Friday, August 1, 2014

Educational Research: At the Heart of Things

In a 2008 article entitled Complexity as a theory of education, Brent Davis and Dennis Sumara discuss the unique qualities of educational research, especially in light of complexity theory, suggesting to me that complexity plays a unique and insistent role in educational research. Complexity has been on my mind for a few years now, especially in its metaphorical expression as a rhizome and specifically as a way to approach the Rhizo14 auto-ethnography, so I want to map Davis and Sumara's ideas to rhizomatic thinking in Rhizo14.

Davis and Sumara begin by noting the appropriateness of complexity thought for educational research. Both are relatively young and emerging systems of thought and they share some common approaches to the study of reality.

First, both complexity and educational theories approach systems that learn. Davis and Sumara say, "Brains, social collectives, bodies of knowledge, and so on can all become broader, more nuanced, capable of more diverse possibilities." I'm sorry that Davis and Sumara seem to limit learning to higher order life systems with sophisticated neuronal structures such as brains, as it seems to me that almost all scales of the universe are capable of becoming broader, more nuanced, capable of more diverse possibilities. For instance, the antibodies and antigens that help make up my innate immune system learn to recognize and defeat new attacks on my body, and as far as I know, they learn this without benefit of a brain. Of course, the pathogens attacking me also learn how to get around my innate defenses and any medicine that I might add to the mix. I don't think bacteria have brains either. So for me, learning is one of the fundamental processes of reality as entities at all scales exchange not only energy and matter, but also information and organization, in order to adapt to and thrive within their environments. Learning theories go to the heart of everything and every theory. Thus, educational theory should be informing all other theories, from sociology and psychology down to chemistry and physics, rather than always pulling its frameworks from those other theories. Educational theory is not derivative, it is generative. Down to the core.

Still, Rhizo14 certainly meets Davis and Sumara's concept of a learning system, and their implied definition of learning might guide investigation of Rhizo14: did Rhizo14 learn, becoming broader, more nuanced, and capable of more diverse possibilities? If not, why not? If so, why and how? Did Rhizo14 exchange information and organization within itself and with its environment? If so, how and why? If not, why not? What values emerged from this exchange? What was the new, emergent information? What was the new, emergent organization? What are the salient characteristics and values of this emergent information and organization?

The term emergent leads to another shared characteristic of complexity and educational theories: emergence. Davis and Sumara say, "each of these phenomena is emergent—that is, each arises in the interactions of many sub-components or agents, whose actions are in turn enabled and constrained by similarly dynamic contexts." Learning has always been an emergent event, but courses such as Rhizo14 make emergence explicit and attempt to ride the emergent wave, assuming that emergence is the source of broader, more nuanced, more diverse possibilities.

Emergence is certainly relevant to the study of a cMOOC such as Rhizo14. The course arose in the interactions of many sub-components or agents, whose actions [were] in turn enabled and constrained by similarly dynamic contexts. Any study of Rhizo14 must be constantly aware of the sub-components and agents that embodied the course and must be aware that each of those sub-components and agents are themselves emergent entities informed by yet another scale of sub-components and agents, all the way down to the core, and learning takes place on each scale and between scales. In other words, information and organization is exchanged in circularly causal loops within a scale and across scales. Learning is unbelievably complex, and while any particular study of learning will out of cognitive necessity focus on a particular human scale (usually an individual or a social group), it must acknowledge that its particular scale is not discrete, but is an integral part of scales within it and without it. Any processes on one scale are fully understandable only in context.

And this brings me to another objection to Davis and Sumara's treatment of complexity: a failure to recognize the transcendent. Perhaps Davis and Sumara are too influenced by the very reductionistic sciences that they are trying to move beyond, but they seem to me trapped just here. Davis and Sumara can see emergence coming up from the core in the sub-components and agents, but they don't recognize in this article the scales above us, the transcendent scales. Western culture has a strong bias—scientific, social, and religious—toward seeing humanity as the highest expression of either nature or the gods. We regularly hear that the human brain is the most highly advanced, most complex structure in the Universe. Being scientific these days, we've traded the soul for the human brain, but the effect is about the same: humans are the pinnacle of creation, the apple of Nature's eye, blessed above all else. What a profound failure of imagination and insight!

Many spiritual traditions, but also complexity science itself, suggest the limitation of this point of view. With ever better tools, science has continued to push out the immanent and transcendent scales of reality: inward/downward to vibrating strings and outward/upward to multi-verses. Just when we think we've hit rock bottom or soared to the absolute ends of the Universe, we find more layers. We humans are somewhere in the middle. Not insignificant, but not so important either, and our normal, unsupported vision is limited to a very narrow scale, a very narrow band of the light spectrum. We don't see the infra-red or the ultra-violet, so we think it isn't there, but it is. Complexity thought says that any scale of reality depends both on the scales below/within it and the scales above/without it. And there are always scales beyond. There is always a transcendent.

Now I do think that it is somehow easier for us, in the West especially, to see the scales below/within us, but this may just be our reductionistic habits and heightened sense of importance over the past few centuries. Still, educational studies must be conscious of and allow for the influences of scales beyond the individual learner or the group learners. The enclosing ecosystem always pulls the emerging learner or group into shapes and processes that it might not otherwise assume, and of course, the ecosystem is then affected itself by the emergence of this new structure within. Imagine a new and beneficial organ emerging in your body to provide some new capability. The organ cannot take any shape it chooses, but must find its shape and place with the existing body, which must rearrange itself to benefit from the new organ. The local causality of the new organ is not enough to explain it. We must include the circular and global causalities also at work.

There is always a higher body, and if cMOOCs such as Rhizo14 are beneficial, affording us new capabilities, then they will shape themselves within existing systems while changing the shapes of those systems. They will exchange information and organization with a transcendent scale of reality. Thus, Rhizo14 should ask what local causes were at work within Rhizo14 to make it behave as it did, but also what circular causalities were at work among the various scales and what global causalities pulled Rhizo14 into its emergent shapes. For instance, a number of Rhizo14 participants wanted to discuss Deleuze and Guattari's concept of the rhizome and how it informs our thinking about education, but that conversation was short-circuited and other conversations emerged. This was certainly not caused simply by any local decision, though local decisions can be identified; rather, it was a pull, a global cause, that emerged from the group and transcended any individual decision or cause. How did that work? How does that work? Leaders in the group emerge. How? Why? In short, there are wonderful dynamics at play in a cMOOC such as Rhizo14 that can only be accounted for by reference to scales beyond the individual or even the group. Of course, that pushes into the fog, the noise, enclosing us. It's a bit akin to a single neuron in a human brain trying to understand the consciousness that emerges on a scale several levels beyond it. It may not even know that it is a part of consciousness. We likely don't know what entities we are part of on the scales beyond us, either, but that doesn't mean that we shouldn't be open to those scales and recognize their influences on us.

I'll explore more of Davis and Sumara again.

Tuesday, July 29, 2014

Who's Writing the Rhizo14 Ethnography: The Problem of Authorship

I read through the Rhizo14 auto-ethnography this past week, in part to re-connect but also to see if it was moving anywhere (I won't say moving forward as that is far too linear a concept for anything out of Rhizo14), but the document itself has been largely inactive since April or so, and I've not seen it emerge in any other space. It is an exciting document with much potential, so I wonder why it isn't moving. This question is not an indictment or even a challenge, as I haven't done much with it myself, but it is a chance to think about the problems of authorship of such a document through such a writing process.

First, authorship has been problematic from the beginning, as the document itself demonstrates. Sarah Honeychurch created Collaborative Autoethnography for #rhizo14 in Google Docs on Feb 16, 2014, announcing that "We (Maha, Lenandlar, Vanessa, Sandra, Sarah, and anyone else who fancies joining us) intend writing a paper about #rhizo14 and will be including quotations from this document." Thus, the document was opened from its inception to anyone else who fancies joining us. A number of people did fancy joining, at least for a while and in a way. The document was initially shared publicly so that people could, and did, contribute anonymously; still, I can identify contributions either to the text and/or to the comments from these 35 different people, in the order that I could identify them, with no priority or rank implied:



  • Sarah Honeychurch
  • Arthur Oglesby
  • Kevin Hodgson
  • Sandra Sinfield
  • Apostolos Koutropoulos
  • Terry Elliot
  • Maha Bali
  • Monika Hardy
  • Ron Leunissen
  • Vance Stevens
  • Ellie Trees
  • Heli Nurmi



  • Barry Dyck
  • Bonnie Stewart
  • Simon Ensor
  • Aaron Johannes
  • Vanessa Vaile
  • Lou Mycroft
  • Lenandlar Singh
  • Clarissa Bezerra
  • Scott Johnson
  • Paul Gareth Smith
  • Tanya Lau
  • Keith Hamon



  • David Jones
  • Janet Webster
  • Nick Kearney
  • Jim Stauffer
  • Danielle Paradis
  • Rebecca J. Hogue
  • Frances Bell
  • Lenandlar Singh
  • Carol Yeager
  • Dave Cormier
  • Paige Cuffe

  • And if I include the eclectic Anonymous, then I have 36 contributors. Quite a rabble itself, but additionally complicated by some who did not want to be identified with the group and others who used the auto-ethnographic content without permission, though just whose permission they needed is somewhat confusing itself.

    So who is writing this document? I think my question itself is problematic, starting with the words who and document. I'll get to the verb writing later.

    For more than a half a millennium, western culture has tried to define the role of the author, limiting it to an individual or a definable group following a positivistic epistemology and mostly for the purposes of establishing property rights within the Western legal tradition. The history of this development is far beyond the scope of what I want to say in this post, but it's worth noting that our ideas about writers writing documents are culturally informed and have mostly to do with identifying what person or group produced what document and thus knowing whom to praise or blame and whom to pay or persecute.

    Western language and speech has a strong bias toward discrete, definable actors (nouns and pronouns) performing discrete, definable actions (verbs). We like stable relationships between one word and one thing, and we become uneasy when words begin to slip their meanings. We expect and want who in who is writing this document to refer to either a clearly definable individual (let's pick Sarah Honeychurch since she created the initial Google Document) or to a clearly definable group (maybe Sarah, Maha, Lenandlar, Vanessa, and Sandra; maybe all 36 above; maybe some other assemblage) and document to refer to a clearly definable electronic artifact. Collaborative Autoethnography for #rhizo14 doesn't seem to be playing this way, and that may be causing problems. We have a rabble writing a cacophony, and it's confusing and paralyzing.

    This is understandable. In his book Genesis (1995), Michel Serres explains much better than I can our problems with rabbles and swarms and rhizomes and the noise they make:
    We are fascinated by the unit; only a unity seems rational to us. We scorn the senses, because their information reaches us in bursts. We scorn the groupings of the world, and we scorn those of our bodies. For us they seem to enjoy a bit of the status of Being only when they are subsumed beneath a unity. Disaggregation and aggregation, as such, and without contradiction, are repugnant to us. Multiplicity, according to Leibniz, is only a semi-being. A cartload of bricks isn't a house. Unity dazzles on at least two counts: by its sum and by its division. That herd must be singular in its totality and it must also be made up of a given number of sheep or buffalo. We want a principle, a system, an integration, and we want elements, atoms, numbers. We want them, and we make them. A single God, and identifiable individuals. The aggre­gate as such is not a well-formed object; it seems irrational to us. The arithmetic of whole numbers remains a secret foundation of our understanding; we're all Pythagorians. We think only in mo­nadologies. (pp 2, 3)
    As Deleuze and Guattari say in A Thousand Plateaus (1980, p 3), we humans need to "fabricate a beneficent God to explain geological movements." Rhizo14 may feel the need to fabricate an author to explain a text or to write a text. Rhizo14 may feel the need to fabricate a specific text—one thing directly attributable to specific authors—to explain the rhizomatic movements of Rhizo14. We may feel the need to subsume the babble of voices beneath a unity, or the flights of tweets, texts, and doggerel into a single document. We want monads: a single, genius author or a single, collaborative group to produce a single document, or several single documents. We want a thesis, a single governing idea, best attributable to a single voice. We want One Ring to rule them all, One Ring to find them, One Ring to bring them all and in the darkness bind them. We have centuries of culture that tell us this is authorship, this is writing, this is how sensible documents are done.

    There is much power in this concept of writing, authorship, and text. First, it brings into relief a writer and a text against the background of noise and chaos. We can say, "Keith Hamon wrote this blog post", but it is just a manner of speaking. While there may be something of me in this post (if there is really even something of me in me), I am acutely aware of how much I am only orchestrating various strands that did not come from me but pass through me and will not end with me. I conventionally attribute other writers, of course, but only where I remember to do so, and my practice covers only the most obvious of my borrowings. I suspect that you could google each sentence in this post and find some source for a similar idea. I didn't attribute any of those. I've forgotten the sources for most of my ideas, and while I can find sources for all of my ideas, I'm not sure that they are my sources, but I am sure that it doesn't matter. All my ideas come out of the noise, attain a brief clarity and configuration (occasionally perhaps a novel configuration) in me, and then melt back into the noise which holds all ideas.

    Then, if we bring into relief a specific writer and a specific text, then we can trace and manage the power relations between this writer and others, this text and others. We can trace flows of status, money, prestige, fame or infamy, credit or blame, influence or anonymity. We can rank and point. We can name and demarcate. We can know if we are in or out, up or down. We can say that we are playing by the rules or not. We can have a profession and be paid for it. We can attain great clarity, and with clarity comes power. We can say, "I have seen the night sky, and these are the patterns in the stars, and these patterns make clear the meaning of life."

    I do not dismiss the virtues of this approach to writing, or to life in general. Clarity and power can lead to a secure sense of one's place in the universe, and that has immeasurable benefits. However, seeing the patterns in a few stars requires ignoring all those trillions of other stars, causing them to recede into the background. It means ignoring the background noise, which holds all the stars, all the patterns, all the meaning, and focusing on just a handful of stars and a bit of meaning. It's an awful dilemma, but while we gain much, we lose more. We in the West don't have good words and concepts for the background hum, the cosmic background radiation of the Big Bang, captured here in a recording by University of Washington physicist John Cramer:


    What do you do with such a sound? You can't dance to it. You can't wrap your head around it. You can only open yourself to it. You have to relax your normal cognitive structures—those insistent, almost automatic processes that frame reality, and bring a few stars, a subset of reality, into relief and render them sensible. But this Big Bang sound isn't a few stars. It's all stars. All galaxies. All things. We don't do so well with that. As Serres notes, it is disaggregation and aggregation without contradiction, and we are overwhelmed. All meaning is no meaning.

    Well, I didn't really intend to write about the Big Bang and all, so let me return to what may have been my point: we, at least we in the West, like to reduce documents to a single artifact and writers to a single person or group of persons. We are not comfortable with distributed documents that emerge out of the noise of many people talking, even though we experience such noise daily in cafeterias, bars, street corners, stadiums, auditoriums, and more. Mostly, we just try to ignore that background noise and talk over it. We don't think that it communicates to us beyond a general tone or timbre. Such documents certainly don't make sense in an academic setting. Who gets credit? Who gets tenure? Who publishes this? What do they publish? Does publication demarcate the document? Who demarcates the authors? This is just a cluster fuck in a mosh pit, and how will we ever determine the genealogy of such monstrous offspring?

    Well, that's the point, I think. Deleuze and Guattari and later Serres are saying that the noise, the rhizome, is the norm and that the clarity and power are the exceptions, the bits of amorphous reality that we wrench into relief for a time, but never for a thousand years. I want to say, then, that the Rhizo14 document is already being written, began before Sarah Honeychurch created the Google Doc, and that it is still being written by any number of people, including me in this post you are reading. It is being written in an academic conference by scholars who didn't even participate in Rhizo14. It is being written by students in Maha Bali's classes who don't even recognize the term Rhizo14.

    This kind of writing is not new, but it is not part of the Western rhetoric that I know. I recently read an article by Samuel Arbesman called The Network Structure of Jewish Texts in which he discusses the network nature—I would say the rhizomatic nature—of Jewish texts as revealed by Sefaria, "an open source database of Jewish texts", which Liz Shayne of UC Santa Barbara has graphically mapped (see some beautiful pix of rhizomatic structures in her article Sefaria in Gephi: Seeing Links in Jewish Literature). So who wrote the Talmud? It is the wrong question, for it assumes an author or limited authorial group and a specific text. The Talmud has neither. Rather, it is the accretion and emergence of cacophonous conversation over millennia. It is aggregation and disaggregation without contradiction. It is a rhizome. We likely don't have all of the Talmud, but we seem to have enough to continue the conversation. There will, of course, be clumps in the conversation, tubers and bulbs called scholarly papers or blog posts, just as there are clumps in the heavens called galaxies and clumps in our bodies called organs, and the clumps are important. They stand out in relief and give us a momentary clarity, but the clumps are not the whole thing, and eventually, they do return to the noise either as a consequence of time and entropy or a shift in our attention. Authors and their texts are convenient fictions, even useful at times, but fictions nonetheless.

    So what conversations about Rhizo14 are emerging?  What patterns can we create out of it? How do we map this conversation and traverse it as knowmads, mindful that knowmads cannot be monads? I'll have to think about that some more, unless of course one of you has a ready answer. I'd love to hear it.

    Friday, July 18, 2014

    hackAhack in light: #clmooc

    My friend Maha Bali writes so well, and she is prolific. I've thought about trying to keep up with her, but I can't, so …

    Still, she just wrote a wonderful post I ____ therefore I am human that challenges me to think about what it means to be human. She hacks Descartes' famous dictum I think; therefore, I am, shifting away from thinking to feeling, framing her thoughts within the current fighting between Israel and Palestine. She ends up with:
    I feel therefore I empathize
    I empathize therefore I am human
    I think I see her point. Descartes grounded his scientific philosophy in an intellectual reductionism that tends to separate everything, breaking down wholes into the tiniest constituent parts and the most basic of interactions, with the assumption that he could put it back together with a more complete understanding. Well, try that with a frog sometimes. Take the frog apart, identify its constituent parts and the basic processes among those parts, and then put it back together. You don't get a frog. You get Frankenfrog—a monstrous, mechanistic mess with no life in it and little value to you or the frog.

    Now try that with a people: Palestinians, European Jews, American Indians … you pick. There are plenty of examples. Try it with a person: your spouse, your children, your students. Take them apart, name their parts and processes, and then try to put them back together. You get Frankenkids and Frankenclasses. When you pull life apart, you lose something really important, and the knowledge or whatever else you gain may not be worth what you lost. Often enough, it isn't.

    Now, I am not suggesting that a reductionist scientific point of view has no value. It does. As Edgar Morin has stated, much of the advances in modern culture can be directly attributed to the patient, inexorable workings of reductionistic science. But it isn't enough, and by itself, that kind of thought blinds us as much as it enlightens. We need something more.

    We need a complex science that incorporates feelings along with intellect. Intellect alone will kill us. Intellect counterpoised with feeling just might save us. I don't suggest that the one resolves into the other; rather, they maintain a delicate, creative tension that informs the other without ever subsuming or canceling the other. They keep in dialogue, never completely agreeing, never disengaging, knowing that both are richer for the other, that one without the other is madness.

    We need a science that values connections as much as it values separation. I connect with Maha Bali. We both connect with the communities of Rhizo14 and CLMOOC. I think it's those connections that make us human. Without those living connections, we are merely Frankenpeople.

    So I want to hack Maha's hack. I want to make a hackAhack:

    I connect to others; therefore, I am human. I could have used the word engage instead of connect. I've been using engage and engagement more in my writing lately, but I'll stick with connect and connection in this post as it may be the more inclusive term. Engagement seems to suggest a more intentional and deliberate connection; whereas, many of our connections are not intentional, deliberate, or even conscious. When I breathe air with you, I usually don't think about it, but it's a connection that I ignore at my peril.

    I'm human, then, because I think and feel, and I think and feel because I connect to others. Without my communities, I really wouldn't have much thought or feeling. I wouldn't be human.

    Tuesday, July 15, 2014

    Hacking Post: #clmooc

    Well, my first Make Cycle for #clmooc (write a how to) took longer than I anticipated, and now I have missed some of the other tasks, but this is one of the best things about MOOCs: only the organizers and facilitators have to stay on task, and even they can slip if they do it right.

    Anyway, I've decided to skip to Make Cycle #4: Hack Your Writing. I'll hack my blog posts, which tend to be analytical pieces, with some poetry, starting with haiku. I'll use the titles of the hacked blog posts.


    How to Study a cMOOC: Part 3 of a list for #CLMOOC

    Pierre Dillenbourg
    turns from fifteen years away,
    answers, "Here I am."


    Investigating MOOCs, Part 2 of a #CLMOOC List

    a tweet uncalled for
    as pointed as a finger
    cooperation


    How to Study a cMOOC: A list for #CLMOOC

    human scale hangs in
    the balance against scaled fish
    — a neuron waits to fire

    Thursday, July 10, 2014

    How to Study a cMOOC: Part 3 of a list for #CLMOOC

    So I'm closely reading Dillenbourg's 1999 introduction to collaborative learning to see what guidance it may provide for studying cMOOCs such as Rhizo14 and CLMOOC. Dillenbourg's first point about looking at collaborative learning from different scales strikes me as most helpful, but his second point about defining learning at best provides negative examples: what not to do. His third and final point about defining collaboration also seems to be a negative example of how not to approach cMOOCs. Let's see what Dillenbourg has to say.

    Dillenbourg looks at collaboration from four points of view, or on four different scales:
    1. situation,
    2. interactions,
    3. mechanisms, and
    4. effects.
    I like that he keeps his commitment to working with any complex system from a variety of scales. This is a key, I think, to looking at any cMOOC. But he is clearly talking about collaboration and not cooperation, an issue that Jenny Mackness opened for me and that I addressed in my last post. This suggests to me that his approach to collaboration may be another negative example for me.

    Collaborative Situations - The first way to explore collaboration, Dillenbourg says, is as a situation in which agents:
    1. are more or less at the same level: collaboration as a situation requires a symmetry in which all collaborating agents have similar freedom and ability to act, a similar level of knowledge, and similar status within the group. It seems that asymmetry disrupts collaboration. If you know significantly more than I, then you may try boss me, breaking the collaboration. A collaborative group, then, requires a certain homogeneity, a red flag for rhizomatic, cMOOC enthusiasts.
    2. can perform the same actions: again an implied homogeneity among collaborative agents. No one is particularly more skillful than the others, though Dillenbourg does allow for some specialization of skills within the collaborative group. Too much, though, undermines the collaborative ethos, it seems.
    3. have a common goal: collaboration requires a shared goal, whereas competition requires conflicting goals (this either/or approach leaves out cooperation altogether, it seems to me). Shared goals can partially assigned at the outset of collaboration, but also depends on the collaborating agents negotiating their shared goal, and in the process becoming aware of their mutual dependence.
    4. work together: Dillenbourg finally mentions cooperation, but I don't think it helps much. He notes that some scholars use the terms interchangeably, while some distinguish them: cooperation is when group agents "split the work, solve sub-tasks individually and then assemble the partial results into the final output," and collaboration is when agents "do the work together." I don't think Jenny Mackness or Stephen Downes would favor this definition of cooperation.
    Collaborative Interactions - The second way Dillenbourg looks at collaboration is by the nature of a group's interactions:
    1. interactivity: collaborative interactions are, well, interactive, which seems intuitively obvious, but Dillenbourg defines the degree of interactivity not by frequency but by the intensity of the interactions, by the degree to which the interactions influence the peers' cognitive processes. This is an interesting approach to interactivity, but as Dillenbourg notes, devilishly difficult to measure.
    2. synchronicity: collaborative interactions are synchronous says Dillenbourg. Collaborators expect their peers to "wait for [their] message and … process the message as soon as it is delivered." Asynchronous communication is out for collaboration, but I see no advantage to Dillenbourg's definition here. Linux, for instance, is a collaborative effort that seems to thrive on both synchronous and asynchronous communication. I hope Dillenbourg has dropped this.
    3. negotiability: finally, collaborative interactions are negotiated rather than mandated. Negotiation implies for Dillenbourg space among the collaborators for negotiation and misunderstanding, a space for constructing shared meaning regarding the project and its execution.
    Collaborative Processes - The third way Dillenbourg explores collaboration is by the mechanisms that enable group interactions and learning. He starts with those mechanisms that are common to individual learning but also occur in group learning: induction, cognitive load, self-explanation, and conflict. He then talks about those mechanisms more closely associated with group learning: internalization, appropriation, and mutual modeling.

    Collaborative Effects - The final way Dillenbourg considers collaboration is through its effects on learning, usually as a measurement of individual task performance. He notes two main problems with measuring the effects of collaborative learning:

    1. It is difficult to isolate in a collaborative situation, with its many contexts and interactions, the specific causes of any identifiable learning.
    2. It is difficult to infer the degree of group learning from measurements of individual learning.
    So what does this have to say about how the Rhizo14 auto-ethnography group, for instance, should go about looking at Rhizo14?

    On the positive side, researchers will benefit from a multi-scale, multi-perspective approach to exploring any complex, multi-scale, self-organizing system such as a cMOOC. This is not to suggest that any single researcher or research effort must attempt to cover all scales and aspects of a cMOOC, but it does suggest that a research effort will benefit if it creates ample space for multiple approaches to the same system.

    I am also interested in Dillenbourg's characterization of interactivity not as a quantity but as a quality. He doesn't measure the number of engagements so much as the degree to which an engagement affects a colleague's cognitive processes. This reminds me of Deleuze and Guattari's decalcomania, one of the six features of the rhizome and perhaps the feature least mentioned and discussed by others. Perhaps it is the least understood, or least impressive, but I think that is unfortunate. Decalcomania appears to me to be the process by which memes (a term coined by Richard Dawkins about the same time Deleuze and Guattari were writing A Thousand Plateaus, so perhaps unknown to them) spread through a system. It is a kind of staining. One is stained through an engagement with another and an exchange of energy, matter, information, organization, or all four. Dillenbourg rightly notes that this view of interactivity is difficult to measure and quantify, but everyone in a cMOOC experiences it: an idea emerges somewhere in the network and passes along tweets, posts, and discussions to many others in the network and outside it. Some stain, some don't. The more who stain, the more pervasive and powerful the meme and the more likely it is to spread more. There is a network power law at work here and definitely network propagation (decalcomania) which cMOOC investigators should keep in mind.

    Then, Dillenbourg's take on the negotiability of collaborative interactions may hold as well for cooperative networks, but I have to think much more about this. Something wants me to frame the notion of negotiated social contracts in a different way, but I'm not ready to do it now, so I'll just pass.

    Finally, Dillenbourg's thoughts about collaborative processes, the mechanisms that enable collaborative learning, seem equally relevant to cooperation as to collaboration. I don't think Dillenbourg was attempting to be exhaustive in the processes he discusses, and I see no reason why induction, cognitive load, self-explanation, conflict, internalization, appropriation, and mutual modeling would not play well in cooperative learning. Though it is possible that other mechanisms that I cannot think of just now play better in cooperative learning than in collaborative learning.

    On the negative side, Dillenbourg's 1999 delineation of collaboration and cooperation seems, to me, to miss the concepts emerging in current conversations about cMOOCs. Jenny Mackness pointed to Stephen Downes' careful explanation about the differences between the two, and Dillenbourg's use of cooperation in this article does not match so well. Downes' distinction hinges on the differences between groups and networks and the role of the individual in each. In collaborative groups, individuals are subsumed under the group, becoming a part of the group, while in cooperative networks the individual is not subsumed by the collection of agents; rather, the network is an emergent property of the collection of individuals and their interactions. Dillenbourg's use of cooperation as mostly a difference in distributing the workload of the group misses most of the richness of Downes' use and affords very little help in understanding cMOOCs.

    On the other hand, Dillenbourg's use of the term collaboration seems reasonably consistent with Downes' use, so I assume that they are mostly talking about the same kind of system. Thus, I take away from Dillenbourg's article some approaches not to use with cMOOCs. For instance, collaborative groups for Dillenbourg and Downes imply a certain homogeneity in the collection of individuals: similar capabilities, actions, goals, and affordances, especially similar languages and technologies. cMOOCs, on the other hand, are open to heterogeneity, and any effort to explore and map a cMOOC must account for this heterogeneity, this openness to divergent actions, aims, abilities, and affordances. For instance, lurkers have negative roles in a collaborative group and are often eliminated, but they can play a very productive role in a cooperative network, or rhizomatic community.

    Dillenbourg's assertion that collaborative groups rely on synchronous communication doesn't match my understanding of what happens online in either collaborative groups or cooperative networks. I take the Linux project to be a monstrously successful collaboration, and I'm confident that group uses both synchronous and asynchronous communications to collaborate. I know that cooperative networks such as cMOOCs use both, so I see no need to limit either collaboration or cooperation to one or the other types of communication. I do see, however, a need to study how and why agents will chose one over the other and what each affords the agents in a system.

    Finally, Dillenbourg's handling of collaborative effects seems hampered by its focus on local causality. Both online and f2f collaborative and cooperative systems can be explored and explained as much, perhaps more, by circular and global causalities as by local causalities. Self-organizing systems can seldom be explained by the local pushes of the one-to-one interactions among its constituent agents. Rather, one must include the global pull of the larger, emerging system as it seeks a comfortable function and form within its ecosystem. Likewise, the learning that emerges within a complex system must include circular causalities which account for the continuous flow and feedback of information, energy, and organization among the individual agents and between the emerging system and its ecosystem. To grasp a cMOOC, our field of reality must be enlarged. For instance, the Rhizo14 auto-ethnography cannot simply ask if an instructional technique employed by Dave Cormier led to a specific learning in any of the Rhizo14 participants, as we might do in a traditional classroom. Rather, the group should expand its field to explore how Rhizo14 emerged and self-organized, shaping and ordering itself around various conversational spaces such as Facebook, Twitter, P2PU, blogs, and G+. What global causes pulled Rhizo14 into this particular organization? The group should explore how one conversation fed into another conversation, reshaping both conversations in a mutually causal feedback loop. What circular causes looped Rhizo14 into poetic expressions? Did DS106 and CLMOOC feed into Rhizo14? Has Rhizo14 fed back into those systems? These are the kinds of questions that must frame any discussion of a complex, multi-scale system, I think.

    Wednesday, July 2, 2014

    Investigating MOOCs, Part 2 of a #CLMOOC List

    This is the second in a series of posts about Pierre Dillenbourg’s 1999 article What do you mean by ‘collaborative learning’?, which introduces his book Collaborative-learning: Cognitive and Computational Approaches. I became interested in Dillenbourg when a Rhizo14 Facebook conversation favorably referenced him and this article. I wanted to see if his approach to studying learning provides guidance for those of us who are exploring rhizomatic learning, and I was delighted when Dillenbourg opened his article with a discussion of scales within learning groups, as I consider cMOOCs a function of complex, multi-scale networks (actually, I consider most everything a function of complex, multi-scale networks). Any investigation of a cMOOC must be aware of the scale or scales from which it is considering the cMOOC and must accept that its focus on any particular scale likely obscures or distorts equally relevant and valid processes, qualities, and affects/effects at work on other scales and that its own scale likely interacts in significant ways with those other processes, qualities, and affects/effects. Dillenbourg’s article, then, provided me with at least one positive approach to studying cMOOCs.

    However, in her comment to my first post, Jenny Mackness points out that Dillenbourg is talking about collaborative learning and from her point of view most cMOOCs are all about cooperative learning. Jenny writes:
    Cooperation in the sense of open sharing was more what the original cMOOCs were about. And indeed Stephen Downes at the time (2008) made a point of drawing attention to the difference between collaboration (groups) and cooperation (networks) and warned against the dangers of groups and group-think. … For me - MOOCs are still about cooperation. I don't participate in a mOOC for collaboration. For me collaboration might (and often has) been the result of my cooperative experience within a cMOOC.
    She is exactly right. cMOOCs are mostly about cooperative learning, in the sense that cooperation tends to emerge in the cMOOCs I engage and that cooperation keeps me engaged; thus, we should rightly question if Dillenbourg’s article about collaborative learning is relevant. I think his observation about scales is relevant, though his subsequent observations may not be. Still, they are worth reviewing as they may provide a useful contrast to other approaches to online rhizomatic learning. I have to keep in mind that this particular article is from 1999, 5 years before the emergence of Web 2.0 and almost 10 years before the first MOOC. At the time, Dillenbourg likely had no frame of reference for online, cooperative, self-organizing learning groups numbering in the thousands from across the world. So I want to look at the second and third elements of Dillenbourg’s collaborative learning, keeping in mind that he almost certainly did not anticipate cMOOCs.

    The variety of meanings for ‘learning’: Dillenbourg says that collaborative learning is usually defined as either a pedagogical method or a psychological process. He defines collaborative learning as neither, or rather as a bit of both:
    the words ‘collaborative learning’ describe a situation [italics in original] in which particular forms of interaction among people are expected to occur, which would trigger learning mechanisms, but there is no guarantee that the expected interactions will actually occur.
    The key to collaborative learning, Dillenbourg continues, “is to develop ways to increase the probability that some types of interaction occur”, and he suggest four ways to encourage interaction:
    1. to set up initial conditions: controlling for group size, group members, group arrangement, groupware used, suitable tasks, and so on.
    2. to over-specify the ‘collaboration’ contract with a scenario based on roles: forcing students to play different roles in some activity such as a discussion.
    3. to scaffold productive interactions by encompassing interaction rules in the medium: supplying structured responses (“I propose to …”) for students to complete or a set number of blog posts and comments.
    4. to monitor and regulate the interactions: performing minimal pedagogical intervention to redirect student work in a productive direction or to encourage students left out of the interaction. 
    As I understand him, then, the situation is a pedagogical method, and the learning mechanisms are the psychological processes triggered, or not, by the pedagogical methods. To my mind, Dillenbourg is not defining learning. I know his main topic is collaborative learning, but his sub-title is the variety of meanings for ‘learning’. I expect a definition of learning, but all I see is that learning, whether alone or in a group, is a psychological mechanism of some kind sparked by some given situation that encourages interaction among people. To be fair, Dillenbourg does note that we learn not because we are alone or in groups, but because we “perform some activities which trigger specific learning mechanisms” such as induction, deduction, compilation, explanation, disagreement, mutual regulation, and so forth. Still, he says very little about what this learning is. This does not encourage me. I’m discouraged even more when he characterizes interactions as social contracts between student peers or between students and teachers. I sense that I will have to work hard to realize some benefit from Dillenbourg’s thoughts here. I am almost certain that I will have to push beyond the way he unpacks these ideas.

    The way Dillenbourg characterizes learning in this article suggests to me staged collaboration in a closed class rather than open cooperation in the sense of a cMOOC or even open collaboration in the sense of Wikipedia, an xMOOC, or the Rhizo14 auto-ethnography. He says that “basically, collaborative learning takes the form of instructions to subjects (e.g. “You have to work together”), a physical setting (e.g. “Team mates work on the same table”) and other institutional constraints [italics in original] (e.g. “Each group member will receive the mark given the group project”).” I don’t know that this definition holds today even for collaborative learning in a classroom, but I’m certain it does not hold for online cooperative learning. This concept of collaborative learning is based on the traditional notion of a prepared course which marches a cohort of students (or subjects) through a fixed course syllabus toward some specified knowledge or skill and delivered, managed, and assessed by an authoritative teacher under the auspices of a sanctioning institution. The instructions to subjects (students) come from the teacher as an authoritative representative of the sponsoring institution. The physical setting, even when aided and mediated by computational devices, assumes a proximate cohort bounded by space and time. The institutional constraints embed the entire process in an institutional framework. This is all so brick-and-mortar.

    This is NOT a criticism. Rather, it is 1999. And in the short 15 years since, cMOOCs have pushed education beyond what our brightest minds were able to conceive and frame. Cooperative, online learning is basically the opposite of the collaborative learning that Dillenbourg describes.

    First, cooperative, online learning does not take the form of instructions to subjects. As the recent Rhizo14 and DS106 have demonstrated, open cMOOCs can function quite nicely without an authority figure giving instructions to his subjects. (Yes, I'm playing with the regal overtones of the term subject here, which I don't think Dillenbourg implies, but it makes my point. My apologies if I offend.) Open, online learning is certainly full of suggestions, often too many to process, but these suggestions must be framed quite differently from the instructions in a traditional educational system.

    Then, cooperative, online learning does not have a physical setting, or rather is not limited to a physical setting, a prescribed space and time. It is not even limited to an online setting. Space and time become very fluid concepts in open, online learning systems. Participants engage as they can with the tools at hand, when they can, where they can, with whomever they can. This relaxation of a specific and specified space and time is quite disorienting to many when they first engage an open, online space. This fluidity disrupts the normal relationships among people, who become confused about who is in and who is out (I think the whole freaking world is in, but that's just me), perplexed about how to relate, when to assert, when to hold back. The familiar social contracts seem to melt, and attempts to reform them seem to flounder. Not only do the familiar relationships among people fade, but the relationships to content become disjointed. Am I learning? If so, what? (As Bob Dylan once said, "There's something going on here, but you don't know what it is, do you, Mr. Jones?").

    Finally, cooperative, online learning has almost no institutional constraints: no grades, no certificates, no ceremony, no sanctioned value. If you want value out of a cMOOC, then you have to create it for yourself with others. No one tells you the answer.

    What are the implications here for research into cMOOCs? Mostly, we have to rethink everything. First, we must rethink the relationships among the participants. The old social contract assumed stable, discrete entities who formed stable relationships made explicit by contracts. Any violation in the terms of the contract dissolves the relationship. In the cMOOCs I like, leaders and groups wax and wane, emerge and fade. I constantly shift from lurker to speaker to leader to follower to in the group to out of the group, as do others. Relationships are very fluid. Are we learning together, or are you researching me? Sometimes it's hard to tell, so how do I relate, and do explicit rules make much sense? Finally, we must rethink how we determine the value gained from a course with no answer and no one purpose. How do I know when I'm finished? Am I still in Rhizo14? Have I really started CLMOOC?

    It's hard to say, but that's what we are proposing to study.

    Sunday, June 22, 2014

    How to Study a cMOOC: A list for #CLMOOC

    I’ve joined CLMOOC, and the first two tasks are underway:
    1. to create a how to as a way of introducing ourselves, and 
    2. to create a list.
    This is my attempt to do both at the same time. I propose here a list of approaches to studying cMOOCs, such as CLMOOC and Rhizo14. Many of my Rhizo14 friends are here as well, so they will recognize some of the themes I touch on here, and those who are not familiar with me will learn something about me. This series of posts that I propose to write (I already see that I can’t do this all in one post) comes from a Rhizo14 Facebook conversation that started when Maha Bali asked how Rhizo14 was different from earlier cMOOCs such as CCK008. She sparked a long conversation that is well worth reading, but along the way, someone mentioned Pierre Dillenbourg’s study of collaborative learning. I was not familiar with Dillenbourg, but he seemed to have some respect amongst the Rhizo14 group, so I moved him to the top of my reading list to see if I could learn something about how to investigate a cMOOC, which I take to be a particularly enjoyable and rewarding instance of collaborative learning.

    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.

    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.
    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.

    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.