MOOCs and Network Scale

I've just listened to a TVO lecture by Eric Mazur, a well known physicist at Harvard University, in which he talks about the stop-motion photography that his lab is able to perform. While I like the magic  of stop-motion photography as much as any, what really impressed me was his clarification of the remoteness of different space/time scales from our own. Different network scales lead to radically different views of reality—in the words of Nicolescu, they lead to different levels of reality.

First, Mazur helped me to see how intimately space and time are bound together. When we speed up or slow down time significantly, then we are automatically reducing or expanding the amount of space that we are encompassing. I know, of course, from my readings in science that since Einstein we have known that space and time are a unit and that if, for instance, you bend space then you bend time, but for whatever reason, Mazur helped me see that more clearly. When you talk about nanoseconds, then you are also talking about micro-distances. The one includes the other.

But mostly Mazur helped me understand viscerally the truly profound differences between different scales, or levels, of reality. Basically, with our natural eye we see very little of life that happens at scales much smaller/faster or larger/slower than our own. For us, anything quicker than the blink of an eye or smaller than a grain of sand simply doesn't exist. Likewise, anything slower than a lifetime or larger than the horizon doesn't exist.

Except, of course, that it does exist, and it influences us. Those influences exert themselves across the various scales, or levels, of reality, affecting us almost as if by magic. Thus, the Moon, on a scale far larger than our own, exerts influences on the molecules of our bodies, a scale far smaller than our own, and drives us crazy once a month, as any grade school teacher can tell you.

Our technology, including Mazur's own amazing lazer-aided photography, allows us to slow down time, to almost stop it, so that we can see events that have been happening all along and affecting us in mysterious ways, but that we could not see. Likewise, with our telescopes we can speed up time almost back to the Big Bang to learn what's been happening in those long processes of the Cosmos.

This makes me wonder, then, about the effects of scale within a MOOC. It seems to me that just saying MOOCs are massive does not quite get the point of all those people in a coherent group. I have a sense that shifting from a normal 20 or even 200-student class to a 2,000 or 20,000-student MOOC is something else entirely. As Nicolescu says of the different levels of reality: "two levels of Reality are different if, while passing from one to the other, there is a break in the laws and a break in the fundamental concepts" (Manifesto, 21). Education among 2,000 may be a radically different scale of education than educating 20 or 200. As Mazur shows, when we use factors of 10 down from a second, we quickly reach scales that are not obvious to the naked eye and that behave very differently than our ordinary scale. Likewise, longer/larger scales are also not obvious to the naked eye and behave very differently. It seems to me quite reasonable that MOOCs are fundamentally different than a 20-student classroom. That is not a radical statement, but I don't think that xMOOCs are aware of it. They appear to be committed to business as usual: transferring some knowledge or skill from a teacher to a student, 20-at-a-time or 20,000-at-a-time. I think they are making a fundamental mistake.

But I don't really know how. Well, I've identified yet another thing that I don't know. I don't understand well enough the different structures and interactions at the different scales of education and I don't know how those different scales influence one another across the various scales. If anyone has already addressed this issue, then please direct me to them if you can. Thanks.

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: Earning a Place in the Network

I continue to revel in Olaf Sporns' wonderful book about neural networks: Networks of the Brain. In Chapter 8: Dynamic Patterns in Spontaneous Neural Activity, Sporns examines the dominant model in brain studies that says brains are mainly structures for receiving, processing, and then responding to sensory impressions from outside the brain (eyes, ears, skin, etc.). As Sporns says, "This theoretical framework treats the brain as a system in which the essential neural process is the transformation of inputs into outputs" (149). If I understand Sporns correctly, then this view of the brain borrows heavily from computer information theory: signals from keyboard and mouse are input to the CPU, which then processes the signals and outputs a result in the form of another signal, or: I press the A key on my Macintosh PowerBook Pro's keyboard, then the internal 2.53 GHz Intel Core i5 chip processes that signal, and finally it outputs signals to the screen to display the letter A. In the view of traditional neuroscience, then, my brain is like the Intel Core i5 chip: a more or less efficient processor of sensory input into motor output.

This is a simple view of brain activity, and it is consistent with a Newtonian worldview that sees reality as a machine: a collection of parts with regular, reliable, and highly predictable interactions in which cause and effect are necessarily linked. If I press the A key on my computer keyboard, then the CPU will process that signal and it will cause A to appear on my screen. If this doesn't happen, then the machine is malfunctioning and requires repair. Or … if I teach (input) the technique for handling in-text citations according to the MLA Style Manual, then my students (CPUs) will process that input, and they will necessarily output papers that properly handle in-text citations according to the Modern Language Association's authoritative guide. If they don't, then their machines (brains) are malfunctioning and require repair (further teaching). If I'm a particularly sensitive and liberal teacher, then I might suspect that the teaching/learning process could be broken elsewhere—say, with my teaching technique—but I will not likely suspect that the entire mechanistic process itself does not adequately capture the reality of how students might learn to do in-text citations according to the MLA.

For two hundred years, both neuroscience and teaching have focused on a mechanistic model of input -> processing -> output, and this model has, indeed, taught us much about both brains and learning, but in the end, this model is too limiting. As Sporns says, "Until now, much of the interest in theoretical neuroscience has focused on stimulus-driven or task-related computation, and considerably less attention has been given to the brain as a dynamic, spontaneously active, and recurrently connected system" (149, 150). So what happens if we begin to consider students as dynamic, spontaneously active, recurrently connected systems?

Sporns explains why, despite its huge and continuing contributions to neuroscience, this mechanistic view does not adequately capture the reality of brains and, by my extension, the reality of students learning MLA techniques. Sporns provides strong research that suggests that the majority of neural activity is not in response to external input through eyes, ears, nose, tongue, and skin or output through motor and cognitive functions. As he says, "Whether considering individual neurons or entire brain regions, one finds that the vast majority of the structural connections that are made and received among network elements cannot be definitively associated with either input or output" (150). This raises at least the possibility that, similarly, most learning is not in response to either input through instruction or output through homework and papers.

Rather, the brain seems to spend much of its time self-organizing, partly in response to external inputs (nurture) and partly in response to internal physical structures (nature) but, perhaps, mostly through its own processes of maintenance and tweaking. As Sporns says, "Spontaneously generated network states form an internal functional repertoire. The observation and modeling of endogenous or spontaneous brain activity provide a unique window on patterns of self-organized brain dynamics—an intrinsic mode of neural processing that may have a central role in cognition" (151). The brain does not merely and automatically intake and process external inputs (say, teaching about MLA); rather, external inputs must "earn representation via their impact upon the pre-existing functional disposition of the brain" (151, Sporns quoting Rodolfo Llinás).

I like that: external stimuli don't just automatically find a place within our brains; rather, they have to earn a place among the stuff that is already there. Thus, merely showing up in class and lecturing about how MLA handles in-text citations does NOT guarantee a place for my lecture in any student's mind. It doesn't even suggest a place. Rather, my lecture must "earn representation via [its] impact upon the pre-existing functional disposition of the [student's] brain." What's more, while the relationship between my lecture and one student brain is complex and dynamic enough, I likely have thirty students, all with differing "pre-existing functional dispositions" in their brains. Now, we're really beginning to appreciate the complication and complexity of learning. How does one teacher awaken in the different minds of thirty people even so simple a concept as in-text citations according to the MLA? Does it even make sense to ask that question, putting the onus of learning simply on the teacher as if she can stamp out knowledge from brain to brain?

Well, it's Sunday morning, and I'm just getting to the essential questions for me, but I'm also in the middle of repainting the guest bathroom, a task my wife really wants me to finish. Her desires are definitely earning representation via their impact upon the pre-existing functional disposition of my brain.

I will, of course, talk more about neural networks and education later.

CCK11: ManyMe, or the Legend of Legion

Last night I posted some thoughts about the network nature of knowledge. While describing how my own understanding merges with understanding at a higher level, I used the metaphor of my voice joining a choir, and I said that "as my voice moves into a choir, my own unique tone and tenor becomes blended and a different voice emerges, a group voice." Even as I wrote those words last night, I was uncomfortable with my choice of the word tenor. It is not a wrong word or even an inappropriate word for the context, but it is not exactly the word that I was looking for, so I was uneasy with it. However, the evening was getting late, I was getting sleepy, so I moved on, ignoring the word.

Or so I thought.

I was awakened early this morning in a hotel room in Chicago by the word I was looking for: timbre (the quality given to a sound by its overtones, as (a): the resonance by which the ear recognizes and identifies a voiced speech sound (b): the quality of tone distinctive of a particular singing voice or musical instrument). This is the word I was looking for. It preserves the euphony that I was looking for—the consonance, assonance, and alliteration—and it has the more useful meaning of overtones, or echoes, that better captures the image I want of patterns echoing into other patterns.

We are all familiar with this kind of thing. We go to bed worrying with some issue only to awaken in the morning with the answer. Common enough. But here's the question relevant to my discussion of networks, especially neural networks: where did this answer come from? I was asleep, unconscious. Who figured this out? Who continued to look at tenor, recognized it as a near miss, looked for the alternative, and then woke me to give me the answer? uberMe? And who is this uberMe? The unconscious mind? That isn't a very enlightening answer.

Sporns makes an interesting observation at the beginning of Chapter 8 in his book Networks and the Brain (2011) when he details how the brain is not limited to merely processing the signals it receives through our sensory organs as we make our way through this world. Rather, the brain is extremely active, even when no sensory impressions are coming in, when the body is quiet, or unconscious as in sleep. Sporns says:

Until now, much of the interest in theoretical neuroscience has focused on stimulus-driven or task-related computation, and considerably less attention has been give to the brain as a dynamic, spontaneously active, and recurrently connected system. … Even cursory examination of structural brain connectivity reveals that the basic plan is incompatible with a model based on predominantly feedforward processing within a uniquely specified serial hieararchy. … The vast majority of the structural connections that are made and received among network elements cannot be definitively associated with either input or output. Rather, they connect nodes in complex and often recurrent patterns. … Even in regions of the brain such as primary visual cortex that are classified as "sensory," most synapses received by pyramidal neurons arrive from other cortical neurons and only a small percentage (5 percent to 20 percent) can be attributed to sensory input. (149, 150)

So much of the brain's activity, even vision, has little to do with sensory input or output; rather, it has to do with the brain's internal creative, organizing, sense-making functions (at least, that's how I'm interpreting Sporns' comments). And this activity is quite independent of my conscious mind, or awareness, which seems to be heavily dependent on the sensory side of the house.

Knowledge, then, even that knowledge easily identified with my own brain, is under the influence of forces and processes of which I have very limited control or conscious awareness. There is an uberMe, an unterMe, which is also at work, and apparently does not tire and require sleep as does the conscious littleMe does.

Hmm … this requires more thought by all the Me's in me, but now I have to go to a conference session. Later.

CCK11: Complex Networks and Knowledge

I think that the concepts of complex networks that I've gleaned so far from Morin and Sporns and of decalcomania that I've taken from Deleuze and Guattari lay two cornerstones for my emerging view of knowledge and learning.

First, complex networks suggest that knowledge is not a single thing, or single think (sorry, I couldn't resist, and I may yet edit this awful wordplay); rather, knowledge is a network of patterns enclosed by larger patterns and enclosing smaller patterns. Any given knowledge pattern is constantly open to the dynamic interactions of all those other various patterns on their various levels. This reinforces Morin's admonition that we define any entity—a cell or a word, say—not from its boundaries inward, but from its center outward. Or better yet, we should define a cell from its center both inward and outward. The center of the cell is not an endpoint of definition; rather, it is the starting point of definition, and to understand the cell, we must move from that center both outward to larger patterns and inward to smaller patterns. The cell must be understood as itself and as a part of an enclosing ecosystem and as an ecosystem for other entities, all dynamically interacting with each other, affecting each other and being affected by each other. Any given knowledge is like this cell: recognizable and addressable as itself, and yet not completely understood without consideration of its constituent parts and its ecosystem and of the ways that it interacts with both those micro and macro scales.

Thus, my knowledge of Connectivism is in fact a pattern of neurons, but that is just a starting point. Moving inward, that pattern of neurons encloses various patterns in different regions of the brain. Each of those patterns encloses individual neurons and individual electro-chemical processes, which enclose individual cells and electrical charges, which enclose other things, and other things, and other things, all the way down to quarks and strings, and maybe beyond that if we ever develop instruments that can see that far in. Back to our starting point and moving outward, the pattern of neurons that is my knowledge of Connectivism is enclosed by my conversation in MOOC CCK11 (among numerous other conversations I'm having—for instance, this blog), which is enclosed by an ecosystem of larger thought about education, which is enclosed by a larger system, and then a larger system, and then the entire Universe, and maybe beyond that if we ever develop instruments that can see that far out. To understand completely my knowledge of Connectivism, then, I must understand everything else.

This, of course, is absurd silliness. It is also our hope for the future. There is no end to learning anything, so we should never be bored. However, in the everyday discourse of common day, we simply can't let a single cell or bit of knowledge bleed into everything else in the Universe, even though it is quite literally connected to everything else in the Universe. A cell or an idea must in some useful way be recognizable and describable and must have potency in and of itself. How do we get out of this predicament?

Perhaps Nicholas A. Christakis and James H. Fowler have an answer for us in their book Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (2009). In describing how social networks work, they note that the influence of people extends out to about three degrees of separation. In other words, the patterns of our own lives influence our friends, our friends' friends, and our friends' friends' friends. After that, the potency of our patterns of behavior and belief fade and lose their efficacy. Perhaps some mechanism similar to this is at work among the various levels of patterns of any given entity. What do I mean?

Well, consider my knowledge of Connectivism as a single cell. My knowledge is still a recognizable entity with some potency within the context of this blog, though this blog also discusses other things. My knowledge is still recognizable and potent within the context of MOOC CCK11 and the larger discussion about Connectivism, but I think you an begin to see that my unique knowledge is beginning to fade in this larger conversation as it joins to and is overwhelmed by more voices and stronger voices. As my voice moves into a choir, my own unique tone and tenor becomes blended and a different voice emerges, a group voice. Connectivism means something different at this scale. Though my own meaning may still be recognizable, at two or three degrees removed from my single voice—my single understanding—the unique pattern of my knowledge begins to fade into the wider pattern of the general conversation about Connectivism. When we move up to a larger choir—the discussion of education in general—then my voice is quite lost, its identity and potency subsumed by and faded into the cacophony of voices. There are still a few voices potent and identifiable at this scale—Dewey, Piaget, Bloom, etc.—but most voices have long since drowned.

Thus, while I can trace the connections of my single knowledge about Connectivism to infinity and back (assuming I have the time, patience, focus, tools, and skill set), it makes great sense day-to-day to speak of my knowledge of Connectivism as a unique, identifiable entity with its own potency and contours and center. Being an English scholar, I think this entity is something of a convenient fiction, but it makes life much easier to manage.

I'll talk next post about decalcomania.

#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.

Formalism in CCK11

Our CCK11 Elluminate conversation today, 2011 Feb 09, featured guest speaker Neil Selwyn, who said several times that he thought we might lose something valuable if we indeed ever managed to rid our educational selves of formal institutions and practices. I imagine that he meant such things such as universities, school boards, curricula, programs of study, grading scales, and college deans. I think I have a faint appreciation for his point, but first I want to quibble with his use of the term formal.

To my mind, Mr. Selwyn was contrasting the wide open, free, self-directed, personalized, sometimes chaotic connect-and-collaborate informal structures of networks with the closed, restrictive, other-director, depersonalized, usually well-defined command-and-control formal structures of hierarchies. Popular usage of formal suggests that hierarchical structures are formal while network structures are informal, but I disagree. I take formal to mean any structure that is capable of generating a recognizable form on the basis of some regular procedures. If this is so, then a flock of birds is a formal structure: it is recognizable as a structure (a flock) and it is formed on the basis of a few, regular procedures. A fractal image is just as formal as, say, a triangle. A swirling eddy of water is just as formal as, and much more common than, a perfectly executed circle. Some forms are rigid and geometric, while others are flexible and fractal, but all are forms and, in that sense, formal.

That being said, hierarchies are different from networks, or rhizomes (to use my favorite term). Hierarchies are closed, rigid, and authoritative. Networks are open, flexible, and collaborative. Hierarchies are imposed on reality. Networks emerge from reality. I greatly prefer networks over hierarchies, and I suspect that many in CCK11 share this preference and predisposition.

Still, I think that Mr. Selwyn has a point. Hierarchies have built much of human culture for the past few millennia, and perhaps we dismiss them at our peril. It's at least an idea worth contemplating for a few minutes. Of course, in the past, we hardly had any options. If we wanted to build large organizations (churches, states, businesses, universities), then we almost had to resort to hierarchical structures, bureaucracies and such. We did not have the technology to enable one hundred thousand people to spontaneously gather and coordinate their behavior for some effort or play. We needed churches and states for that, so we built them—some big ones, too. In some ways, then, hierarchies have been one of the crowning achievements of humanity. I just happen to believe that they've been rendered somewhat irrelevant by networks, but perhaps not totally irrelevant.

The question, then, is what do hierarchies do well that we should keep them, at least in special cases?

Clay Shirkey posted an essay entitled Ontology Is Overrated that addresses this very issue, I think. What he calls ontological classification is very much like what I refer to by the word hierarchy. They both impose a prescribed order on reality rather than allowing an order to emerge from reality (this is reminiscent of Deleuze and Guattari's distinction between tracing reality and mapping reality). Shirkey makes a strong case that the new technology allows for humanity to largely abandon ontological classification schemes for more flexible tagging schemes for tracking and finding information. However, he notes, classification and hierarchy still have some strengths. Hierarchical classification works best when the domain being organized has:

1. Small corpus
2. Formal categories
3. Stable entities
4. Restricted entities
5. Clear edges

This is all the domain-specific stuff that you would like to be true if you're trying to classify cleanly. The periodic table of the elements has all of these things -- there are only a hundred or so elements; the categories are simple and derivable; protons don't change because of political circumstances; only elements can be classified, not molecules; there are no blended elements; and so on. The more of those characteristics that are true, the better a fit ontology is likely to be.

Shirkey adds that this scheme also benefits from being used with certain types of people, those who are:

1. Expert catalogers
2. Authoritative source of judgment
3. Coordinated users
4. Expert users

If the educational objective fits the above characteristics for both content and students, then traditional hierarchical structures may provide the student and teacher real benefits over a network structure. Thus, the first introduction to a new programming language might benefit from a more formal approach, in the sense that Selwyn was using the term. However, becoming a really good programmer means that eventually we leave the formal behind and move toward the more informal.

Even as I write this, something in me rebels. I'll have to think some more.