Why Rhizomatic Learning? #etmooc

Okay, so I enjoyed the conversation about rhizomatic education over at Christina Hendricks' blog, You're the Teacher. In the conversation, I'm definitely championing rhizomatic, connectivist education, but why? I've been writing about this for a couple of years now, but can I state my point of view succinctly and reasonably clearly? Well, I can try.

Learning is a network phenomenon.

That's rather succinct, and owes deep apologies to neuroscientist Olaf Sporns, but I can say it with a bit more texture: learning is a function of our complex interactions across multi-scale physical, cognitive, technological, and social networks. For me, this is the DNA of a connectivist and rhizomatic view of learning, and everything else I say about learning will follow from this core idea. At least, I hope so.

But can I defend my claim that learning is a network phenomenon? I think so, but in some ways, starting points always carry with them assumptions that one either accepts or doesn't, and they carry assumptions that the believer is quite often unaware of. I think my use of networks falls into this category. However, I can point to some reasons why I use the concept.

Networks provide me a most useful model of how the Universe/Reality/Everything works, including learning. Of course, as soon as I say that, I am reminded of George E. P. Box's famous dictum that "essentially, all models are wrong, but some are useful" (Empirical Model-Building and Response Surfaces, 1987). I am convinced that, despite how right network thinking feels to me, eventually people will come to see the faults with the network metaphor just as we are coming to see the faults with the mechanistic clockwork metaphor that we inherited from Galileo, Newton, and Descartes. As Edgar Morin has pointed out in his book On Complexity (2008), the mechanistic, clockwork model of reality and the science and technology built upon it has been spectacularly successful, but over the past century, cracks have begun to appear as we have come to see more of Reality, especially at the macro and micro levels. As we peer into our scopes, bits of reality emerge that no longer fit the clockwork model. Reality is stubborn, so we change our model. But slowly, sometimes too slowly.

The model that appears to be replacing the mechanistic clockwork model is networking. Of course, not everyone uses that term. Edgar Morin speaks of systems, especially complex systems. In his book Interaction Ritual Chains (2005), Randall Collins defines the core sociological unit not an individual but the situation, a dynamic nexus of intersecting vectors which to my mind requires a network structure. James Lovelock calls it Gaia, the movies call it The Matrix. All of these sources have valid reasons for using the term that they do, but to my mind, networking (and here I'm using the verbal form intentionally to capture the complex dynamics in my concept) is the most convenient and natural-feeling term. I spent many years of my professional life building campus networks and connecting students, faculty, and staff to the Internet, so it just works for me; however, I also frequently use the term rhizomatics or rhizomics to play off Deleuze and Guattari's concept of the rhizome (A Thousand Plateaus, 1988), a more free-form, complex, dynamic, and inclusive form of networking that reveals some properties that I find particularly useful and fun.

So the networking model in all its various iterations and apellations appears to be the emerging model of how things work. I like Olaf Sporns' comments about this in his book Networks of the Brain (2011), so I'll end this post with a long quote that has a decidedly scientific bias that I think will inform our thinking in the humanities:

Over the last decade, the study of complex networks has dramatically expanded across diverse scientific fields, ranging from the social sciences to physics and biology. This expansion reflects modern trends and currents that have changed the way scientific questions are formulated and research is carried out. 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)

Why Connectivism?

I've not blogged in over a month, and I have a serious case of disconnection. I'm irritable about it. Really. I'm not so pleasant just now, and I think a large part of it has to do with my loss of connection with my writing, my thoughts, my conversation. Of course, I have good reasons for being disconnected—mostly demands from other connections: family, vacation, a personal blog, work, an election, and more—but those reasons do not ameliorate the dissatisfaction. The only solution is to reconnect. Perhaps a better way to say it is: it's time for me to refire a dormant neuron.

And it occurs to me how differently I think about things now and how I owe much of that difference to this conversation about connectivism.This has been a most important conversation for me, and I'm uncomfortable when I don't exercise it regularly. So what is it that makes connectivism important? If I had to chose one word for you, then I would say networks, networks in both their formal sense as mathematical, scientific structures and their informal sense as rhizomatic, literary structures. I admire and respect the first way to think about networks, but I love the second. The first is a revered teacher, the second a passionate lover. Both aspects of networks have reshaped my thinking about most everything in life, but especially the way I view education and rhetoric. Networking is an archetypal meme that radically changes the way I see my world. For me, this has been big stuff.

I've been reminded from several sources just this past week about the revolution that is occurring all around us as the networking meme (virus might be a better term) spreads. The webzine Edge had a great conversation with Albert-lázló Barabási about thinking in network terms. Barabási notes first that "we always lived in a connected world, except we were not so much aware of it." We became aware of networks as technologies gave us a way of better viewing them. This is the same as our using telescopes to learn that the Earth is but a speck of dust on the outer edge of the Milky Way galaxy. We had always been a speck of dust on a speck of dust, but the telescope helped us to see that. Similarly, we have always been nodes in physical, chemical, biological, social, spiritual, intellectual, rhetorical networks, but it took computers and computer networks for us to appreciate that fact and to address it. Now, as Barabási notes, "We never perceived connectedness as being quantifiable, as being something that we can describe, that we can measure, that we have ways of quantifying the process. That has changed drastically in the last decade, at many, many different levels." New technology has given us the ability to approach rationally a phenomenon that has always been here and sensed on some (usually spiritual or artistic) level, but not quite graspable outside of poetry and prophecy. At last, science has the tools to systematically deal with networking, and it's going to change everything.

The network meme is in the DNA of connectivism. As far as I know, connectivism is the most coherent  and vibrant attempt in educational theory to deal with education as a network structure, and for me, that is connectivism's greatest value. Just as many scholars are doing in physics, chemistry, biology, sociology, mathematics, and other disciplines, connectivism places networking at the core of its methodology and thinking. Networking guides its practice and preaching. Connectivism has converted me, and like the Apostle Paul, I hope to take this new thinking to my home town: Rhetoric. I believe that networking will revolutionize rhetoric and writing instruction.

I'd better start writing. Wow. I do feel better. I hope you do, too.

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.

Writing at Different Scales, #cck12

So what happens to the field of writing if we start with the idea that writing is a function of complex networks?

One of the first concepts that I draw from the study of networks is that network structures appear at most any scale from which you consider an entity. For instance, if we think of human consciousness as a function of complex networks, we find networks whether we consider consciousness at the molecular or cellular levels, the neuronal level, the brain regions level, the level of the nervous system as it extends throughout the body, and on to the sensory level, and out to the interpersonal, social, cultural, historical levels. Physics is currently able to push in to reality all the way to strings (those wispy networks of harmonic vibrations) and push out all the way to networks of galaxies. A dedicated student could follow consciousness all the way in to strings and all the way out to galaxies, I think.

Writing is similar. Whether we look at the scale of cognition, physico-motor, language, interpersonal, social, poetic/rhetoric, genre, or more, we find network structures at work. This text, for instance — this very post that I am writing and you are reading — can be thought of as a network structure: morphemes networked into various words, words networked into sentences, sentences into paragraphs, paragraphs into sections or posts, posts into a blog, the blog into larger educational, intellectual, and social networks. I think this network structure has always been a feature of written texts, but it was not obvious. Given the requirements of print, we tended to emphasize the linear nature of text, but we can think of this linearity in the same way we might consider a strand of DNA: linear if we view it one way, but very much a network if we shift our view just a bit. We can think of DNA strands as they unfold, or blossom, into a living organism. We can think of these sentences as they unfold into a living discussion. These sentences in this post are strands of DNA expanding in an ecosystem, creating an organism that interacts with other organisms, that both draws from and adds to the ecosystem/s within which it finds itself. And of course, hypertext makes explicit this network nature of written text.

But I think even standard printed text can also be seen as a network structure. For instance, this post is one node within this blog, and it interacts with the blog in much the same way that a new tadpole interacts with its puddle. This post draws value and energy from the blog as an ecosystem, and it feeds back its own value. I can scale down, and see the same dynamic at work: this very sentence is a node within this paragraph, and it draws meaning and value from the paragraph and returns meaning and value to the paragraph. This blog is easily seen as just one node within a network of blogs all exploring higher education, or writing, or Connectivism, or things I'm not even aware of.

And meaning emerges at all those different scales, and the meaning at one scale interacts with, supports, and modifies the meanings at the other scales, and we can see different meanings whether we are giving a text a close reading or fitting it into its larger genre. Different meanings emerge at different scales. This is a very dynamic way to think about writing and written texts, and it gives us dynamic tools for thinking about writing and for teaching writing. This, I think, is worth exploring.

We also see that the rules, the patterns of organization and interaction, can shift from scale to scale. This is a new idea for me just now, and I need to do more work on it, but it seems right. I like the ring of it.

Writing as Network Enterprise

Manuel Castells' book The Rise of the Network Society continues to inform my understanding of a Connectivist rhetoric, though my reading has been incredibly slow over the past month or two. I've had way too many distractions.

Anyway, Castells' discussion of the emergence of the network enterprise has clarified my understanding of the socio-linguistic ecosystem that informs writing. Castells defines the network enterprise as that specific form of enterprise whose system of means is constituted by the intersection of segments of autonomous systems of goals (187). I understand him to mean that a networked enterprise (he is speaking almost exclusively of business organizations) organizes itself and conducts its business through various segments of autonomous networks that are available to the enterprise but not owned or controlled by the enterprise.

At first glance, this may not seem like much of an insight. Haven't organizations always used autonomous networks such as highways, waterways, airways, mail systems, and so forth to do their business? They have, but something has shifted in the past few decades. The biggest shift is, of course, the emergence of the Internet – the distribution of millions of interconnected computers. The Internet provides a new, highly capable, very flexible, and autonomous substrate that allows organizations of any kind or purpose to organize themselves on most any scale and to interconnect in most any way with markets: researchers, suppliers, producers, transporters, customers, regulators, and information.

The Internet also makes explicit to most everyone exposed to it the networked structure of human interaction. Transportation systems and postal systems were also networked structures, also mostly autonomous of any one business enterprise, but for whatever reason, those networks lacked the visual or emotional impact to knock most people from their focus on the individual, at least in Western culture. We could continue to think of Microsoft as mostly Bill Gates, WalMart as Sam Walton, and the United States as JFK or Ronald Reagan.

This viewpoint is hardly sustainable in a networked enterprise. The Internet makes the network explicit to all because it connects all to all. In the old industrial enterprises, only the top management could see and connect to the entire organization. Only they could see how the whole hierarchy fit together. Most people in the hierarchy, certainly the mass of workers, saw and connected only to a handful of others and only to very little information. Today, even workers connect to others both inside and outside the enterprise, and they are more aware of the scope and reach and intricate network nature of their organizations and their place within that network. Moreover, their place in the enterprise is becoming more fluid. No longer do we all have jobs that are discrete positions on an unchanging organizational chart with static duties. Organizations are more flexible, jobs are more fluid, and this flexible fluidity requires a greater awareness on the part of each person of not only their current position within the organization but also their trajectory through the organization.

Thus, as Castells demonstrates quite thoroughly, the convergence of organizational change with technological change has led to new kinds of enterprises, which he calls networked enterprises. These new enterprises make explicit for everyone from CEOs to janitors the network reality of business. Or government, or religion, or education. My hat is off to businesses for capitalizing on these new structures more quickly than have governments, churches, and schools.

So what does this have to do with rhetoric, writing in particular? Well, writing has always been a network phenomenon, but as with business enterprises, that network has been somewhat obscured by the hierarchical structures within which writing took place and by our own intellectual, social, and emotional biases in favor of the individual. On the most sophisticated level, writing was a hierarchical, industrial process with clearly defined jobs: writer, editor, typographer, typesetter, printer, bookseller, reader/consumer, etc. Even in classes, the job of the student writer was quite distinct from the teacher grader, and seldom were the student and teacher in a real conversation that was meaningful to either of them as a conversation rather than a graded exercise. Even writing a letter home to Mom through the postal system (a network) was obscured by the disconnect between the discrete processes of writing the letter, transporting the letter, and reading the letter. Today, people text each other, and they feel (I don't think most of them think about it) connected to the processes of composing, transporting, reading, and responding. Or a better way to say this is that people now see writing as the coherent, systematic, mostly social interaction between networked nodes that it has always been at heart. We'll explore later how to make this mostly social interaction more academic and intellectual.

By the way, I think this coherence of writing/reading as a unified social transaction is the root reason why people are so attached to texting. When writing connects people to their peeps and to their info, then they come to value writing. This is a value and an energy that schools and teachers have yet to capitalize upon. Shame on us.

Then, writing as a network phenomenon makes use of an autonomous substrate known as language. I use English. I don't own English and I don't control it. If I did, then English would quickly become useless as an environment within which millions of people (network nodes) can connect to other people and information sources (other network nodes) to do the work and play of society. This substrate has rules (grammar), as does the Internet (TCP/IP), that are fairly reliable in the sense that no single person or entity (not Apple or Google or English Teachers) can change them for everyone else but that are flexible in the sense that the group as a whole can modify them if a sufficiently compelling reason emerges. Internal use rather than any standard of external merit or appropriateness determines the rules.

Moreover, the substrate is almost infinitely malleable, so that a particular subgroup (say, lawyers or redheaded, left-handed skateboarders) can create their own localized language to facilitate organizing themselves and conducting their affairs. This is quite similar to how organizations will create their own virtual networks over the substrate of the Internet. Here is the reason for network neutrality. If the Internet does not remain autonomous in the sense described here, then it will cease to be a sufficient substrate for all of us. We should expect various entities – governments, businesses, churches, schools – to try to dominate the Internet (or English) and to dictate what is proper to it and how it can be used, but if any group ever captures control of either the Internet or English, then both will be finished as adequate substrates for cultural evolution and progress. Fortunately, most networks have the ability to identify any nodes that attempt to calcify the network into a rigid, authoritarian, hierarchical structure, and the network can isolate those nodes and flow around them.

Writing in the Network

I'm reading a new book: Manuel Castells' The Rise of the Network Society, second edition (West Sussex, UK: Wiley-Blackwell, 2010). Originally published in 1996, this book makes a strong case for the monumental shift caused by the emergence of electronic networks. Though I'm just beginning the book, clearly Castells provides exhaustive, well-researched evidence that networks have changed every sphere of life: political, social, economic, religious, educational, criminal, and mental. I'm thinking, then, that he may provide a useful context for exploring how composition and rhetoric have changed.

In the Prologue, Castells introduces the general problem for anyone wanting to write in a networked world. In speaking of how global networks switch on and off individuals and groups according to their perceived relevance to the global network, Castells notes that:

There follows a fundamental split between abstract, universal instrumentalism, and historically rooted, particularistic identities. Our societies are increasingly structured around a bipolar opposition between the Net and the self. [Thus], in this condition of structural schizophrenia between function and meaning, patterns of social communication become increasingly under stress. … The information society, in its global manifestation, is also the world of Shinrikyo, of the American militia, of Islamic/Christian theocratic ambitions, and of Hutu/Tutsi reciprocal genocide. … Postmodern culture, and theory, indulge in celebrating the end of history, and, to some extent, the end of reason, giving up on our capacity to understand and make sense, even of nonsense. (3, 4)

As I understand him, then, Castells is saying that the complexity and irresistible momentum of the global networks is overwhelming individuals and groups who seek refuge in chauvinistic creeds and identities to provide the meaning and values that they need. As one might suspect from the sheer length of Castell's book and the amount of energy that has gone into writing it, Manuel Castells does not accept the end of history and reason. Rather, he affirms his faith that the world has pattern and that human reason can make sense of that pattern. His book is one attempt to discern and describe that pattern.

This is, perhaps, the heart of modern rhetoric: the use of reason (the regular and sharable heuristics of thought and communication) to explore and explain the world and to inform human activity in that world. But I wonder if Castell accepts an essentialist view of reason that posits one standard of reason applicable to all people, at all times, in all situations, or if he accepts a complex view of reason that posits a relative standard of reason negotiated by a group of people, at a given time, in a given situation. I suppose I will find out.

Whichever way he goes, he poses an interesting challenge for rhetoric: how do we communicate in a world that is polarized, on one hand, by global processes that can subsume and crush individuals and groups with an economic logic and, on the other hand, by the fragmentation of individuals and groups into discrete, antagonistic identities that not only resist communication with other groups, but deny that communication is possible? This is a tough challenge, if indeed, it is real.


P.S.— It happened that just an hour after writing this post, I came across a NYTimes article Does Your Language Shape How You Think? by Guy Deutscher. Mr. Deutscher argues that we have recovered enough from the excesses of Benjamin Whorf to look more clearly at the influence of language on the way we think, including the way we reason.

For many years, our mother tongue was claimed to be a “prison house” that constrained our capacity to reason. Once it turned out that there was no evidence for such claims, this was taken as proof that people of all cultures think in fundamentally the same way. But surely it is a mistake to overestimate the importance of abstract reasoning in our lives. After all, how many daily decisions do we make on the basis of deductive logic compared with those guided by gut feeling, intuition, emotions, impulse or practical skills? The habits of mind that our culture has instilled in us from infancy shape our orientation to the world and our emotional responses to the objects we encounter, and their consequences probably go far beyond what has been experimentally demonstrated so far; they may also have a marked impact on our beliefs, values and ideologies. We may not know as yet how to measure these consequences directly or how to assess their contribution to cultural or political misunderstandings. But as a first step toward understanding one another, we can do better than pretending we all think the same.

I accept that we do not all think the same. I think common experience tells us this is so, and I think research is beginning to confirm that it is so. The challenge of academic rhetoric for me, then, is to reason about the world and our activities in the world, while at the same time being conscious of the thought structures we are employing and being explicit about them. Finally, we must employ strategies of engagement with our audiences that allow for those who, through willfulness or ignorance, disregard our own impeccable and exemplary reason. I must think more about those strategies.

CCK11: Why Networks?

In my last two posts, I talked about Olaf Sporns' book Networks of the Brain, and I want to continue working with that book. I'm finding it very rich and resonant.

In his Introduction (2), Sporns asks, "Why should we take advantage of modern network approaches to study the brain?" I want to ask why should we take advantage of modern network approaches to study knowledge and learning?

First, because knowledge and learning are network phenomena, and network approaches tell us things about learning and knowledge that we just can't get any other way. Sporns' comments are salient here. "Virtually all complex systems form networks of interacting components" (2). Learning and knowledge are complex systems receptive to network approaches which, says Sporns "can provide fundamental insights into the means by which simple elements organize into dynamic patterns, thus greatly adding to the insights that can be gained by considering the individual elements in isolation" (2). If we consider just a single brain alone, knowledge is the selection and orchestration of many individual neurons into meaningful patterns of interactions. No single neuron alone constitutes a chunk of knowledge; rather, knowledge emerges only when all the relevant nurons fire coherently. As I write each word of this sentence, patterns of relevant neurons are firing in my brain to orchestrate thoughts, motor movements, and memories into (we hope) a coherent expression of knowledge.

We must, of course, keep in mind that it greatly helps to understand "the individual elements in isolation," and I appreciate those physical scientists who dedicate their careers to studying how neurons fire. Knowledge absolutely depends upon the proper firing of individual neurons within our brains, and if we understand this electro-chemical process, then we understand real and crucial facts about knowledge and knowledge creation. But understanding single neurons alone isn't enough. It cannot explain thought, memory, consciousness, and knowledge. Not even complete knowledge of the fundamental physical element of knowledge—the neuron—will explain knowledge. To understand knowledge—to know knowledge—we must understand how individual neurons orchestrate themselves into meaningful patterns. As Sporns says of the brain:

The collective actions of individual nerve cells linked by a dense web of intricate connectivity guide behavior, shape thoughts, form and retrieve memories, and create consciousness. No single nerve cell can carry out any of these functions, but when
large numbers are linked together in networks and organized into a nervous system, behavior, thought, memory, and consciousness become possible. Understanding these integrative functions of the brain requires an understanding of brain networks and the complex and irreducible dynamic patterns they create.

Studying the neural patterns within a single brain seems complex enough, but if we accept the network approach, then we must accept that, as Sporns says, "networks span multiple spatial scales, from the microscale of individual cells and synapses to the macroscale of cognitive systems and embodied organisms. This architecture is also found in other complex systems—for example, in the multiscale arrangement of social networks, ranging from interpersonal relations and cohesive social groups, to local communities and urban settlements, all the way to national economies and global political organizations" (2). Thus, just understanding the pattern created by a single mental concept is not sufficient; rather, we must move up the scale to clusters of concepts housed within other clusters of larger networks, like ecosystems housed within planets, within solar systems, within galaxies, within galaxy clusters, within multiple universes.

To remove us from the black hole that I just landed us in and to put some bounds on this train of thought, imagine the patterns of neurons that are firing in your brain as you read each word in this current sentence (actually, studies show that you are likely reading clusters of words, but more of that in another post). You have a unique pattern of neurons for each word or word cluster, but each unique pattern of neurons yields precious little knowledge—precious little because each identifiable pattern is precious, or absolutely necessary for your knowing the sentence, but also little, or absolutely insufficient for knowledge. Rather, to understand what I'm writing, you must scale up to a larger pattern of patterns, from individual words and word clusters to sentences. And if you follow this logic, you see that to understand the sentence, you must scale up again to the paragraph. Then you must scale up again from the paragraph to the post. Then again from the post to the entire blog. Then you must scale again to the conversations about Connectivism, CCK11, complexity, rhizomatics, and to awareness that I'm writing all of this on a beautiful Sunday morning in Macon, GA, USA after a wonderful night's sleep and  two cups of coffee while my wife across the room watches the television show CBS Sunday Morning about the upcoming Oscars.

Sorry, but I tend to expand outwards. To center my thinking again, consider that to understand any knowledge pattern, we must understand the context, or ecosystem, within which that knowledge pattern exists, and we must accept that no scale level makes complete sense without understanding the scales above it and below it, or to say it better, no scale can be understood without understanding the scales it contains and the scales within which it is contained. To understand any layer of an onion, you must understand both how it functions as a layer by itself AND how it functions with the layers it encloses and the layers that enclose it. In the words of Edgar Morin, your thought—your knowledge—must be complex. Olaf Sporns says it better and more succinctly than I, so I'll end with him:

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. The brain is a case in point. We cannot fully understand brain function unless we approach the brain on multiple scales, by identifying the networks that bind cells into coherent populations, organize cell groups into functional brain regions, integrate regions into systems, and link brain and body in a complete organism. In this hierarchy, no single level is privileged over others. The notion that brain function can be fully reduced to the operation of cells or molecules is as ill conceived as the complementary view that cognition can be understood without making reference to its biological substrates. Only through multiscale network interactions can molecules and cells give rise to behavior and cognition. Knowledge about network interactions on and across multiple levels of organization is crucial for a more complete understanding of the brain as an integrated system.

Apply this, then, to students and learning: Only through multiscale network interactions can learning give rise to behavior and cognition. Knowledge about network interactions on and across multiple levels of organization is crucial for a more complete understanding of students and learning as integrated systems. Ultimately for me then, we must apply network approaches to learning and knowledge for political and moral reasons: to stop the dreadful reduction of students to test scores. Test scores simply do not capture the complexity of learning and knowledge.

The Value of Connectivism and CCK11

In one of our past Elluminate sessions in CCK11, George Siemens mentioned a book by Olaf Sporns called Networks of the Brain (2011). Something about the book piqued my interest, so I'm reading it now. The book addresses the question "What can network science tell us about the brain" (1), and I confess up front that I do not have either the scientific or mathematical backgrounds to follow all of Prof. Sporns' arguments, but as with most conversations that I engage, I'm reading it through the foggy windows of my own interests and biases, so it is still worthwhile.

I'm interested in the book because connectivity and complexity are at the heart of how Sporns is attempting to understand the brain. He says in his Introduction that science in general is informed by the perspective of complex networks:

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. … All such complex systems display characteristic diverse and organized patterns [which are] the outcome of highly structured and selective coupling between elements, achieved through an intricate web of connectivity (1).

As I have mentioned in an earlier post, Edgar Morin says that this emergence of complex network thinking is a third great paradigm in the development of science, the first being the static, mechanistic universe of Newton and the second being the declining universe of thermodynamics. I hear Sporns agreeing with Morin that the idea of complex networks is radically changing the way that scientists explore and describe (or map, to use Deleuze and Guattari's term) reality. If this is the case, then it seems to me that Connectivism, and the discussion emerging about that concept, is a response to this new and emerging way of viewing the world. Connectivism is an attempt to move beyond the reductionism of Cartesian dualism (despite all its marvelous successes) to a richer, more complex understanding.

What does this mean for education? I am not so well read in educational theory as to say reliably, but lack of knowledge does not appear to be a strong deterrent, so I'll make a few observations, hoping that others better informed will correct me. The other three major strains of educational theory—behaviorism, cognitivism, and constructivism—appear to me to focus primarily on the individual. In those theories, knowledge is something in an individual brain or mind or both. Learning is something that happens in that same individual, discrete mind, whether we think of the mind as an inscrutable black box (as in behaviorism) or a translucent computational device (as in cognitivism). Knowledge and learning, then, belong to the individual student and are observable, measurable, and describable only in terms of that individual student. This attitude is reflected in our grading economy, which insists upon an inviolable and sacred correspondence between 1 student and 1 grade. As everyone knows, group grades suck.

This reductionism is precisely what Connectivim tries to overcome, while at the same time respecting the truly impressive achievements of the reductionist theories. Reductionist theories and the schools built upon them largely favor "only knowledge of elementary system components," or the individual student; whereas Connectivism attempts to add "knowledge of the ways in which these components interact and the emergent properties of their interactions." Connectivism does not deny that knowledge and learning occur in individual students; rather, it counters the diminutive and reductionist idea that knowledge and learning occur only in individual students. Connectivism says for me that knowledge and learning are most properly understood in terms of individual students and the interactions of students with their ecosystems and the emergent properties of all that dynamic interaction. This is a radical difference in understanding, a precipitous difference. Really. A school built on Connectivism will not function or look like existing schools.

Now, I am not suggesting that Connectivism has invented complexity or networking theory, nor am I suggesting that cognitivists and constructivists are total reductionists with no understanding of complexity and networking structures. Even as unread as I am, I can think of scholars such as Wenger who have incorporated the interactions within groups into their ideas about education. I'm speaking in this post on a very general level, fully aware that most anyone who reads this could think of numerous scholars from the other camps who have already anticipated many of the insights of Connectivism. I am in no way suggesting that Connectivism is totally new. I'm not sure that a totally new idea has ever existed, and largely, I regard any complaint by curmudgeons that this idea or that theory is not new to be a red herring. Who cares? Rather, I want to ask if an idea or theory is useful.

Connectivism is useful for me. It gives me a conversational space within which to connect with and engage others who are examining and thinking—in light of complex, networked systems—about how we humans create and share knowledge.