Assessing Complex Systems and Sonnet 73

As my own views about education continue to emerge, I understand them best within the context of the conversation about complexity—complexity as a large, transdisciplinary conversation that has been emerging for centuries, but that was made unavoidable by the emergence of relativity and quantum physics at the beginning of the 20th century. The fact that I just used a form of the term emerge three times in a single sentence suggests how much Complexity has informed my thinking. As I am so very fond of following rabbit holes, it helps me from time to time to gather my thoughts to see if something coherent emerges. See?

I've been reading through a series of articles about complexity and the limits of knowledge from a 2005 special edition of Futures. I recommend it to anyone interested in either complexity or knowledge or the knowledge of complexity or the complexity of knowledge. You can really get tangled up, or at least I can. So I want to do a bit of untangling.

At the largest scale I can think about, complexity is that zone of engagement between the open-ended future and the closed past. We call that zone of engagement the now or the present. I could refer to it as The Now and perhaps win an honorable mention in the next Eckhart Tolle book or a few minutes on Oprah, but I'm feeling sober this morning, so I'll just stick with the now. Complexity is the activity that emerges between the juxtaposition of the hot, open-ended potential of the future and the cold, fixed certainty of the past. Complexity is the result of the tension between hot and cold, or to borrow a phrase from David Foster Wallace, it is the result of the miscegenation between a hot air mass and a cold air mass. That image works for me: we exist in the thunderstorm of the now, and though we may long for the potential of the future or the certainty of the past, we cannot live in either place. Life, and by extension knowledge, cannot exist in the chaotic order of the future or the fixed order of the past, but only in the dynamic, emerging order of the now as the heat of the future slides by and is transformed into the cold of the past (I'm perfectly willing to believe that the transition from hot activity to cold fixity only gives us the illusion of movement, but the visual metaphor is appealing to me). The complexity of the now is all we get, all we have, but because the now is a complex system, it is profoundly affected by and interacts with both the future and the past. Both the future and the past inform the now, and the dynamism of the now informs both the future and past in turn.

So for me, complexity is about as big an idea as I can have—sort of a God idea, but I don't intend to talk about God in this post; rather, I want to talk about knowledge and education and what the overarching concept of complexity has to do with them. How does it inform my ideas of knowledge and education? That's the question.

In their Introduction: Complexity and Knowledge (Futures, 2005, Vol. 37, pp. 581-584), Peter Allen and Paul Torrens note that the study of open systems proved to be very problematic for scientific knowledge in both the hard and soft sciences. They say:

For isolated and closed systems classical thermodynamics gave us the knowledge to predict the transformations and final equilibrium states of a system. Obviously, for frictionless systems such as those involved in planetary motion, Newton’s Laws allowed the prediction of orbits and eclipses, both forwards and backwards in time. Knowledge was complete and related directly to prediction. But, open systems were much more problematic. (581-582)

Closed systems, it seems, function in the simple and complicated domains, as defined in the Cynefin Framework. The simple and complicated domains afford us "the knowledge to predict the transformations and final equilibrium states of a system … both forwards and backwards in time." In closed systems, we can arrive at complete knowledge with reliable—testable and verifiable—predictions. Open systems do not allow such affordances.

This is a big problem, as Allen and Torrens note. So what's wrong with open, complex systems? First, we have a boundary issue. Open systems do not have discrete boundaries. I can see this quite clearly when I try to imagine the boundary between now and the future. The boundary has a thickness. I can feel the future coming and the past slipping, sometimes quite strongly, but I can never quite put my finger on the exact line between the future and now, and as soon as I fix my finger to a line, it slips into the past (the line, not my finger, which fortunately stays with me in the now). So the boundary also has an incredible thinness. So which is it—thick or thin? Well, both, of course. The boundary is open, and the exchanges between the system inside (now, for instance) and the systems outside (future and past, for instance) modify all systems. I really am speaking universally here; thus, I include those systems within the simple and complicated domains. From my point of view, everything belongs to the complex domain, and the simple and complicated are but temporary arrangements that we form for our convenience—like a sock drawer, or a classroom. We can pretend for a moment that our classrooms belong to the simple or complicated domains, but they don't. The classroom is a complex system of complex systems, and to treat them otherwise is to risk complete misunderstanding.

The dynamic interaction at the boundaries among complex, open systems means that it is very difficult to limit ourselves to local causality. In other words, the events in any one classroom are the result of remote causes (familial, social, economic, political, etc.) just as much, sometimes more so, as local causes (say, a classroom lecture or demonstration), and we are unlikely to be able to assess exactly what caused any given behavior in our students. Nor can we predict reliably the effects of any applied intervention or instructional design. As Allen and Torrens put it:

The simplest definition of a complex system is one that can respond in more than one way to its environment. … So, ‘knowledge’ about the future trajectory of the system can be both quantitatively and qualitatively wrong. … Innovation can occur, and it may have untold implications for the future evolution of both the ‘inside’ and the ‘outside’ the system. Similarly, the same ‘intervention’ may produce two different results on what were believed to be similar systems, since a single complex system can respond to an intervention in different possible ways. The outcomes could differ qualitatively and this surely must therefore introduce some doubt into the ethical basis for the intervention. … These new ideas force us to accept a significant reduction in our powers of prediction, and even in our ability to frame a useful question.

I find myself, here, slipping into considerations about evaluation and assessment in education, and I'm reminded of the recent words by Christina Hendricks, Stephen Downes, and Keith Brennan about how to assess a MOOC. I won't go into the details of their discussion, but I will say that from my vantage point measuring a MOOC, or any other classroom, is more like measuring a thunderstorm than measuring an automobile. That being said, I think we are beginning to develop some useful metrics for measuring open, complex systems. I may need to complete one of Siemens' learning analytics MOOCs to learn what some of those metrics.

I want to add, as well, that I think we literary scholars have been confronting open, complex systems for a long time. Consider a Shakespearian sonnet—Sonnet 73 will do. Almost all the data that I can gather from traditional measurement (meter, rhyme, number of lines, number of feet, etc.) says so very little about the poem. That data can enrich my understanding and appreciation of the poem, but by itself, that data reduces the poem to a closed system, a handy sock drawer, some trivia to answer on a test, and I would never read the poem again if that's all I had. Only when I open the poem to its environment, allow it to breathe, allow it to help me make connections to grandma, winter freezes, and dying embers, to my hopes and fears, only then do I find value and meaning. I find that value and meaning difficult to measure and assess, but I'm hopeful that we are developing the tools that will help us do so. Some very interesting things are happening in the digital humanities that point this way. I'll have to read some more.

MOOCs, Transdisciplinarity, and Thinking Big

In his 2004 Phi Beta Kappan essay entitled Thinking Big: A Conceptual Framework for the Study of Everything, self-described contrarian educator Marion Brady writes that "the main task of educating is to help students make more sense of the world, themselves, and others" (p. 277). He attacks the current state of knowledge as represented in the plethora of academic subjects and disciplines and insists that such a fragmented approach to knowledge will, in the words of Buckminster Fuller, "be the undoing of the society." He quotes Fuller again in a marvelous 1980s complaint to American educators: "What you fellows in the universities do is make all the bright students into experts in something. That has some usefulness, but the trouble is it leaves the ones with mediocre minds and the dunderheads to become generalists who must serve as college presidents . . . and presidents of the United States." I truly wish I had said that, but … well, he was Buckminster Fuller.

Brady then identifies the basic theory of education that underlies the fragmented, disciplinary approach to knowledge:

The present curriculum, made up as it is of separate, specialized studies, exerts considerable pressure on teachers to make major use of what could be called “Theory T.” Theory T dominates American education. … T stands for “transfer.” Those who accept Theory T believe that knowledge is located in teachers’ heads, textbooks, reference materials, and on the Internet and that the instructional challenge is to transfer it from these locations into the empty space in students’ heads. The degree of success of the transfer process can be measured with relative ease, which helps explain its broad appeal. … Evaluating performance is simple enough to allow student responses to be scored by a machine. (pp. 279, 280)

 He then contrasts Theory T with what he calls Theory R:

Theory R assumes not that students’ heads are empty but that they are full. The primary instructional challenge, then, is not to transfer new knowledge but to help students reorganize existing knowledge to make it more useful, consistent, or true and to supplement it with insights and skills that will help explain more fully what they already know.… Students in Theory R classrooms must be active processors of information. Theory T emphasizes recall; Theory R requires students to engage in every known thought process. … Theory R requires students to make connections, to perceive relationships, and to synthesize ideas. It sends students searching the far corners of their minds without regard for the artificial, arbitrary boundaries imposed by academic disciplines.

Brady gives here a neat precursor to Connectivism, I think. First, he emphasizes that each student already possesses all the neuronal networks needed for making connections, perceiving relationships, and synthesizing ideas. We teachers do not transfer anything into the imagined empty memory slots of student brains; rather, we present them with a, hopefully, coherent and engaging series of artifacts and experiences to which they may connect, perceive relationships, and synthesize ideas, or not. All too often what they connect to, perceive relationships among, and synthesize are ideas that we never taught, or didn't know we were teaching. And each student makes these connections and patterns within an ecosystem (their own life stories) that we teachers know little to nothing about, and that ecosystem, that context, provides almost all of the meaning for whatever new connections and patterns the student is weaving. This reminds me much of Paul Cilliers' definition of knowledge as "information that is situated historically and contextually by a knowing subject" (Why We Cannot Know Complex Things Completely in Capra, Juarrero, Sotolongo, and van Uden's Reframing Complexity: Perspectives from North and South, 2007, p. 85). In other words, while information may exist apart from our students as data, it does not become knowledge until the student situates that information within a context that includes themselves and that necessarily informs the information in ways we teachers cannot predict or control.

But what most impressed me about Brady's article was his observation that this process of making connections (mapping, as Deleuze and Guattari say) "sends students searching the far corners of their minds without regard for the artificial, arbitrary boundaries imposed by academic disciplines." It seems to me that Connectivism and MOOCs are wonderful vehicles for transdisciplinarity, which transcends the "boundaries imposed by academic disciplines." I know that the MOOCs I have joined have had a marvelous, transdisciplinary reach in content and participants. Though I have had some of the most engaging and rewarding conversations of my professional life, as far as I know, I have actually had no conversation with another writing teacher, aside from one colleague who shared an office with me and a few MOOCs. Almost all of my conversations have been with scholars and practitioners outside my discipline, which makes my engagement in the MOOCs most transdisciplinary.

I think I will explore this a bit more in the next few posts.

Connectivism and Ideology 3

So on the whole, I like what James Berlin has to say about reality, knowledge, and rhetoric in his article Rhetoric and Ideology in the Writing Class: that "the real is located in a relationship that involves the dialectical interaction of the observer, the discourse community (social group) in which the observer is functioning, and the material conditions of existence" (488). Berlin and I are starting from much the same place epistemologically, but a few of his comments secondary to this core concept bother me. I should explore those.

First, Berlin insists emphatically that knowledge depends entirely on language. When he explains the dialectic at work among observer, social group, and material reality, he says:

Knowledge is never found in any one of these but can only be posited as a product of the dialectic in which all three come together. … Most important, this dialectic is grounded in language: the observer, the discourse community, and the material conditions of existence are all verbal constructs. This does not mean that the three do not exist apart from language: they do. This does mean that we cannot talk and write about them – indeed, we cannot know them – apart from language. Furthermore, since language is a social phenomenon that is a product of a particular historical moment, our notions of the observing self, the communities in which the self functions, and the very structures of the material world are social constructions – all specific to a particular time and culture. These social constructions are thus inscribed in the very language we are given to inhabit in responding to our experience. Language, as Raymond Williams explains in an application of Bakhtin (Marxism and Literature 21-44), is one of the material and social conditions involved in producing a culture. This means that in studying rhetoric – the ways discourse is generated – we are studying the ways in which knowledge comes into existence.

If I'm reading Berlin correctly, then he is saying that knowledge is created, managed, expressed, and propagated solely through language. If that is his point, then I disagree. Berlin does not clearly define either language or knowledge in this essay (they are not his central terms), so perhaps he is using both or either in a way that allows him to make them concomitant, but my understanding of both leaves room for much knowledge that is not concomitant with language. For me, it is sensible to say that my dog knows where to find his food or knows how to find his way home, yet aside from a few barks and growls, the dog has no language to speak of (sorry, I couldn't help that. I didn't see it coming). Limiting myself to humans, Berlin's view seems to disregard body knowledge. I've coached enough soccer to know that the foot knows how to do some things that the mind cannot speak of. Any craftsman's hands knows things that her tongue cannot articulate. Our lives are laced with aesthetic, ecstatic, religious, and emotional cognitions that capture a knowledge too deep for words and yet that form some of the most profound and precious knowledge we possess. Indeed, it is not uncommon for people to feel that capturing such knowledge in language profanes that knowledge. For me, this knowledge is real.

I suspect that a dialectical materialism – a wonderful ideology – lies at the heart of Mr. Berlin's point of view, yet he may be giving it too narrow an interpretation. For me, knowledge is a collection of beliefs that structure my interactions with the world. In other words, knowledge is what I'm willing to take action on or against. I am well aware that most of what I know is likely wrong, incorrect, inaccurate, unreliable, inconsistent, unreasonable, irrational, and more. Most of what I take for knowledge will be nonsense, error, and myth 100 years from now, much less 1,000 years, but my errors are my current knowledge none the less. Mr. Berlin may not allow for any reality other than the material or any knowledge other than that which can be named, but that is too narrow for me and, in my rhetoric, it is indefensible.