Why Rhizomatic Learning, Pt. 2 #etmooc

In my last post, I said that networking is the lens through which I see most everything, or at least I try. I confess that I still have some old habits of mind, mostly that I'm unaware of, but when brought to mind, I do try to address them. I quoted Olaf Sporns comments that science is increasingly using the networking metaphor to guide both its subject matter and its research. I want to comment on a couple of points he made, and I quote:

Increasingly, science is concerned with the structure, behavior, and evolution of complex systems such as cells, brains, ecosystems, societies, or the global economy. To understand these systems, we require not only knowledge of elementary system components but also knowledge of the ways in which these components interact and the emergent properties of their interactions. (1)

Note first that he although he started with the term networks, mid-stream he switches to complex systems, the same term that Edgar Morin uses. In my reading, these terms have often been used interchangeably, and I will likely do so in my own discussion, unless I find some reason to distinguish between them.

Second, Sporns captures neatly the distinction between the reductionist, mechanistic clockwork type of science with its focus on "knowledge of elementary system components" and the evolutionary, organic networking type of science with its focus on "knowledge of the ways in which these components interact and the emergent properties of their interactions." This shift in metaphors, or paradigms if you prefer, is extremely important for me.

Although Sporns and I do not share similar disciplines—he studies and teaches neuroscience and I study and teach writing and literature—his work has a critical, core benefit for me: Sporns insists and demonstrates through exhaustive research that cognition is a network phenomenon. I accept his argument, as I have not found a better, more detailed, more precise description of how the brain works. I was pleased, then, to read James Zull's educational book The Art of Changing the Brain (2002) which applies the networking paradigm to learning and draws out some implications for teaching and pedagogy. Networking, of course, is at the heart of Connectivism. Throughout his writings, Stephen Downes makes a number of statements that express knowledge and learning as network phenomena. For instance, in the 2011 post What Networks Have In Common, Downes says, "the state we call 'knowledge' is produced in (complex) entities as a consequence of the connections between and interactions among the parts of that entity." I could no doubt find even more pointed pronouncements in Downes' writing, but this is sufficient. In his online book Knowing Knowledge (2006), George Siemens says, "Knowing and learning are today defined by connections ... connectivism is the assertion that learning is primarily a network-forming process" (15).

For me, then, learning is the ability of an entity to recognize, build, and traverse networks. Moreover, the tools entities use to recognize, build, and traverse networks are themselves networks, and knowledge is an emergent property of the interactions among and across those networks of neurons, sensory organs, sound waves, light waves/particles, classrooms, social groups, languages, the Universe … as far out or in as you wish to take it.

Anyone who has read Downes and Siemens will see that nothing I say here is new. Those fellows have already said it, and in general, I agree with them (details are always problematic, but that doesn't concern me here). Learning is networking across multi-scale networks, and that has huge implications for the way we teach, but is learning rhizomatic? Perhaps a better way to ask this question is what does the concept of the rhizome as developed in Deleuze and Guattari's book A Thousand Plateaus bring to connectivism that it doesn't already have? This is similar to a question I have heard Siemens ask of Cormier in some of our previous MOOCs, and it merits an investigation, if not an answer. I'll try to do that. Tomorrow.

WAC 4: ePortfolios

I have grounded my concept of a writing across the curriculum program (WAC) in connectivist theory: that knowledge and communication are network phenomena, a function of mapping and traversing complex, multi-scale networks. As Stephen Downes says in his post Types of Knowledge and Connective Knowledge, "connectivism is the thesis that knowledge is distributed across a network of connections." To my mind, language is one of our primary tools for mapping and traversing these networks. Indeed, language is more than a tool—language is a fundamental part of the knowledge and communication networks themselves. Language is like DNA: it is the tool and instructions by which the organism/network emerges, it is part of the scaffolding of the emerging organism/network, and it is part of the maintenance system for the emerged organism/network. Language, like DNA, is woven into the very knowledge and communications that emerge from its play. It's a bit like making the blueprints and hammers and saws part of the house they are helping to build.

But this is still a very abstract concept that may not have an intuitively obvious application. A core, practical application in my WAC is the ePortfolio, an ideal application that fits nicely into a connectivist, network perspective. I'll say why, but first let me point out that I am not saying that ePortfolios are connectivist. A constructivist, cognitivist, or behaviorist can use ePortfolios as well as any connectivist, but I particularly like a connectivist take on ePortfolios. Here's why, and let me cite my source up front: Jonan Donaldson's article Digital Portfolios in the Age of the Read/Write Web in the current issue of Educause Review Online. Mr. Donaldson, an instructional designer at Oregon State University, says all of the things I want to say about ePortfolios and more, so I'm leaning on him heavily in this post.

The first key feature of ePortfolios is that they have emerged from the read/write web. I began using ePortfolios when the e(lectronic) in ePortfolios meant a PowerPoint burned to a CD. This was decidedly old-school and not very network aware. All that is changed, and now ePortfolios are best understood as a function of complex, multi-scale networks. This implies that all ePortfolios are on the open Web and not locked within some organizational silo and that they are owned and managed by the student.

Jonan Donaldson lists a number of affordances provided by ePortfolios:

• ePortfolios help shift from teacher-centric education to student-centric education, as students become active producers of knowledge rather than passive consumers of knowledge. Rather than simply learning the eternal truth from their teachers, students use ePortfolios to create connections among their bits of personal knowledge and the people they encounter in school. This fits well with Downes' contention that "The very forms of reason and enquiry employed in the classroom must change. Instead of seeking facts and underlying principles, students need to be able to recognize patterns and use things in novel ways. Instead of systematic methodical enquiry,… students need to learn active and participative forms of enquiry. Instead of deference to authority, students need to embrace diversity and recognize (and live with) multiple perspectives and points of view." ePortfolios can provide the scaffolding for this approach to learning.
• ePortfolios provide students with intrinsic motivation. As Donaldson points out, "Turning consumers of knowledge into producers of knowledge transforms learning into an active experience." Mapping networks is not a passive activity, and it requires some intrinsic motivation. Deleuze and Guattari make this clear in their distinction between mapping and tracing the rhizome. Traditional education is largely a matter of tracing which depends on extrinsic motivations such as rewards and punishments rather than mapping which relies on intrinsic motivations.
• ePortfolios enhance student autonomy. Donaldson says, "Not only can students individualize the look and feel of their portfolios through templates and design options, they can also enjoy increased individualization of content and the delivery format of portfolio artifacts." ePortfolios let students "recognize patterns and use things in novel ways" and "learn active and participative forms of enquiry." In other words, it helps fit the knowledge to the student rather than fit the students to the knowledge. (Many may seem autonomy as inconsistent with networking, but this is a misunderstanding of networks. Each node in a network must maintain its own autonomy and integrity to perform its role in the network and to make the network what it is.)
• ePortfolios enhance collaboration. Donaldson notes wryly that "it is often said that we learn best when we do, but perhaps it would be more appropriate to say that we learn best when we do together." A network demands collaboration and cooperation (in Downes' sense of the term) among its various nodes, and research shows that when students connect to (network with) a teacher, another student, or a community of practice, then they are more likely to stay in college and succeed.
• ePortfolios enhance digital literacy, as Donaldson notes, "incidentally while tackling the learning objectives at hand." Students learn to recognize, validate, and use a wider range of patterns in different kinds of data and information (text, image, video, audio, number, and more), and they learn to orchestrate this data into coherent, appealing documents. These are incredibly valuable skills.
• ePortfolios enhance students' digital image. Most of today's college students already have digital image that is unfortunately not under their control and not always positive. Building an ePortfolio helps the student to learn how to build a professional brand and why that brand is important. The online world is not going away, and our students must know how to navigate it and use its powers.
• ePortfolios enhance students' 21st century writing skills. As Donaldson says, modern writing means "being able to create digital content that conveys information effectively for dissemination through websites, blogs, wikis, online presentations, illuminating graphics, audio content, and video content." This ain't your grandma's writing. Rather, this is the production of illuminated manuscripts: documents illuminated with image, video, sound, calculation, hyperlinks, and yes, text. ePortfolios help us learn this kind of writing, the kind of writing we will do in the 21st century.

I want to add to Donaldson's list that ePortfolios connect students to their communities of practice—first as students and then as fledgling professionals. Blogs, Twitter, RSS feeds, and more tools that can be aggregated on an ePortfolio help connect students to their personal learning networks and to their communities of practice. They connect to each other to get through school and then to practicing professionals to join a profession.

Finally, perfect WAC would include ePortfolios from the faculty and staff. I know of no better way to teach students how to build an ePortfolio than by building one myself.

Yes, ePortfolios.

More Agency, Rhetoric, and Connectivism

If agency is the ability to recognize and respond to the surround, then does agency fit with connectivism? Yes. In fact, I can't think of an educational theory that agency does not complement. Education is hardly understandable without some notion of agency on either the teacher's part, the student's part, or usually both parts. But is agency in connectivism distinguishable from agency in behaviorism, cognitivism, and constructivism? I think so.

In her article Rhetorical Agency as Emergent and Enacted (CCC 62:3, 420-449), Marilyn M. Cooper locates her concept of rhetorical agency in the same theoretical framework as connectivism: complexity theory, and for her the acting agent is a complex system within a complex system. She is quite clear that the agent is not a classical subject, or a "centered, conscious, rational self", and she defines her task as rescuing the notion of agency from the "death of the subject" (420). She begins this rescue by denying the existence of the subject: "a workable theory of agency requires the death not only of the modernist subject but of the whole notion of the subject" because "the subject is inescapably defined by an agonistic relation to the object/other: the subject attempts to control the object/other in order to escape being controlled" (423).

As I understand her, Cooper is troubled by the inherent and unavoidable power struggle in a modern, reductionist view of the subject – a view I associate with behaviorism and cognitivism. As long as we view agents as discrete subjects distinct from and independent of the objects/others around them, then we cannot avoid sliding into issues of power. Indeed, the agency of a modernist subject can only be viewed in terms of power: the ability of the subject to effect change in an object through the exercise of power, however benign or well-intentioned. This idea of agency as power neatly captures the traditional notion of education: a teacher/school effecting change in students through the exercise of power, usually well-intentioned. We then measure the amount of change in the students to determine the efficacy of the teacher/school. It's a wonderfully simple model that seems as if it should work. One could almost wish it did.

Cooper replaces subject with actor/agent, which she borrows from Bruno Latour's Actor-Network Theory: "Unlike subjects, agents are defined neither by mastery, nor by determination, nor by fragmentation. They are unique, embodied, and autonomous individuals in that they are self-organizing, but by virtue of that fact, they, as well as the surround with which they interact, are always changing" (425). Agency is an emergent property of the interactions of agents with their surround, "the process through which organisms create meanings through acting into the world and changing their structure in response to the perceived consequences of their actions" (426). In other words, we perturb the world, Prufrock notwithstanding, and the world perturbs us in return. In the patterns of this interaction, we come to recognize and know our intentions and agency. Does this complex agency have a place in connectivism? I think so.

Both Cooper's concept of agency and connectivism, then, are grounded in complexity theory. In his blog post What is the unique idea in Connectivism?, George Siemens says that connectivists "find support for connectivism in the more nebulous theories of complexity and systems-based thinking." In his article Learning Networks and Connective Knowledge, Stephen Downes notes that knowledge itself is an emergent property of the interactions of neurons: "human thought amounts to patterns of interactions in neural networks." Knowledge does not lie in any neuron or any grouping of neurons but in the emergent patterns of neuronal interactions and networking.

While Siemens and Downes both ground their thinking in complexity theory, I find the most useful treatment for agency in David Cormier's concept of the community as curriculum. In his 2008 article Rhizomatic Education: Community as Curriculum, Cormier describes how curriculum itself can be an emergent property of a community of learners: "In the rhizomatic model of learning, curriculum is not driven by predefined inputs from experts; it is constructed and negotiated in real time by the contributions of those engaged in the learning process. This community acts as the curriculum, spontaneously shaping, constructing, and reconstructing itself and the subject of its learning in the same way that the rhizome responds to changing environmental conditions."

To my mind, Cooper's concept of agency fits quite nicely into Cormier's community as curriculum, particularly as expressed in connectivist MOOCs. Agency, curriculum, and knowledge all emerge as properties of the interactions of a community of learners, and all three are the trajectories of the patterns of interactions among the various nodes of the community. As learners join a community such as a MOOC, their very presence (even lurkers) perturbs the community, which in turn feeds back into the learner's own mind. The dynamic interplay and interaction of learners, artifacts, and network enables patterns of intention and mapping, in Deleuze's terms, to emerge, and our awareness of these patterns helps us to articulate, mentally and physically, the agencies, knowledges, and curricula that bubble up out of the brew.

I think I have more to say about agency and the rhizome, especially in light of Cormier's use of the term and Cooper's dismissal of Deleuze and Guattari, but not tonight.

The Nodes and Edges of Connectivism

I've just finished reading Scott Weingart's Demystifying Networks, Parts I & II, in which Mr. Weingart tries to correct the misuse of networks by humanities scholars. He provides a basic and quite clear explanation of what networks are and what they are not, how current technology can analyze networks, and what technology can say about networks, and most importantly, what it cannot say about networks.

Along the way, he provides the DNA for networks, and this reminds me of how fractal and complex networks are, with networks nested within networks and interacting across multiple scales. If networking is part of the DNA of connectivism, then what is the DNA of networking? Weingart gives me a few handles to work with.

He starts his discussion by defining networks in a typical fashion: networks "stand for any complex, interlocking system. Stuff and relationships [emphasis in the original]." He calls the stuff nodes and the relationships edges, in keeping with common terminology. A network, then, is a collection of nodes that are in some way related along recognizable edges. Stuff and relationships, or nodes and edges, are part of the DNA of networks. This is simple and intuitive enough, and Weingart makes this definition directly applicable to connectivism when he notes that

generally, network studies are made under the assumption that neither the stuff nor the relationships are the whole story on their own. If you’re studying something with networks, odds are you’re doing so because you think the objects of your study are interdependent rather than independent. Representing information as a network implicitly suggests not only that connections matter, but that they are required to understand whatever’s going on.

Starting with these basic concepts, then, I immediately think that there isn't any information – or any other thing, for that matter – that cannot be represented as a network. Indeed, I agree with Weingart "not only that connections matter, but that they are required to understand whatever's going on." I think this is Downes' point when he says on his blog, "At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks."

Both the Universe and our knowledge of it are network phenomena. Actually, I already object to that statement as it seems to suggest that our knowledge is something apart from the Universe. It isn't. Our knowledge is somehow an active node in the universal network, connected along multiple edges, just as natural an emergent phenomenon as rocks are.

I don't know that either Weingart or Downes would completely agree with the statement that everything is a network phenomenon, but it makes sense to me. I can usefully model everything as a network – this very post, for instance.

This post is a multiscale network: nodes joined by edges to form the nodes joined by other edges at other scales. As nodes, letters network to form morphemes, which network to form words, which network to form sentences, which network to form paragraphs, which network to form posts, which network to form blogs, which network to form conversations, and so on. And this covers just the syntactical view of the network. We can then look at the semantic networks in which subject, verbs, objects, and other nodes network together to create concepts, which network together to create arguments and explanations, which network together to create a belief system, which network with other belief systems to create a conversation, and so on.

It is quite useful to me, then, to think of this post as a network structure, and whatever knowledge emerges herein "is distributed across a network of connections" that shifts in scale from letters and morphemes to conversations about networks, education, and knowledge. This knowledge emerges for me as I write – adding, rearranging, deleting, and shifting words and sentences about – and for you as you read – scanning for patterns of meaning using the syntactical cues I've left behind. I hope that the pattern of knowledge that emerges for you as you read this post is reasonably similar to the pattern of knowledge that is emerging for me as I write this post. If the two patterns are reasonably self-similar (and I'm not exactly sure how we can ever establish that for certain), then I will believe that I have communicated my message to you, that I have somehow transferred knowledge from me to you, even though we both know that nothing was transferred.

But there is no guarantee. Every speaker, writer, or actor is aware that an audience can perceive very different patterns in the same configuration of words, sentences, and paragraphs. My father – an old-fashioned, hellfire-and-brimstone preacher – frequently remarked that most of his congregation heard sermons that he never preached. The message they heard depended more on their own sense of guilt and sinfulness than on his choice and arrangement of words.

Once this post is published, then, it becomes a node in a network of people (you and I) who each engage the overall network of writer, reader, and text from different vantages. It should be no surprise, therefore, that knowledge emerges in different ways for each of us, sometimes slightly different, sometimes radically.

If nothing else then, the complex, multi-scale, network nature of writing helps me understand and explain why even a simple piece of writing such as one of my brilliantly clear and concise writing assignments can receive such divergent interpretations, with almost every student doing something different. If knowledge was a discrete, transferrable thing, then I could give all my students the same thing, but because knowledge is an emergent pattern scattered across a network of words, I can hope only for a reasonably similar pattern blossoming in the minds of my students. Sometimes the magic happens. Sometimes it doesn't.

What's the Matter with MOOCs?

In a recent Chronicle of Higher Education article entitled What's the Matter with MOOCs?, Siva Vaidhyanathan dismisses the current obsession with MOOCs as "something that very wealthy private institutions offer for free, at a loss, as a service to humanity." He adds insult to injury by adding that he, indeed, enjoys MOOCs: "Let me pause to say that I enjoy MOOCs. I watch course videos and online instruction like those from the Khan Academy … well, obsessively. I have learned a lot about a lot of things beyond my expertise from them. My life is richer because of them. MOOCs inform me. But they do not educate me. There is a difference."

Those of us who have actually been in a MOOC will find Vaidhyanathan's argument silly at best and outrageously unfortunate at worst (kudos to John Mak for trying to correct Vaidhyanathan's errors). His failure to understand MOOCs is catastrophic and staggering. Vaidhyanathan has failed scholarship and done a great disservice to the Academy and its conversation about MOOCs, which have almost nothing to do with online video banks or rich, private universities, but with collaborative communities created more often than not from somewhat remote, public universities. Still, I suppose this sort of misunderstanding is bound to happen.

Eventually, any theory or practice worth its salt moves beyond its origins and begins to take on a life of its own. The same will happen to Connectivism. Others will begin to define and shape Connectivism, perhaps in ways that Downes and Siemens do not anticipate and will not support, but it will happen if Connectivism doesn't die first. It seems to be happening more quickly with MOOCs. Luck of the draw?

I'm not sure, but I do have a connectivist/rhizomatic explanation for it that turns me back to my own discipline of writing. A newly-minted theory (and Connectivism is still rather new in the history of educational theory) is like a newly-minted book (or a newly-minted baby, nation, or computer system): it has a generative point with a rather limited DNA, but once it is released into the eco-system, then the theory (or book, baby, nation, system) takes on its own life, direction, and development that the originators (or writer, parents, founders, inventors) seldom anticipate and never control. I'm reminded of a story about Robert Frost reading his poem The Road Not Taken, and afterward, responding to a young woman who asked him what the famous poem really meant. He asked her in turn what she thought it meant; whereupon, she spoke at length. When at last she concluded, he said that, from then on, that's what the poem would mean to him.

I don't know if the story is factual, but it is true, and Frost was wise to understand that the meaning of his poem no longer belonged to him, unless he wanted to rewrite the poem, and then it would just be another poem that he would eventually lose control of.

Of course, Cormier, Downes, and Siemens, along with others, are still writing Connectivism and MOOCs, and I'm certain that they still have points to add and clarify, but really, they can only supply the generative DNA. The growth and development of Connectivism and MOOCs will depend on so much more. Let's hope that they enjoy watching their baby grow.

Connectivism and Complexity

Well, I look around, and it's been a month since I've written. How does that happen? I could list the details, but they aren't that interesting – family, work, and medical appointments mostly. Fortunately, all is well with my world.

The sad part for my blog is that I've lost my train of thought. As I recall, I was thinking about networking as part of the DNA of connectivism, and the DNA comment elicited a comment from Stephen Downes about my confused attempt to reconcile connectivism and essentialism. My last post was an attempt to figure out why Downes thought I was trying to reconcile the two concepts when actually I was trying to establish that DNA did not imply an essentialist approach. Was it poor writing, poor reading, or a mix of both? And did connectivism have an explanation for that kind of communication failure?

Those are good questions, and I will attempt to come back to them and to the general issue of networking as one of the generative concepts of connectivism sometime in the future, but today (July 4th, as I start this post with a free morning. Happy Birthday, USA) I want to talk about a second bit of DNA in connectivism: complexity. I've just finished reading Melanie Mitchell's Complexity: A Guided Tour, and the topic is on my mind.

To my mind, complexity is concomitant to networking. We can think of networks as static, fixed entities, much like the pictures in our books, as shown to the right (thanks to Scott Weingart's Demystifying Networks, Parts I & II in the Journal of Digital Humanities for this pic and lots of other ideas about networks that I intend to explore later):

This is a helpful abstraction of networking, but it misses much that is interesting about networking: the dynamism which results from the nodes of the network engaging each other and the larger eco-system. This dynamic engagement is complexity. Rather, this is what I mean by complexity, and I think that complexity is one of the amino acids in the DNA of connectivism. As with the concept of networking, complexity is not unique to connectivism. A scholar can follow a constructivist or behaviorist agenda, for instance, and incorporate both networking and complexity. However, I think a scholar can still be a constructivist or behaviorist without accounting for networking and complexity. I don't think that a connectivist can do so. These two concepts are part of the DNA.

If Mitchell is correct, then complexity is not a settled scientific term. As she says: "There is not yet a single science of complexity but rather several different sciences of complexity with different notions of what complexity means" (95). This provides me with some wiggle room to decide what I mean by complexity, but I do not stray far from Mitchell's own use of the term in her discussions of information, computation, analogies, and information processing in living systems. It seems to me that complexity is the amount and/or degree of engagement of an entity with its ecosystem – or to put it in terms of networking: the amount of engagement among the nodes of a network and between that network and other networks.

This definition lands me squarely in the issue of information and information processing, of which my own discipline, writing, is a subset. So I really like this definition, and for the moment it is the one I will use. For me, then, complexity is the degree to which any node in a network can recognize, process, and respond to information from the other nodes in its network and from other networks at different scales. This information processing appears to extend throughout reality from simple, almost mechanical physical and chemical reactions through the ideas and societies of humanity and beyond to God, Gaia, or whatever you may believe exists at some network scale beyond us. Information processing stitches the universe together and drives it through its unfolding expressions, including us humans and our societies and languages. It may be, as Mitchell suggests, that we humans may someday consider information as one of the fundamental aspects of the Universe along with mass and energy, but … I'm getting way beyond my level of competence. That is sheer fantasy for me; still, it's of vital interest to me that information processing seems to be such a core function of life.

Mitchell describes several ways that this information processing occurs in different systems from immune systems, neural networks, and ant colonies to genetic and metabolic networks. In all of these systems, if I understand her argument correctly, the individual nodes (neurons, ants, lymphocytes, etc.) are able to recognize patterns in their own network and in their ecosystems (some nodes work locally in their own networks and some globally beyond their local networks). These patterns are the information that each node can process, or understand, and can then respond to. This seems to me to match quite nicely with Stephen Downes' contention that human knowledge has much to do with pattern recognition and with negotiating our way through networks. While human thought may work at a different scale of complexity than, say, a lymphocyte binding to an antigen, the concept is similar, or fractal: the same pattern at a different scale.

To some degree, each network node (from bacteria, to slugs, to Senators in the US Congress – though those scales may not be that different) is able to process and to respond to the information it gleans from its environment. It then can realign itself with its network, which changes the network, which leads to further changes in the node, which leads to further changes in the network. This dynamism in the network, or organism, is complexity. While this dynamism is usually regular, it is probabilistic rather than deterministic, even at the most elementary physical and chemical scales, and it is this element of chance that probably lead to the emergence of COMPLEXITY as the term of choice for naming it. It is also self-organizing, so that the few possible actions of any one ant can lead to quite sophisticated  behaviors of the ant colony. Such dynamic information processing can also lead to a sonnet, or a blog post.

Okay, this is what I mean by complexity, and I insist that it is at the heart of connectivism along with networking. I'll explore both concepts more in future posts.

Writing to Learn Connectivism

Stephen Downes was kind enough to comment on my last post, and that's a good thing. His comment brought a fair number of visitors to my blog, giving that post as many hits as any other I've written.

But alas, it seems that I was not very clear in what I was trying to say. Stephen complains that:

Keith Hamon ties himself in knots trying to reconcile essentialism and connectivism. And I don't think he helps himself adding DNA to the mix. "Richard Cartwright has defined essentialism as 'the view that, for any specific kind of entity, there is a set of … attributes all of which are necessary to its identity and function.'" But there are many things for which essentialism is false. As Wittgenstein famously argues, consider the definition of 'game'. There's nothing essential to being a game. For every property you can think of - competition, rules, points - there are exceptions. Or consider membership in a family. People in a family resemble each other, but there is no one trait that their [sic] all share. What makes them a family is that they are connected, not that they share some essential trait. In many ways, connection replaces essentialism, and does not need to account for it.

Quite likely I did tie myself in knots in that post, though from my point of view, I was untangling a knot. I was trying to untangle an issue in my head, and now that I've done it, it is really quite straightforward, so let me now write the post I should have published.

I've been trying to define Connectivism without resorting to the essentialism and reductionism typical of most definitions, relying instead on complex, multi-scale networking to frame my definition (I was, in fact, replacing essentialism with connectivism). I had been using some language from Edgar Morin's book On Complexity, including the concept of DNA. Gradually, I realized that DNA as a concept could be too easily shaded with Essentialist overtones, and that would be problematic for my argument. So I wanted to see if I could show how Morin's concept of DNA does not necessarily imply Essentialism. I decided that DNA avoids essentialism in two ways:

1. it is a start point for an entity, not an end point, and
2. it is specific to one entity, not many.

That's a rather short post and likely would not have caught Stephen Downes' eye; however, I didn't have my conclusion when I started writing the post. I was just pulling at the tangle of thought until I had it unraveled, at least in my own mind.

The more interesting question now, though, is how did Stephen and I miscommunicate? It would be trite  to say merely that I didn't write well, or that Stephen didn't read well, or perhaps a bit of both. Is there a Connectivist explanation for this kind of communication where the meaning in the author's head does not seem to match closely enough the meaning in the reader's head? There should be. So let's sketch some outlines that might suggest how and why this communication fell out as it did.

First, keep in mind that this post is itself exploration rather than an explanation. I may be able to explain whatever emerges—if anything—more clearly later, but I can't now. Just now, I'm playing, pushing around some ideas that just might work, but no guarantees.

I'll start with what I was doing—my writing—mainly because I can speak with some authority about that. I've been writing for decades, and I've paid attention to how I write. I'll have to be far more general and speculative about Stephen's reading, as I don't know his particular reading habits.

I was writing the previous post in a writing to learn mode. This is one of two large modes of writing that I introduce to my students:

1. writing to learn, and
2. writing to communicate.

Perhaps you think that any writing loosed on the public, such as blog posts, should be writing to communicate, but I don't think this is the case. So what's the difference between the two? Writing to learn is mostly for ourselves while writing to communicate is mostly for others. It's a shift along a sliding scale rather than a shift in kind, however, but it is an important shift. When we are writing to learn, we are using writing as a tool for rendering explicit to ourselves what we know. When we are writing to communicate, we are using writing as a tool for engaging others.

In a connectivist sense, then, when I wrote my post I was using written language to externalize the patterns of thought in my mind. I was creating a text as an external artifact onto which I could arrange and play with my thoughts. The text, the post, became an other somewhat removed from me, with which I could converse. I would write a phrase or sentence, and then stop to read it, looking for a match between the patterns I felt, sensed, or thought in my mind and the patterns I read on the screen. Sometimes the sentence spoke back to me, or stained me, in a way that felt right, and I would keep the sentence, but more often than not, the sentence did not stain me in quite the right sense, and so I would change it. I would erase it and try again. Or sometimes, I would just leave it and move on to try again.

The post became, then, another node in the network of interactions that formed my thoughts about essentialism and DNA and connectivism, but it is a node with some peculiar affordances (thanks again, Bon) that renders thinking more productive in certain ways. First, it became an explicit thing, outside my head. This is of inestimable value. While a few people can structure and manage quite well the thoughts in their heads, most people, including me, lack that ability. My thoughts are too often jumbled—and when they are crystal clear, I seldom know why—and I can go over and over the same idea in my head without ever moving it forward, but as soon as I put it on screen or paper, then it seems to stabilize. It becomes an explicit, external object that I can work with. I can assess it's value, shape, and meaning, and decide whether or not it meets my needs. I too often find that hard to do in my head alone.

Then, the post became another node in the pattern of meaning that I was trying to create through my thinking and writing. As such, the post fed back into my head the thoughts that I had written, and those written thoughts began to interact with the mental thoughts, each affecting the other. I thought something, I wrote something, that fed back into my thoughts, and that fed back into my writing, over and over. It is a reiterative process that constantly maps back and forth, in and out, as the thoughts in my head feed into the thoughts on the screen which in turn feed back into the thoughts in my head. Each loop modifies the the internal and external thoughts, tweaking the patterns until I feel (it really is a feeling for me) an elegance and coherence between the text and the thoughts. The great rock guitarist Duane Allman used to speak of "hitting the note," of how he would play all night looking for that one note that pulled the whole performance together. That really is the feeling I'm looking for, and sometimes I have to write, or play, a long time before I find the pattern, or note, that pulls it together for me. It is the process that Deleuze and Guattari describe as cartography and decalcomania: a reiterative mapping between mind and reality, trying to shape the patterns in each in ways that are useful for ones life. I had to write a long time in that post to find out what I was trying to say. I had to play a long time to "hit the note."

This is writing to learn. And I think it is the part of writing that my students are most challenged by and least convinced of its value. It's also the part of writing this is too often least useful for readers, though its value for writers is inestimable.

This feedback loop, this mapping to use D&G's terms, is an integral part of Connectivism and Rhizomatic learning, I think. I know it is an important part of writing. It describes how we gaze upon the text and it gazes back at us. It describes how we push the text and it pushes back. Our thoughts feed into the text, and the text feeds back into our thoughts, and the loop continues round and round until we feel at peace somehow with the place that the text occupies in our thoughts. We come to terms with the text, our own creation, and we accept it as a fair node of the network that is our knowledge.

This does not mean, however, that the text is yet suitable for a reader. Quite likely it isn't. I'll talk more about writing to communicate next.

Connectivist DNA: Epistemology #cck12

I started this post weeks ago, but life happened. I want to continue talking about defining Connectivism.

So if we are to avoid a definition of Connectivism that disjoins the theory from similar theories and from the rest of the world and reduces the theory to a handful of essential characteristics how should we proceed? Morin says that we proceed by "distinction, conjunction, and implication" (51). I guess that clarifies things. Let's see.

We distinguish Connectivism as a theory about education without separating it from other such theories about education and without separating it from the very thing that it seeks to illuminate: Education. We look for both the particular starting point of Connectivism and the connections that Connectivism affords us (connections should be easy for a Connectivist theory). The starting point is the DNA; the connections are the flows of energy, matter, organization, and information between Connectivism and its eco-system. Thus, we distinguish Connectivism from Cognitivism, say, but we do not disjoin it from Cognitivism. Rather, we include in our definition the flows of energy between the two. Likewise, we look for the flows of energy and information between Connectivism and all those who have explored it and between the theory and the actual practice of Education. We also include our own DNA and the DNA of others who are exploring Connectivism. We assume, then, that Connectivism is defined by the dialogue, the unresolved tension and interplay, between its DNA and its eco-system. Connectivism is what emerges within this dialogue. This is a start.

For me, the first bit of Connectivist DNA is found in its epistemology. This is not a casual choice, but one that reflects my interest in rhetoric, my own intellectual DNA. In his book Rhetoric and Reality (1987), James Berlin says that the rhetorics of the 20th century can be defined by their epistemologies. In fine Cartesian fashion, he disjoins the three main strains of 20th century rhetoric and reduces each to a central tenet about how knowledge is generated and propagated. I have an interest, then, in what a Connectivist, or rhizomatic, rhetoric might look like, so I want to follow Berlin's lead—if not his methodology—and begin with epistemology. Given that Education is all about the generation and propagation of knowledge, epistemology has much to recommend it as a starting point.

So what is the epistemological DNA that Connectivism brings to the eco-system? Both Downes and Siemens write about knowledge, but I'm drawn first to Downes' 2005 article An Introduction to Connective Knowledge, mostly because I'm familiar with it, but also because it has received significant reading from others and, finally, because I just reread it. For me, this article makes about as clear and concise a statement about knowledge as an article can make when it says that "Knowledge is a network phenomenon, to 'know' something is to be organized in a certain way, to exhibit patterns of connectivity. To 'learn' is to acquire certain patterns. This is as true for a community as it is for an individual."

At the heart of Connectivism, then, is this idea that knowledge is not some thing, like a nugget, that we can pass among ourselves and reduce to a nifty definition. Knowledge is not a nugget that resides either in objective, external things or in a subjective, internal mind. Rather, knowledge is a function of complex networks. Knowledge is the pattern of dynamic connections among various nodes regardless of whether the nodes are neurons in an individual brain, people within an individual community, communities within an individual society, or societies within an epoch. Knowledge is what emerges from the patterns of interactions of millions of individual neurons functioning according to their own rules of behavior and in response to the rules of the clusters of neurons they have joined or found themselves grouped with. Knowledge on a different scale is what emerges from the patterns of interactions of millions of individual people according to their own rules of behavior and in response to the rules of the clusters of people they have joined or found themselves grouped with. While the specific mechanisms and rules may vary from node to node and scale to scale, the pattern seems remarkably consistent: meaning and knowledge emerge from the unresolved, dynamic interplay between an individual node and its network/s of other nodes.

This view of knowledge seems to me to be different from that of other educational theories. Behaviorism, as I understand it, appears to place meaning and knowledge firmly in the objective, external world of observable, measurable behaviors, and it focuses on developing those behaviors. Cognitivism, on the other hand, places meaning and knowledge in the subjective, internal world of the mind, however defined, and it focuses on developing those cognitive skills and resources. As I understand constructivism, it places meaning and knowledge in the interaction of the individual mind with reality. Social constructivism expands the concept by adding the social group to the mix so that meaning and knowledge is created by the individual in her interaction both with reality and the group. Social constructivism, then, focuses on developing those interactions among the individual, the group, and reality. This approaches, perhaps even implies, a network structure, but I don't know that it requires it.

I am aware that my statements about the above theories are gross reductions that distort the ideas of some brilliant thinkers, and I do not want to suggest that those theories and thinkers do not have tremendous value in helping us understand knowledge and how people learn. I am least fond of behaviorism, but that line of thought has generated true insight into humanity and education. They have all contributed, but I do want to say that I think we can see and understand things differently by starting from the view that knowledge is a function of complex networks, as Connectivism does. And I think that particular starting point is part of the DNA of Connectivism, but not core to the other theories, not even social constructivism. I think one can be a social constructivist without a commitment to knowledge as a function of networks. I know that one can be a behaviorist or a cognitivist without any consideration of networks. I don't think one can be a Connectivist without that very commitment.

So what do we gain by saying that knowledge is a function of networks? If we climb this particular mountain, then what do we see that we didn't see from the other peaks? What can we connect to from this starting point that we could not connect to so easily from the other starting points? I want to explore that.

#CCK12 - Shifting Gears

My new classes are changing the way I think about this blog, and perhaps the biggest change is in the frequency with which I write.

I'm requiring all my Composition I and Principles of Composition students to keep a blog and to post to us four times a week. I think I should do the same, but this changes the way I write. As you will have noticed if you've followed this blog at all, I write long posts, often too long. They take me hours.

So I have to speed up if I'm to post four times a week. I will. I'll try speed writing. I'll shorten my posts. We'll see how it goes.

So I'm still exploring how the rhizome affects the classroom. One of the first things that I do in class is start connecting my students to each other. Of course, lots of teachers who have heard of neither rhizomatics or of Connectivism also use group-building techniques to get students to engage each other, but I think these sorts of connections are required for a Connectivist/rhizomatic approach to teaching.

One of the keys to Connectivism is the insistence that knowledge is in the connections. As Stephen Downes says so succinctly in his blog Half an Hour, "At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks." My first order of business, then, is to start students constructing a network of connections, or a personal learning network (PLN), with their colleagues, their peers. I start with their peers, first, because a group of 25 to 30 students makes for a larger PLN than 1 teacher does, and second, because I want to undermine their conditioned reflex that the central connection in the class is with the teacher.

Fortunately, there are countless exercises for building a community of practice, a group, a PLN, or whatever you want to call it, but something as simple as having students introduce each other to the class and tell something interesting about the person they introduce works just fine. It puts the focus on connections among the students.

I then follow up with group exercises, usually very fun stuff at first, that encourages them to talk together about themselves in relation to the course content or to their experience as college students. I want very early in the class to show them that this class values their value-add and that they indeed have knowledge and value to bring to the class. Not all class value comes from the teacher. This further emphasizes that their PLNs go far beyond the teacher and the textbook. I then structure group assignments which challenge them to do something new such as set up a blog. I'm always available as a resource, of course, but if they get stuck, they must seek help from their group first. The group almost always knows. And if their small group doesn't, the class group does. This demonstrates that knowledge is distributed across a network, and not located just in the brain of a single teacher. That's good stuff, I think.

I'm putting words in Deleuze and Guattari's collective mouth, but I think they might say that knowledge is distributed across a rhizome and learning consists of the ability to construct and traverse the rhizome. Of course, they might not say that.

A Coin Toss and Epistemology

On the drive to work this morning, I was thinking about the World Cup Final and lamenting that it ended in a most unsatisfying penalty kick shootout—not unsatisfying because the US lost, though I did want them to win, but unsatisfying because the shootout seems so random, more like a coin toss than a competitive decision. And in my mind (I was driving alone), I said, "A shootout is like a toss of the coin, it's like a coin toss." Or that's what I meant to say. What I actually said in the safe confines of my own brain was: "A shootout is like a toss of the coin, it's like a toin coss."

Of course, I made a common speech error in which I swapped the initial phonemes of two words. Most everyone has done something like this at some time, and some of us do it more often than others, but usually we simply chuckle or blush, correct ourselves, and move on with the conversation. However, I was conversing with myself this morning, and when I noticed what I'd done in my mind, I was reminded of the conversation I've been having about epistemology these past few weeks with Dave Cormier, David Wiley, Stephen Downes, and others. The conversation started when Wiley posted some observations about the value of MOOCs, and then George Siemens, Cormier, Downes, and others responded to Wiley's observations. The conversation was for me a wonderful chance to clarify my own thinking about knowledge and learning, and some of the ideas from that conversation help me clarify my phonetic shuffle this morning.

Why did I say toin coss rather than coin toss? Where did the non-words toin coss come from? I have not learned these near-words, so it makes no sense to say that they were stored in my brain in either short-term or long-term memory waiting for the right occasion to present themselves for use. The point is, until I used them this morning, these phonetic structures didn't exist, at least not for me. However, they are clearly related to two authentic phonetic structures—coin and toss—that did exist for me. I had just used those real words in the preceding sentence. But then I wonder if the real-words coin and toss also existed prior to my using them this morning, and I think that this may be an important question.

I could say—and perhaps most people would say—that the real-words existed in my mind because I have learned them, used them before, and know them; thus, they must be stored somewhere in the brain's memory that my mind can access when it needs that word. The image of a filing cabinet or a computer hard drive seems like a good image for this way of thinking about the brain, but this fails to explain the near-words. They clearly weren't stored in my neural filing cabinet. I could explain the near-words by saying, "Well, my brain just misread the words the second go-round, as brains are wont to do, and produced the near-words." But I think there is a more satisfying explanation that relies much more on the notion of complex, dynamic networks.

Neither the real-words nor the near-words existed in my brain in some storage system before I used them this morning. Rather, my mind created all of them on-the-fly as it helped me find the meaning I was searching for. In the very instance that I sought to express an idea about the value of penalty kick shootouts, a network of neurons and clusters of neurons in different regions of my brain began firing, assembling almost instantaneously phonemes, words, word clusters, sentences, and clusters of sentences. The brain uses both inherited and learned sets of rules to structure this network of neurons and the mind uses mostly learned set of rules to structure the physical network into phonemes and words and sentences and they do it so quickly and, usually, so reliably that I don't notice it. I'm too busy thinking my thoughts to notice how those thoughts emerge—at least, until I make a mistake. Then I notice.

So what have I learned from my mistakes this morning? First, knowledge is not some static thing stored in the brain. Even something that we might commonly think of as irreducible and as stable as a word is assembled, on-the-fly, as a network structure. It's likely also that the brain does not store or preserve even that network structure representing any given word. Rather, each word dynamically emerges each time I use it from and within a network of sounds and other sounds and words and sentences using a different neuronal substrate, depending on the total state of my mind and body and social situation, so that how I say the word coin this time is slightly, perhaps greatly, different from the way I said it last time or the way I may say it in the future. The coin I type here just now is different from the coin I thought this morning in the car.

Of course, the two instances of coin are also the same. Or perhaps it's better to say that they are receptive to definition from the center out so that they possess a core that keeps them recognizable from instance to instance of use. This core is the definition that we might find in the dictionary, and it is absolutely necessary for the word coin to be useful to us humans, but the definition is also just about the least we can say about the word coin. A definition artificially isolates an entity from its environment. It reduces a coin to one thing totally separate and distinct from all other things. This is a useful fiction, and we can learn things about coin this way that we might not see any other way, but the real value of coin usually arises when we embed coin in a conversation, an ecosystem, and the meaning begins to resonate across, through, and within other network structures.

I also see that I have separated brain and mind. That wasn't my intention when I started this post; however, in trying to say one thing, I have inadvertently said another thing. That often happens to me, and it is what editing is for: to correct your mis-statements or un-intended statements. However, I'm going to let this one stand, mainly because I don't know how to correct it. I know that lots of people want to make mind and brain synonymous, to reduce mind to a physical function of neuronal structures and processes. I'm not ready to say that just yet. I do believe that mind absolutely depends upon brain, but I'm not at all certain that it doesn't also depend on the body, on society, on speech, writing, and television, or on the spirit as well. That's another post.

The Extension of Neural Complexity

In the last chapter of his book Networks of the Brain, Olaf Sporns extends his neural processing and, thus, cognition beyond the brain and to the body and the body's environment. This is the feature of neurophysiology that finally destroys all my old ideas about cognition, thought, and knowledge, for no longer can I think of thoughts as belonging only to the brain. Thoughts and emotions – all forms of cognition – flash through the brain, through the body, into the environment, and then back through the body and into the brain. I have only to think of some of the lively and spirited conversations that I have had over the years to see how my thoughts at any given time were not my brain's alone, not even mine alone, but the reiterative, feedback process of patterns flashing through the conversational space from my brain to my colleague's brain and back to me and back to them, over and over. Sporns, of course, says it more scientifically precise:

By acting on the environment, the brain generates perturbations that lead to new inputs and transitions between network states. Environmental interactions thus further expand the available repertoire of functional brain networks. … The body forms a dynamic interface between brain and environment, enabling neural activity to generate actions that in turn lead to new sensory inputs. As a result of this interaction, patterns of functional connectivity in the brain are shaped not only by internal dynamics and processing but also by sensorimotor activity that occurs as a result of brain-body-environment interactions [which] can be conceptualized as an extension of functional connectivity beyond the boundaries of the physical nervous system. (306)

Sporns follows the argument of Andy Clark to say that

the minds of highly evolved cognitive agents extend into their environments and include tools, symbols, and other artifacts that serve as external substrates for representing, structuring, and performing mental operations. If this view of cognition as extending into body and world is correct, then cognition is not "brain bound" but depends on a web of interactions involving both neural and nonneural elements. The networks of the brain fundamentally build on this extended web that binds together perception and action and that grounds internal neural states in the external physical world. (309)

Those who are familiar with Stephen Downes' thoughts on this issue (for example, here) will quickly recognize his ideas about the extension of knowledge through a social network, so that anyone person's – say, Susan's – knowledge of the French capital Paris is a network of flashes across Susan's brain, body, and interaction within the general, historical discussion about Paris as well as with the actual city of Paris. For Susan, then, cognition of Paris is the interplay of patterns in her head, in her body, in her conversations with others (mediated by voice, text, image, networks, and other media) and with Paris itself. Indeed, the more sophisticated Susan's Paris network becomes, the richer is her repertoire of ways to think Paris. At any one time, Susan will likely never use the entire network of meaning available to her, but because she has such an extensive, rich network, then she can think significantly about Paris in almost any situation for any reason.

I have a couple of quick observations to make about this view of knowledge as a kind of cognition. First, we can only have personal knowledge. By that I mean that Susan must always view Paris from the center of her meaning network. With lots of training and hard mental work, she can perhaps learn to look at Paris from other points of view than her own, but she can never not think of Paris from her own point of view (I think that's the correct combination of negatives. Count'em). Even if she changes her mind about Paris, she is simply knowing Paris from a different center, but still her own.

Second, knowledge can never be merely personal. Yes, this contradicts my first observation, but there it is. Susan's knowledge of Paris always extends throughout her ecosystem to include shared language, shared social groups, shared experiences, and so forth. Susan must form her knowledge from the center, but she must also form it in dialog with others who are likewise working from their own centers. Any attempt by Susan to look at Paris from another's center is a sometimes useful exercise in fiction. It's a God's view that Susan can sustain for only a short time. Any attempt by Susan to look at Paris only from her own center is a fatal entrapment in fiction. Knowledge depends on what Morin terms the dialogic principle: the constant interaction of any entity from its own center with its environment and the other entities in that environment interacting from their own centers. Knowledge is that zone of tension between loss of self in its own center and loss of self in the centers of others. Susan interacts with her world – sometimes skillfully, sometimes not so skillfully – and that's what makes Susan who she is. Education is the attempt to help Susan interact more skillfully.

CCK11: The Orchestra of Mind

In Chapter 9 of Sporns' book Networks and the Brain, I think we reach the heart of the issue for the discussion about Connectivism. In this chapter, Sporns is tackling the issue of cognition, or neural activity in all its various forms: learning, thinking, feeling, daydreaming, dreaming, etc., and he makes the bald, bold statement that "cognition is a network phenomenon" (181). This is the basis of Connectivism. It is certainly consistent with Stephen Downes 2008 statemtent in his Innovate article Connectivism & Connective Knowledge that "the term connectivism describes a form of knowledge and a pedagogy based on the idea that knowledge is distributed across a network of connections and that learning consists of the ability to construct and traverse those networks." Sporns lays a strong, well researched, authoritative foundation for the discussion of Connectivism, and I think it's helpful to consider three traits of this network concept of cognition as Sporns lists them at the end of Chapter 9:

1. "Cognition has an anatomical substrate" (205).
2. "Integration involves dynamic coordination (synchrony, coherence, linear and nonlinear coupling) as well as convergence" (205).
3. "Stimuli and cognitive tasks act as perturbations of existing network dynamics" (206).

Anatomical Substrate

I find it easy for my own New Age imagination to posit some cosmic Mind emerging from the idea of cognition as network, but Sporns assiduously avoids any hint of the New Age, keeping his conversation firmly grounded in the physical anatomy of the brain and its observable and verifiable behaviors. As he says, "All cognitive processes occur within anatomical networks, and the topology of these networks imposes powerful constraints on cognitive architectures" (205).

These neural networks have "small-world attributes" that are similar to other networks that are perhaps more familiar to us: social networks, the Internet, Wikipedia, or gene networks (Small-world network). Small-world networks are characterized by clustering, which groups nodes about a more well-connected node, thus facilitating quick connectivity to most any other node in the large-scale network. This is similar to the way Google works on the Net: it is a well-connected node that reduces the hops between us as individual nodes and most any other node on the Net. It may be the way an orchestra works with clusters of violins, bassoons, and drums, with a lead violinist about whom the other violins cluster and who connects those violins to the rest of the orchestra.

This small-world architecture means that cognitive processes are both segregated and integrated. An act of knowing relies on segregated clusters of neurons firing in different regions of the brain (different instruments sounding in different regions of the orchestra), and these segregated firings are then integrated (apparently within milliseconds) into a coherent thought, much like all the sounds of the orchestra. Which brings us to Sporns' second trait of cognition as network phenomenon.

Dynamic Coordination and Convergence

The brain apparently has a couple of mechanisms for integrating segregated patterns of neuronal firings into a coherent whole pattern. First, the brain can synchronize neuronal firings, or perhaps the better way to say this is that the neurons can synchronize themselves, much as a jazz band can find its way back to a  chord progression, time signature, or tune to synchronize the various flights of solo fantasy. Then, various firings can converge in a particular firing which takes the inputs and feedforwards them as a single input.

I do not understand neurophysiology well enough yet (perhaps never) to understand how synchrony and convergence work in the brain, but I understand the import: the brain is an incredibly rich orchestra of instruments which can sound or not, in unison or not, according to an internal rhythm, pitch, timbre, tone, and volume, and the brain's clusters of instruments—say, the woodwinds—can converge to create a single tone amongst the tones from the other regions of the orchestra. Every single instrument is vital to the orchestra, but no single instrument makes the orchestra. Every instrument must maintain its own integrity (the trumpet must not try to become a cello) just as surely as it must find its place in the orchestral network.

Stimuli and Cognitive Tasks as Perturbations

I think Sporns is using perturbation in its scientific sense as a variation or deviance in a system caused by some outside effect, and this is perhaps the most amazing trait of cognition as a network phenomenon. We in education typically think of external inputs (classroom lectures, for instance) as the most important aspect of learning, yet if Sporns is correct, then external inputs are best seen as an interruption of or as a more-or-less complimentary addition to the internal system. As I noted in a previous post, any external input must earn its place in the orchestra. An external input hardly ever totally supplants the music the orchestra of the brain is already playing, except in the case of trauma or other profound experiences. Of course, anyone who has ever tried to get the attention of twenty-five kindergarteners (or of twenty-five kindergarten teachers, for that matter) knows how difficult it is to keep them focused on your external input, whatever it is. This, it seems, is the natural state of things. Education is not the systematic, mechanical input of data into the blank data banks of students' minds; rather, education is an attempt to join and to modulate the tunes already playing in our students' minds. Surely these two processes are radically different and require radically different pedagogies.

CCK11: Knowing and Points of View

In a previous post, I tried mapping my knowledge of Connectivism. I created a couple of static images that showed how I related to various other entities in the network of concepts, people, and experiences that make up my knowledge of Connectivism, but even as I posted these images, I complained that they were not quite dynamic enough.

My sister, introduced me to a new mapping tool called SpicyNodes that seems to do a better job of capturing at least some of the dynamism that I sense in knowledge networks, so I started again mapping what I know of Connectivism—in part to learn SpicyNodes and in part to learn Connectivism. This is my first attempt, but I share it with you because I think it works well enough.



Note that unlike my earlier static images, this SpicyNode allows for a shift in perspective as one traverses the network. This is important.

This SpicyNode, for instance, begins with the Connectivism node in the middle. Keep in mind that this was a rhetorical decision on my part. There is nothing inherent in the Connectivism node that makes it the starting node of this network, or even the key or central node. I just happened to start there. I could have started with one of the other nodes: me, Stephen Downes, George Siemens, but I didn't. Rather, I made a rhetorical, political, logical choice to start with the Connectivism node for this particular SpicyNodes text. I should not confuse my choice of order among the nodes with the natural order (if there is one) of the Universe. Even this small collection of nodes is a rhizomatic structure in the sense that Deleuze and Guattari suggest: it has no center, no president, no controlling concept, except the one that I (or you) give it. My choice is mine, and in this particular case, was likely influenced by the fact that I'm enrolled in the CCK11 MOOC: Connectivism and Connective Knowledge.

So I started with the Connectivism node, but in SpicyNodes, I can move to another node, and the network magically rearranges itself about the new center. This captures visually a delicious interaction between knowledge and point of view. Our knowing at any given time depends on our point of view at that time.

Click on Stephen Downes in the SpicyNode above, and see how the whole pattern of knowledge about Connectivism rearranges itself. Click on George. Click on the subnodes. The pattern shifts. There is no knowledge, then, of Connectivism—there is only a knowing of Conenctivism from a particular point of view.

This would seem to break us apart into isolated silos of knowing, but while isolation does occur (Us: the Wall should come down, and Them: the Wall should stay up), it is neither inevitable nor permanent. In his book On Complexity (2008), Edgar Morin says that we must engage other points of view through dialog, not with the aim of reconciling our points of view through some Hegelian dialectic, but with the aim of understanding, accommodating, and perhaps sharing our points of view through a Morinian dialogic. We must accept that knowledge cannot calcify into absolutes of inviolable patterns, tiny dialectics falling like mollusk shells to a sea floor; rather, knowing must remain a dynamic dialog with others, always conducted from the center of our own point of view but with conversations like cellular filaments arcing among all the different points of view to permit a shared conversation that mutually informs all points of view.

For me, at least, this captures the idea behind MOOC CCK11: a dynamic dialog, mostly in writing, that permits a shared conversation that informs all points of view without trying to make them all the same (a useless task anyway).

#CCK11: Mapping the Complexity of Knowledge

I spent some of the afternoon trying to create some images that captured my sense of how knowledge and, thus, learning are complex activities. I'd like to share them, though I'm already dissatisfied with them. Still …

I started trying to map my knowledge about Connectivism in Figure 1. Those of you in CCK11 will immediately recognize a heavy debt to Stephen Downes' illustration about the meaning of Paris.

Figure 1: My Concept of Connectivism

My understanding of Connectivism is represented by the six-pointed star in the middle of the image and is surrounded by people and resources that have contributed in some way to my understanding. My understanding is not one thing, even though the six-pointed star seems to suggest that it is. Rather, it is the dynamic pattern created by the retro-interactions of various people, some of whom know about Connectivism and some who don't, the CCK11 MOOC, readings, some of which are about Connectivism and some which are not, conversations, and my own critical analysis. No one of these things is sufficient to explain my concept of Connectivism; however, all of them are necessary.

It is easy for me to see in this image how just my understanding alone at this level is a complex activity: understanding is the emergence of an idea from the interplay of various patterns of meaning to create a new pattern which takes on intelligibility and a stable core even as it continues to develop and grow in meaning from the center out and even shifts its center from time to time as drastic new patterns occur. In other words, as I keep listening and talking, reading and writing, drawing and thinking, the six-sided star of my understanding of Connectivism defines itself from the core outward, gains its own identity and presence, and begins to interact with the other patterned elements in its field, affecting and being affected, or to use the term of Morin: retro-interactions.

Figure 2: Our Understandings of Connectivism

Complex, yes, but really only just the beginning. If I add the concepts of others—for instance, those of you in CCK11, represented by U1 and U2—then you can see how each of your understandings of Connectivism (represented by the four- and five-pointed stars) starts to interact with my own understanding, and the image becomes even more complex.

What immediately impresses me is that none of us can have exactly the same knowledge of Connectivism. We all come at the concept from different angles and with different concepts, different neural pathways, different understandings of teaching and learning, different emotional fields, different connections to others and to other resources. This seems so obvious as almost to be not worth saying, yet our educational system is predicated on all students learning the same things, at the same time, through the same lessons, and monitored by the same tests. This assumption of standardization is simply wrong. Consider U2's understanding of Connectivism in Figure 3.

Figure 3: U2's Understanding of Connectivism 

It looks nothing like my own understanding. Indeed, there is only an overlap where U2 and I share somewhat similar patterns and some common resources, but both U2 and I have lots of patterns, people, and resources that contribute to our understandings that don't directly contribute to each other. U2 and I cannot possibly have the same understanding.

How can we communicate, then? Well, as near as I can see, communication lies on the borders between the miraculous and the impossible, and the best that U2 and I can manage is a functionally similar understanding. We cannot share an exact understanding. There is no chunk of knowledge that we can both swallow mentally and then say, "Yup, you've got it! Exactly!" The best we can do is to continue in dialogue (in all its various manifestations) until we both create functionally similar patterns of knowledge that allow us to say, "Yeah, that's pretty much what I mean."

Then as if this wasn't complex enough, I'm reminded what Sporns says about the various layers of networks: "Networks span multiple spatial scales, from the microscale of individual cells and synapses to the macroscale of cognitive systems and embodied organisms. … In multiscale systems, levels do not operate in isolation—instead, patterns at each level critically depend on processes unfolding on both lower and higher levels" (2). Thus, within my own mind, a similar complex network of patterns is churning and emerging, and this level affects the churning and emergence of knowledge at the wider level of the MOOC, and in turn, the MOOC level is affected by the wider discussions of education, chaos, complexity, and so forth. These wider discussion are themselves part of a larger ecosystem of discussion about society, politics, and economics, which are themselves elements within language and thought throughout the Ages. And on, and on. Worlds within worlds, patterns within patterns, all self-similar at each scale. All dynamic within their own scales and adding to the dynamism of all the enclosed and enclosing scales.

Finally, if I really wanted to capture a sense of this complexity, then I would have made a movie that captured all these patterns at all the various levels growing, fading, clarifying, and fragmenting as they interacted with elements in their own scale and with the other scales. I don't know if I have the technical talent to create that movie, but I definitely don't have the time just now. Maybe later. It'll be impressive, I think.

Decalcomania and CCK11

In his blog connectiv: On Connectivism and Learning, Jaap distinguishes between training and learning when we train ourselves to play a piece of music. I think he is capturing the distinction I am trying to explore between tracing and mapping, competence and performance, and working and playing. Jaap's training, then, is tracing and working toward competence, and learning is mapping and playing toward performance. Music provides a wonderful metaphor: to play well enough to bring joy and satisfaction (and perhaps a paycheck) to both herself and her audience, a musician must have competence with music and instrument (which requires ten thousand hours of work), but she must also transcend mere competence into performance in order to play the music on her instrument and to expand and express as an artist. Training/tracing and learning/mapping are not opposing activities, but different ends on a sliding scale of activities, and both are connectivist in nature.

I understand both training and learning as Connectivist through Deleuze and Guattari's concept of decalcomania, one of the six characteristics of rhizomatic structures that they explore in their book A Thousand Plateaus (1988). Decalcomania is the artistic process of transferring an image or pattern from one structure to another, usually by pressing the two structures together. According to ARTTalk, "technical explanations of decalcomania describe the method as geometric shapes--irregular, broken or fractured (rather than smooth and even). The two images created by pressing one area of liquid with a top sheet of paper display a form of 'self-similarity,' appearing similar in scale and magnitude - very nearly exact duplicates. In early production, this meant that the creation of two images was made with each attempt. Infinitely fine detail is immediately apparent yet, when magnified, yields startling accents." The capitalismandschizophrenia.org website defines Deleuze-Guattarian decalcomania as a method of "forming through continuous negotiation with its context, constantly adapting by experimentation, thus performing a non-symmetrical active resistance against rigid organization and restriction."

A class about fractals at Yale University notes that decalcomania can form dendritic fractals, as in the picture below:

To my mind, decalcomania is a process for transferring a pattern from one thing to another, and it describes quite accurately how we create meaning in our minds. In decalcomania, a surface with a potent image or medium is pressed against another surface. After the two surfaces are separated, self-similar images reside on both surfaces. The images can diverge more and more as the two surfaces vary in material, texture, porosity, density, color, and so forth. The images can diverge again given the viscosity and consistency of the intermediary medium being pressed between the two structures, and the images can diverge even more if the pressing is inexact or uneven and smears. Decalcomania, I think, provides a nice metaphor for understanding learning and training: the process of impressing patterns between student and class, person and world, guitarist and guitar, artist and canvas.

But first, let me correct a part of my definition. In decalcomania, pattern is NOT transferred from one thing to another. Transfer is an habitual manner of speaking that obscures a deeper insight. Only in it's most basic and popular form of decals, where an image is removed from a special paper and applied whole and unaltered to a new surface, does decalcomania reduce to mere pattern transfer. Unfortunately, this is the dominant metaphor for traditional learning and all training: a knowledge pattern is transferred whole and unaltered from a source into a new brain which then has that new knowledge pattern. This is fundamentally wrong and leads to all sorts of counter-productive pedagogical strategies and theories.

Rather, decalcomania awakens patterns in both structures. When an artist presses some medium—paint, for instance—between two surfaces—say, cloth and paper—then the act of pressing and releasing the paint creates a pattern on both the cloth and the paper. The two patterns very well may be self-similar, but they are highly unlikely to be exact duplicates. Even in industrial processes which impress images on some surface (on a Coke bottle, for instance), "infinitely fine detail is immediately apparent yet, when magnified, yields startling accents," or variations.

Decalcomania, then, helps me explain my interaction in MOOC CCK11. I have pressed some media between myself and MOOC CCK11—different media: Elluminate sessions, discussions, back channel chats, blog posts, essays, Facebook comments, Youtube videos, etc.—and each pressing has awakened in my mind new patterns or reinforced or changed old patterns. Each pressing has also awakened different patterns in MOOC CCK11. Both I and MOOC CCK11 are different because of the impressions each has made on the other. (Of course, CCK11 is bigger than I am, so the impression I make is smaller on it than the impression it makes on me; however, think of the impressions made by Downes and Siemens to see more clearly how the act of impressing works both ways, changing both the individual and the group.)

This process can be explored more. For instance, I am certain that my learning is slightly different, perhaps radically different, from the learning of others in MOOC CCK11, even when we consider the same media. In strictly physical terms, no two brains are structured alike; therefore, a pressing between my brain and MOOC CCK11 through the medium of a given Elluminate session will create a necessarily different pattern of knowledge amongst my neurons than amongst, say, Stephen Downes' neurons. The surfaces of his brain and of my brain are perhaps similar but still different, even in physical detail and certainly in knowledge detail. I may not even map what I learn in the session in the same area of the brain as he does. I certainly won't map it with the same arrangement of neurons. It takes multiple pressings through different media for the two of us even to begin to approximate consistent knowledge patterns in both our brains and in our interactions. (It's the whole process of getting to know each other.)

This process of decalcomania seems to describe many of the classes I've taken and taught. It also explains to me why the industrial method of education as described by Sir Ken Robinson has become so ineffective. If you haven't seen him speak on this issue, then watch Sir Ken explain why we need a radical shift from the industrial paradigm of education:

Performance vs Competence in CCK11

Mapping and tracing are both efforts by people to orient themselves within a given structure, say a class or a conversation. Whereas tracing attempts to assign an order to the structure, mapping seeks to uncover the order in the structure. In terms of MOOC CCK11, tracing attempts to impose an order on the class (roles, meeting times, duration, interactions, etc) and on the content (beginning, middle, end, etc), and when a tracing does not find the expected points, it becomes disoriented. Mapping, on the other hand, does not impose an order, but remains open to the possibility to any order or to no order at all (though the human mind is quite adept at imposing or creating order even in the absence of any apparent order). Tracing is an attempt to wrangle reality into sense, while mapping is an attempt to uncover the sense in reality.

This last distinction points to another reason why I am attracted to the conversation about Connectivism. Connectivism is still in the mapping phase of theory construction. It seems to me that most theories begin with a mapping phase that seeks to uncover the sense in reality. Moreover, this attempt to map some slice of reality is usually in reaction against some other theory that has calcified into dogma and seeks only to trace reality, or to wrangle reality into the sense of the theory. Mapping is often prompted when a Galileo at last notes enough points in reality that don't fit in the old theory without excessive wrangling and so begins to look at reality in a fresh way. To my mind, Connectivism is looking at reality in a fresh way. If eventually Connectivism becomes accepted theory, then it will likely go the way of most theories and itself become dogma, a tracing rather than a mapping (not a static map, but a dynamic tracing—a verb rather than a noun), a routine rather than a ritual. But that hasn't happened yet, so until it does, I will enjoy the ride.

It helps, then, to sharpen our distinction between mapping and tracing. Deleuze and Guattari note that "the map has to do with performance, whereas the tracing always involves an alleged 'competence'" (12,13). I find this so insightful and quite germane to education with its practice of assessment and grading. It reminds me of a story I once read about an education professor who visited a kindergarten class and asked the five-year-olds which of them could sing, dance, and draw. At each question, all the children enthusiastically raised their hands, certain that they could sing, dance, and draw. The professor then returned to his college classroom and asked the same questions. Of his adult students, only a few could sing, a different few could dance, and yet another two or three could draw. He concluded that the main function of modern education was to teach people what they couldn't do.

I appreciate the professor's point, but I think that Deleuze and Guattari can give us a more precise way of explaining what happens to students between kindergarten and graduate school. If we assume a sliding scale between performance and competence, then kindergarteners are focused almost totally on the performance end of the scale in total disregard of how well they sing, dance, or draw, while grad students are focused almost totally on the competence end paralyzed by assessments of how well they sing, dance, or draw. Kindergarteners are concerned only with exploring and mapping an activity through their performance, while grad students are concerned only with competently tracing a sanctioned activity.

In this MOOC, Downes and Siemens are refusing to grade the performances of most students, and this disregard for the traditional markers of competency confuse some of us. How do we know if we are doing it right, dancing right, learning what we are supposed to be learning? Most of us have lost the questions on the performance end of the scale that drive open-ended, free form inquiry, mapping, and play (though I suspect the members of this MOOC are perhaps more open to performance than most students; otherwise, they wouldn't be in this MOOC). I think that a big part of the lesson in MOOC CCK11 is to reawaken those questions of performance and play within the MOOC's members.

One might accuse me of totally favoring performance over competency, but I do not. However, I do have a profound distrust of the merely competent, which in my experience, informs too much of traditional education and all of the back-to-basics movement. I insist that education should be large enough for both performance and competence, and that the best education happens in the interplay between the two. For example, mastery of the guitar is a fine educational process that necessitates a nuanced balance between performance (play) and competency (work). A guitarist must work the guitar to attain competency with it, and this can require ten thousand hours of practice, hitting the same notes over and over, going through the same fingering patterns, reading the same musical scores. But the guitarist must also play the guitar to attain more than competency with it, and this builds upon the ten thousand hours and sustains the guitarist's drive to put in the ten thousand hours. Performance first informs competence, and then it transcends competence, but mere competence is never enough to make a guitarist. This is perhaps easy to see in a jazz guitarist who can improvise whoever he wants, but even a classical guitarist who is tightly constrained by working a musical score (competency) must also play that musical score (performance).

Associating performance with play and competence with work makes sense for most educators, I think, and it makes sense to me that traditional education has focused too much on the work of competency and not enough on the play of performance. Education has sadly overlooked the ludic element in our pedagogical mix, and MOOC CCK11 is a nice corrective to that pattern.