and programs dream of achieving, and it’s the reason why I get so frustrated with the continual focus on ‘completion’ as a means to evaluate the effectiveness or value of MOOCs. It’s not about completion; it’s about engagement. And thought-provoking, behaviour-changing engagement can be triggered even through one conversation or experience – as long as it’s with the right people, at the right time, and at the right level.
So writing about a cMOOC, defining it from within, aims not so much at giving teachers practical strategies and formulae for modifying their classroom practice as at helping them to shift their mindset and to engage “with people who are driven to continually question, experiment, explore and improve”. And if the AE group can identify a reusable practice or technique—well, that’s okay, too.
I see that I have pushed beyond what Dillenbourg was suggesting, so I have to give my usual caution when I’m discussing the work of another. I am a somewhat poor scholar in that I am much less interested in figuring out what someone else means than in figuring out what I mean. Take my reading of Dillenbourg, then, not as critique of Dillenbourg but as an exploration of how I think we might systematically map a complex, multi-scale system such as a cMOOC.
Okay, that’s Item 1 in my list about how to study a cMOOC. Items 2 & 3 soon.
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