Tuesday, February 28, 2012

Human and Non-human Connections, #cck12

I want to continue using comments from a discussion I've had with Frances Bell, mostly on Dave Cormier's blog. Let me note up front that I have not understood Frances particularly well, or perhaps a more forgiving way to say it is that I am having to learn what she means, and I don't always do that before I speak. It's a bad habit, but thus far, she has been quite generous with me.

At the end of her comment on Dave's post, Frances introduced two very interesting topics that I've been edging toward through my last two posts:
  1. the connections between humans and non-human in understanding learning, and
  2. power relations in networks, especially "where the machine is seen as amoral and humans as 'democratised.'"
I want to explore in this post the first issue: the connections between humans and non-human in understanding learning. Connectivism says that knowledge can involve non-human entities. I find a telling footnote in a list of Principles of Connectivism in George Siemens' online book Knowing Knowledge. The salient principle reads "Knowledge may res ide i n non-human appliances, and learn ing i s enabled/facilitated by technology." The footnote reads:
The concept of knowledge resting in non-human appliances (mediated by artificial intelligence or directed by intelligent agents) is controversial. As with the discussion on context-games, how one defines knowledge largely determines whether one will accept this definition. As I mentioned in the preface, I have largely avoided the use of the word information in this text. It could be well argued that all knowledge is simply varying shades of information, and information itself is transformed into knowledge when we have a personal relationship with it (i.e., we internalize information). This discussion, from my perspective, is unnecessary for the purpose of this book. In order to have any practical discussion of information and knowledge, we need to discuss it as if it is something that a) describes some aspect of the world, and b) something on which we can act. This simple definition provides the basis for viewing knowledge as being able to reside in non-human appliances.
Of course, this is too short a selection to be taken as a definitive statement of Siemens' position, but it can be a useful point of departure for my own thoughts. First, I notice a tension in how Siemens situates knowledge in an appliance, by which he seems to be suggesting modern, electronic appliances with artificial intelligence and intelligent agents. In his principle and then again at the end of the footnote, Siemens says that knowledge can reside in non-human appliances. He compliments the verb resides with resting when he says that "the concept of knowledge resting in non-human appliances … is controversial." To my mind, reside and resting suggest a passive holding place for knowledge, and this is very old hat indeed. We've been using non-human appliances such as cave walls, clay tablets, and papyrus scrolls to hold knowledge for millennia, both as extensions to our memories and vehicles for communication. Nothing new here. Of course, we can store more information in smaller spaces than before and we can share that information more readily with more people, and those are important differences, but they seem to me differences of degree rather than kind.

What is new is captured in Siemens' verbs mediated and directed. I don't know how active a role George is positing here for non-human appliances—and the meanings of these two particular verbs could be slanted either way toward more or less activity—but this is a difference in kind from the non-human knowledge appliances that came before, or so it seems to me. One of the virtues of a printed book is that it does NOT interact with the text, with the information contained within its covers; rather, the book preserves unaltered the text so that what I read today is the same as what I read yesterday (minus my own marginalia) and the same as what I will read again tomorrow. The text is static. Today, text is dynamic—along with other forms of information/knowledge such as image, number, audio, and so on (allow me to use information and knowledge interchangeably for a moment). Few these days will visit a third time a web page that hasn't changed, and while those changes are still mostly made by humans, they are increasingly being made, mediated, and directed by non-human appliances. This represents a fundamental shift in the relationship between human and the non-human knowledge/information appliance.

I see this difference most clearly in terms of Edgar Morin's distinction between closed systems and open systems. A stone is an example of a closed system: it is self-contained, needing next to nothing from the eco-system to maintain and persist as it is. Life forms, including humans, are examples of open systems: they are not self-contained, but absolutely require a dynamic exchange of energy, matter, organization, and information between themselves and their eco-systems to persist as living forms.

A book is more like a closed system (not completely closed, as I will argue another time, but for now, let's just say it's more closed); the recommendation engine on Amazon is more like an open system. The book does not take in more energy or information, process it, rearrange itself according to the inputs, and release new energy, information, and waste into its eco-system. This is not to say that the book is not a dynamic system. It is. Rather, the book is dynamic more in the way a stone in a stream is. Dynamic eddies and swirls develop, shift, grow, and wane as the water rushes about the rock, but the rock does not take in those as inputs. It just remains what it is until stronger outside forces push it into being something else. We want something similar from our books. We want them to stay put as they are. Just try re-writing Huckleberry Finn to see what a fuss you will raise.

The Amazon recommendation engine, on the other hand, does take in information and energy from its eco-system. It then processes that information, rearranges itself accordingly, and releases new energy, information, and presumably waste into its eco-system. This engine is more like a rather single-minded amoeba, or maybe a pigeon. I'm not sure how high up the intelligence ladder to go, assuming there is such a ladder, but this non-human appliance is able to monitor its environment, take in information, recognize options, make regular judgements based on that information, and release new information into the eco-system, which then becomes part of the reiterative feedback into the recommendation engine. Like all life-systems, the Amazon recommendation engine has the ability to self-organize, or simulates that ability very, very well.

Interacting with an open-system appliance is different from interacting with a closed-system appliance, or it sure feels different. But if so, then how? Let's think on that for a day and talk about it tomorrow.

Sunday, February 26, 2012

Intentionality in the Rhizome, #cck12

Yesterday, I tried to explain why I think that Connectivism may be guilty of focusing too much on the network and not enough on the individuals in the network. I suggested that Edgar Morin may have the correct stance: it isn't either the network or the individual; rather, it's each that must be accounted for in the examination of the other.

This is not some philosophical compromise or a happy medium in which opposing viewpoints each get a little something to save face; rather, it's a radically different way of viewing reality. I'll explain by starting with an objection to something that Frances Bell said in reply to my comments about intentionality being another point of entry into the rhizome: "I agree that intentionality emerges from more than just an individual ‘forming intentions’ and to some extent may be seen as a local network effect." To be fair, this is basically an introductory statement to her real point about connectivism overplaying the network effect, so I do not suggest that it adequately expresses Bell's point of view, but I can say that it represents the common view about human cognition, including intentionality. For most people, intentionality is a function of the individual brain or mind, even if it involves some local neural networks. If we want to understand any given intention, then we need only look to the individual who has, or creates, or forms, or expresses that intention.

I disagree with this point of view. I insist that if we look only to the individual, then we simply cannot understand the intention. Why? Because as Olaf Sporns says in his book Networks of the Brain, cognition is a function of networks. Olaf devotes much of his book to the neural networks that are the most obvious scale of the networks that support cognitive activity such as intentionality, but he quite clearly opens the discussion to the networks functioning at higher and lower scales. Networks depend upon other networks and form the basis for yet more networks. Limiting a study to one scale can be a useful fiction that allows for great focus and parsimony, but it is not reality—it's a fiction. And I say that in the very best sense of the term and with the utmost respect for fiction. I happen to believe that good fiction is the best we humans can do.

But … I start to wander.

Back to intentionality as a function of the individual. We simply cannot reduce intention (or any other cognitive function, such as learning) to the given individual said to be forming the intention or doing the learning. We can understand any given intention only as the complex interaction of an open system (the individual) with its eco-system. As an open system, any individual is defined in great part by the flow of energy, matter, organization, and information between itself and its eco-system. While the brain of the individual forms a necessary substrate for intentionality, it is not sufficient for intentionality. Rather, intentionality requires the dynamic interaction—what Morin calls stabilized dynamics (On Complexity, 11)—between the individual and his physical, social, emotional environment. Morin goes on to say that "the intelligibility of the system has to be found, not only in the system itself, but also in its relations with the environment, and that this relationship is not a simple dependence: it is constitutive of the system. Reality is therefore as much in the connection (relationship) as in the distinction between the open system and its environment" (11). Thus, if we want to understand anyone's intentions, then we must understand not only their individual reasoning but also the dynamics between them and the world. It's an impossible task to understand even one single intention completely, a human condition for which I am most grateful. We will never have an end to learning. Never. There are simply too many connections to follow, and each intention is the nexus of innumerable arcs, trajectories, flows, and asignifying ruptures.

But, God, can we create some magnificent fictions, full of real insight, beauty, and helpful hints about reality. If Deleuze and Guattari are correct, then we use cartography and decalcomania to accomplish these fictions.

So to sum it all up: yeah, it's all in the connections. Probably even more so than Siemens and Downes know or can imagine. Those connections, of course, include non-human, even non-living, entities.

But the Oscars are on, and my wife wants me to watch them with her, so let's talk tomorrow about how cartography and decalcomania aid the individual in managing the flow of organization and information between the individual and her world.

Saturday, February 25, 2012

The Problem of Intentionality, #cck12

In a recent exchange on Dave Cormier's post Embracing Uncertainty and the strange problem of habituation, Frances Bell challenged that Connectivism "tends to overplay the network effect and underplay human agency." It seems that she does not see much room in Connectivism for intentionality. I am not as familiar with the actor network theory that she referenced, so I did a bit of reading, including France's own article Network theories for technology-enabled learning and social change: Connectivism and actor network theory, (and graded 70 papers from my first year college students), and while I've much thinking to do yet on the issue, I want to make a few remarks.

I'll start by addressing Bell's complaint that Connectivism overplays "the network effect." She may very well be correct. While I won't speak for other Connectivists, I will say that I have a tendency to focus way too much on networks, or its more robust big sister—the rhizome. I do have a defense, though, and it has to do with contrast between the individual on one hand and the network on the other. Let me say up front that my discussion draws heavily from Edgar Morin's excellent little book On Complexity (2008), a book that I recommend to all who are interested in Connectivism and its related discussions.

Western culture has three hundred years of intense scrutiny of the individual by a science and philosophy that habitually reduced phenomena to closed systems, or discrete individuals, understandable in and of themselves. In educational terms, we have studied students as individuals, pretty much limited to what's inside their skins and brains. We teach them as individuals, we certainly test and assess them that way, and we promote them that way. We tend to think of knowledge as a function of individual brains (materialists) or minds (mentalists and spiritualists). My own field, rhetoric, has reduced writing to the use of proper grammatical and syntactical structures combined in regular ways—something like a fine watch. This is a mechanistic world view at its finest.

This science has had almost unbelievable run of successes that is difficult to challenge, but of course, it has been challenged. As Morin notes, the epistemology of classical science was undermined in the 20th century by a microphysics "which revealed the interdependence of subject and object, the insertion of randomness into knowledge, the de-reification of the notion of matter, [and] the eruption of logical contradiction in empirical description" (9) and by a macrophysics which "unites in a single entity the concepts of space and time" (9). And now, "the pedestal of knowledge is cracking" (8).

We now recognize that most systems in the Universe are not closed, especially those systems that we find most interesting: living systems, including us humans. We living things are open systems in a constant and dynamic exchange with our various eco-systems, or the networks within which we are embedded. (Forgive me here as I use eco-systems and networks interchangeably. I know that they are not synonymous.)

This brings me to my point: this blossoming awareness of open systems (Morin's term) and networks (Connectivism) and rhizomatics (Deleuze and Guattari) has proven to be among the most engaging and captivating strain of intellectual thought, at least to my mind, in the latter half of the 20th century. I suppose there are still things to say about the individual, but the rhizome is such rich and fertile ground that I, for one, am seduced by it and spend most of my time talking about it. I suspect that others find it equally attractive.

However, the emergence of the rhizome/network/open systems line of thought really should not dismiss all that we have learned through such great effort about the individual. That knowledge is still critical to our understanding. In fact, I think that we cannot understand the rhizome/network/open system without including the individual. Again, Morin says it best: "Reality is therefore as much in the connection (relationship) as in the distinction between the open system and its environment" (11).

For me, the Sunday School lesson is this: if you want to understand any phenomenon, especially any phenomenon such as intentionality that involves living systems, then you must consider both the individual and the network, the system and the eco-system. We've had 300 years of emphasis on the individual, and now some of us are perhaps over-emphasizing the network. I'm okay with that, but only up to a point, and I'm always pleased when someone reminds me that my point of view is just a bit skewed. It usually is.

Frances said more things, but I will address them later. This is a start.

Tuesday, February 14, 2012

Technology & Teaching - #CCK12 #CHANGE11

MOOCs such as CCK12 and Change11 almost by definition involve a lot of technology, and so questioning the use of technology in teaching might seem … well, almost sacrilegious. Still, The Chronicle of Higher Education published an article recently entitled A Tech-Happy Professor Reboots After Hearing His Teaching Advice Isn't Working, which seems to suggest that Michael Wesch, the Kansas State prof who has supposedly turned his back on educational technology, has finally seen the error of his ways. So are those of us who followed Michael Wesch's marvelous viral videos into the 21st century now supposed to do an about-face? I don't think so.

The title is a flagrant abuse of journalistic license that maligns both ed tech and Michael Wesch. You should read the article yourself, but clearly, Wesch has not dropped technology. Still, you can almost hear the collective sigh of all those tenured professors who can return to their lectures notes and bits of chalk ends, content that this instructional technology thing has been exposed as a bad idea.

It hasn't. What has been exposed is poor, passionless teaching whether to a face-to-face group of 20 or an online group of 200 or 2,000. The article itself makes the case plainly, despite its inflammatory title:
Mr. Wesch is not swearing off technology—he still believes you can teach well with YouTube and Twitter. But at a time when using more interactive tools to replace the lecture appears to be gaining widespread acceptance, he has a new message. It doesn't matter what method you use if you do not first focus on one intangible factor: the bond between professor and student.
Duh. I really doubt this is a new message from Mr. Wesch. I suspect he has always supported impassioned, competent teaching, even before he went online.

So here's the message: a passionless, inept teacher can muck up 20 students in a classroom or 200 students online. Upon reflection, this might actually be something of an argument against instructional technology. Given that through the use of technology, an inept teacher can damage more students, then we should keep technology out of the hands of inept teachers. I can buy that. However, it doesn't strike me as an argument against instructional technology; rather, it's an indictment of poor teaching.

The article is also an illuminating example of The Chronicle's bias toward teaching as the salient aspect of higher education rather than learning. The point of technology is not mostly to work for the teacher, but for the student. Technology does, in fact, work for students in my writing classes. Pen and paper doesn't work in some f2f classes.

Finally, the article creates a false dichotomy. Technology and f2f are not mutually exclusive. We can do both in different situations. I can imagine a wonderfully delightful f2f session with Cormier, Downes, and Siemens around a couple of pints on a clear, summer evening in Charlottetown, PEI. No doubt, as the student, I would learn much—perhaps they would also learn a few things—but this is not likely to happen as I am in south Florida and they are scattered across Canada (actually, Downes in Moncton is closer to me in West Palm Beach (1,960 m/3,154 km) than he is to Siemens in Athabasca (2,897 m/4,663 km)—just in case you are wondering). While the pints of beer have certain desirable affordances, the Internet has other just as desirable affordances (okay, not quite as desirable, but you get the point). Fortunately, we can have both, and the Net is just so much more accessible. So don't disconnect just yet.

Sunday, February 12, 2012

All Models Are Wrong - #CCK12

I was watching a wonderful slideshare by Jurgen Appelo called Complexity versus Lean, when I came across one of those pithy quotes that pulls ideas together for you. On  slide 74 of 92, Appelo says, "All models are wrong, some are useful." I liked the quote so much I googled it and discovered that, according to Anecdote.com, George Box, the industrial statistician, is credited with the quote ‘all models are wrong, some are useful’. I will leave it for another day to figure out what Box and Appelo mean by the quote, but I know what it means for me today.

Just yesterday, I left a comment on Joanne's post Rhizomes and Canons - Week 3 - CCK12, in which she says YES to many Connectivist principles that she's learning in CCK12, but NO to the idea that there is not "some knowledge that is settled and unassailable." She particularly wants to reserve a special place—perhaps a sacred space—for her own knowledge of God and human love. I have great sympathy for her point of view, being a believer myself, and yet I think she is confusing knowledge of the thing with the thing itself. This is not uncommon. It's what most of us do most of the time, and usually, it gets us through the day quite nicely.

But this quote—All models are wrong, some are useful—puts this habit of mind in perspective for me: all our models of God are wrong, some are useful. Likewise, our models of reality are wrong, some are useful. This, I think, is a core principle of rhizomatic/connectivist thinking. Reality does not sit still for our models. While we must create models of reality to attain some kind of sanity, the models are at best useful for a time. Eventually, all our models slip into an intolerable inconsistency with the reality they once mapped, and they cease to be useful—or worse, they become harmful and dangerous.

This is why Deleuze and Guattari insist that one of the core principles of the rhizome is cartography, or mapping. We must be in a constant process of mapping reality, especially that reality that we think we've already nailed down. Reality slips, and our models no longer map to it. We must build models and constantly rebuild our models. Models such as Connectivism, then, are wrong, though I and others find it useful for a time—perhaps a life time. I'm satisfied with that, but also vigilant. We are in most danger not when we think we know, but when we think that our knowledge is permanent, settled and unassailable. Nothing stops learning as quickly as settled and unassailable knowledge.

Saturday, February 11, 2012

Chasing Metaphors in CCK12

In a recent post entitled Week 3: Rhizomatic or biological neuralogical network?, my colleague in CCK12 Matt Bury writes that he's "been pondering the analogy of distributed networks of learners, i.e. Connectivism, as rhizomes" and concludes that he "wasn’t convinced by it from the start." You can read the rest of Matt's thoughtful comments on his blog, but if I understand him correctly, he doesn't see a tight fit between botanical rhizomes and networks of people. Actually, he seems to prefer neurological networks, which appear to be structured much more like social learning networks. I, too, have found neural networks to be most helpful in understanding networks in general and neural networks in particular, and I heartily refer interested scholars to Olaf Sporns' book Networks of the Brain.

Matt makes a fair point that others have made: the Deleusian rhizome doesn't match so well with botanical rhizomes which don't match so well with social networks. I see Matt's point, and I think it has some substance, but for me, it is somewhat beside the point for several reasons. First, Deleuze and Guattari use the rhizome mostly as a metaphor, or so it seems to me, and I don't think metaphors can be pushed to any great precision. Rather, a metaphor compares a more tangible thing to another less tangible thing to illuminate some aspect of the second thing, or sometimes both things. Love is a rose is a metaphor that suggests certain features of love that we might not have thought about before; however, if we press the metaphor too closely, we can quickly discover features of love that are not like a rose and vice versa. Metaphors shift our point of view so that we look at an object differently than has been customary. It doesn't map to the second thing precisely.

Then Deleuze and Guattari do not rely so much on any botanical definition of rhizomes; rather, they describe the rhizome as a linguistic and social structure mostly, providing a definition of sorts based on six features: connectivity, heterogeneity, multiplicity, asignifying ruptures, cartography, and decalcomania. I'm no botanist, but I don't think these features are prominent in any definition of botanical rhizomes. For example, Deleuzian rhizomes are heterogenous. Most botanical rhizomes are homogenous. Rather, these features describe much more closely the way language develops and spreads, and Deleuze and Guattari use them that way.

I have found Deleuze and Guattari's rhizome to be a particularly potent metaphor that has given me a new way of thinking about social networks and a new vocabulary to use in discussing those networks. The metaphor may not work for everyone, however. Love is a rose no longer works very well for most people, though at one time, it was quite the fresh and striking image.

I'm not sure why Deleuze and Guattari chose the rhizome upon which to construct their analysis. I think it was the visual features that appealed to them, but that's just conjecture. Or perhaps they wanted another botanical image to contrast with the tree image that they were using to describe hierarchical structures (another metaphor, and again, not so precise as some trees such as aspens could be classified as botanical rhizomes—a detail Deleuze and Guattari ignore or are unaware of). Anyway, I think the point I've been wandering toward is this: when we speak of the Deleuzian rhizome, or rhizomatics, we are not speaking of a botanical rhizome, but of a metaphor for that undifferentiated ground of being out of which structures emerge and into which all structures eventually return. To scale that down to something more practical, we are talking about how we humans are constantly trying to map a shifting landscape—to capture in language, mathematics, and social, political, religious, and economic structures those details of reality that for a time seem important, but which always shift away from our names and structures into something else. If that is how the complex world works, then how do we educate for that? That's rhizomatic learning.

Thursday, February 9, 2012

Rhizomatic Growth in CCK12

In a response to my previous post, fellow CCK12 MOOCer and blogger, Matt Bury, describes a number of techniques that he uses to build communities of inquiry and practice in his classrooms, and it reminds me that formal theories—if we choose to call Connectivism a formal theory—grow in very informal, rhizomatic ways, spreading like oil—or as Deleuze and Guattari say of the rhizomatic growth of language: It evolves by subterranean stems and flows, along river valleys or train tracks; it spreads like a patch of oil. It is not proselytized as a monolithic system of thought. I think this is one of the appeals of rhizomatic thinking for me, and I suspect it may be for others as well.

The monolithic system of thought, of course, has a most useful function. For a time, sometimes for a long time, it steadies our thoughts and allows us to measure progress and change. We can define goals and even appear to meet them. Yet, if Deleuze and Guattari are correct, then this measurement and movement is always something of a fiction—a useful fiction often, but a fiction—and eventually it becomes a fascist kernel that becomes more interested in preserving its own identity and establishing its own hegemony than in being useful. Even this open-ended, freely evolving Connectivist community may eventually write its own creed and bless those who are inside that creed and castigate those who are outside.

But never fear. If Deleuze and Guattari are correct, then the rhizome will simply move on, flowing around and beyond the little fascist knots that calcify from time to time. This movement in rhizomatic structures comes most explicitly, and sometimes forcefully, through asignifying ruptures, the fourth characteristic of the rhizome.

Wednesday, February 1, 2012

#cck12 - A Connected Classroom

I'm finding it quite easy to frame most of what I do in my writing classes with rhizomatic/connectivist thinking. I work hard to connect students to someone other than to me. I begin class by asking my students to take out their cell phones and text someone about what they are doing at the moment: learning how to write. This is a bit theatrical as most of the students think at first that I will demand that they turn off their cell phones. They are shocked but pleased to learn that this class will encourage cell phone usage. We then read the responses aloud, which almost always provides some merriment. This exercise immediately lets them know several things about the class:
  • connectivity is paramount in the class.
  • the class will connect beyond the confines of the classroom.
  • the class will utilize whatever tool is convenient and productive for writing.
  • the teacher may not be the center of the class universe.
  • writing is quite likely not what they thought it was.
  • we will find ways to have fun.
The ludic element should not be overlooked. Research shows that few things work better than fun and play for connecting people with each other and with a new endeavor. Rhizomatic connectivists must have a shtick and a game. By the way, one cannot read Deleuze and Guattari without being struck by the theatrical, ludic quality of their writing. If you aren't laughing through A Thousand Plateaus or Anti-Oedipus, then you're missing the point.

I then ask my students how many of them consider themselves writers. Usually, only a handful raise their hands. I then ask them how often they text each day. They all text a lot. I then insist that they are all writers, and usually, they protest that texting is not writing. This allows us to discuss writing, with me trying to convince them that their generation is generating more writing by more people than any other generation in history. I'm not sure how many of them are convinced, but it does serve them notice that they are not in a traditional college class, much less a traditional writing class. They sense that something is afoot, and by this time, most of them are alert. I like this.

I then have them introduce each other to the class, but only after they interview each other and take notes (more writing and connecting, but they don't usually think of it as writing or connecting). They have to learn the single most interesting thing they can about the other person that can be publicly shared. Both the interviews and the introductions are usually great fun, and after the introductions, I lead them in a discussion of writing as a tool for learning and for remembering. I again ask them how many make notes and lists for themselves or take notes in class. Most all of them do, so I submit that as further evidence that they are already writers. Usually by this time, many are beginning to warm to the idea. I ask how many enjoyed the interview, and most do. So I ask again if they enjoy writing. Not so many raise their hands this time.

I conclude the class by giving them my Gmail address and asking them to send me a Gmail identifying their Google account so that I can send them the link to the Google Sites class wiki, where the syllabus is housed.

So I devote the entire first day connecting the students to each other, to someone outside the class, to writing as they already use it, and finally to me and to the course apparatus, which obviously relies a great deal on Google. I find the Google tools much less restrictive and far more open to connectivity than the school's LMS.

Of course, next term I may use completely different activities, but the point will likely remain the same: foster connectivity that centers about the class proper, but encourages connectivity beyond the class.