We’ve questioned Success Academy’s “success” on this blog before. These statisticians bring a new lens to that question.
I don’t want to denigrate the good work that Success Academy teachers and students are doing. There are practices and systems well worth replicating and investigating in these schools. But Eva Moskowitz’s political framing and marketing of her schools as the solution to poverty is problematic.
“Everything we’ve done points to the fact that there’s not one single message that works. Sometimes swim parallel is great, sometimes it doesn’t work. Same for floating.”
It’s a view that the Surf Life Saving Australia has taken, too. After working with Brander, they’ve updated their messaging. Rips are a complex, dynamic hazard and the multitude of variables—swimming ability, current strength, circulation, wave size—make the threat nearly impossible to solve with one-size-fits-all advice. No single “escape strategy” is appropriate all the time, the group now says, and lifeguards in Australia currently recommend combining the advice from both MacMahan’s circulation concept and traditionalists like Brewster. If you’re not a strong swimmer, stay afloat and signal for help; if you can swim, consider paddling parallel to the beach toward breaking waves—though be mindful of the potential circulating current. “All responses,” the group concedes, “have their pitfalls.” [Bold added]
While this quote may refer to rip tides, I think the concept of dynamic complexity and variability could just as easily apply to schools and school systems. As we’ve explored here before, in the face of complexity, sometimes you’ve just got to try multiple strategies until something sticks. And sometimes, you’ve just got to pick something and stick to it. It is not always so easy to predict what will lead to a breakthrough.
In an article in Harvard Business Review, “The Biology of Corporate Survival*” the authors lay out some principles for managing complex adaptive systems. While framed for a business audience, these principles could be applicable to the complex adaptive system (or, perhaps more aptly, the “complexicated” system) of a school.
The authors delineate a set of principles for robustness into structural features, and managerial levers:
Expect surprise, but reduce uncertainty
Create feedback loops and adaptive mechanisms
Foster trust and reciprocity
How might these principles apply in a school?
I’ll leave that to you to contemplate, but for the record, I’ll note that most public school managers typically do quite poorly in reducing uncertainty and in fostering trust.
When I first started this blog, I hoped–as my younger, more idealistic and grandiose self–that we would uncover ecological principles of complex adaptive systems that could be applied in everyday practice.
While I have certainly uncovered many interesting themes and patterns along the way (such as obliquity, or the influence of unconscious bias on behavior), my slightly more hoary-eyed self can say, in an honest moment, that I have not discovered an alchemical praxis that will transmute principles of self-organizing systems into pedagogy or school organizations. Sorry!
A blog post, “Life Is Complexicated,” by Benjamin Goertzel helped me to clarify a reason why it might be so difficult to distill principles of complex adaptive principles into readily applicable practices.
Goertzel critiques the “Santa Fe Institute” concept of complexity, which has examined complex adaptive systems that have qualities of self-organizing emergence to identify universal principles. For Goertzel, the problem is not that there aren’t such systems, but rather that the real world systems that we wish to most understand aren’t simply complex—they are an admixture of both complex and complicated:
They are complex (in the Santa Fe Institute sense) AND complicated (in the sense of just having lots of different parts that are architected or evolved to have specific structures and properties, which play specific roles in the whole system). . . .
They are messy in a lot of different ways. They have lots of specialized parts all working together, AND they have complex holistic dynamics that are hard to predict from looking at the parts, but that are critical to the practical operation of the parts.
When considering a school or a school system, this messy confluence of self-organizing emergence and highly specialized roles and frameworks sounds like a more apt description. Our analogy of a school to an ecosystem is meant to push back against the linear thinking that many apply to schools—but I will readily acknowledge that a school is far from an actual ecosystem (really, it’s perhaps more akin to a garden). Schools are institutions embedded within a wider complexication of bureaucracy, policy, culture, economics, and politics.
So perhaps I shouldn’t feel bad about having difficulty in simplifying the realm of education based on an analysis of schools as complex adaptive systems. Schools are complexicated.
Ip asks an interesting question: How can we allow danger to make us safe?
He provides the example of the aviation industry, and how it is now far safer to fly than it is to drive in a car, thanks to the great pressure and transparency generated by any disasters that have occurred. He also frames this in terms of the economy, acknowledging that risk-taking is ultimately what increases wealth.
In the world of education, there has recently been much talk on the importance of failure in learning, and it’s interesting how this parallels broader discussions about complexity and uncertainty within other sectors. For example, if you really want to geek out, you can watch video of the panel of Tyler Cowen, Jared Bernstein and Alex Pollock debating economic principles — what I found interesting was how all of the panelists implicitly concurred on the point that human beings suffer from psychological limitations, which results in greater uncertainty and unpredictability. We have frequently examined this topic here under the banner of “cognitive bias.”
Much of the work that we do in my school’s Support Services department (we’ve decided to rebrand the term “special education) is to try and shift student perceptions of themselves. Often the greatest barrier to student learning is not disability, nor even the content and tasks demanded by rigorous academic subjects, but rather a student’s belief that they are either unable to do the work, or that asking the necessary questions to clarify their understanding is simply not worth the “risk” of appearing “stupid.”
To bring the classroom side of things back to Greg Ip’s question: How can we allow danger to make us safe? I think in a school, we can never completely remove the psychological “dangers” of peer and self-perceptions when challenged by difficult and complex academic content and tasks. The question in a school is not how can we make content easier or ignore the reality that failing in front of others is inherently risky, but rather how can we increase students’ willingness to take the risks necessary for learning? And as Ip suggests about the aviation industry, maybe being transparent about the smaller failures and misconceptions that inevitably do occur along the way can be of greater benefit in the long-run, and prevent much greater disasters from occurring father down the line.
We’ve investigated the concepts of randomness, disorder, and chaos and how they might relate to complex and dynamic systems here before. The obvious connection to a school, in case you’ve never worked in one, is that you can never quite anticipate what’s going to happen on any given day. Schools are complex systems rife with social and emotional and cultural and political and psychological interdependencies and turbulence. Yet it is this very complexity that makes working within them so very compelling.
An interesting article on Nautilus by Kelly Clancy, “Your Brain Is On the Brink of Chaos,” the concept of chaos is examined in its relation to the brain. Clark lays out some principles worth exploring further. For example, she lays out the following definition of chaos:
Chaos is not the same as disorder. While disordered systems cannot be predicted, chaos is actually deterministic: The present state of the system determines its future. Yet even so, its behavior is only predictable on short time scales: Tiny differences in inputs result in vastly different outcomes. Chaotic systems can also exhibit stable patterns called “attractors” that emerge to the patient observer. Over time, chaotic trajectories will gravitate toward them. Because chaos can be controlled, it strikes a fine balance between reliability and exploration. Yet because it’s unpredictable, it’s a strong candidate for the dynamical substrate of free will [bold added].
An important feature of chaotic systems is that, although they become unpredictable when you try to determine the future from a particular uncertain starting value, there may be a particular stable statistical spread of outcomes after a long time, regardless of how you started out. The most important thing to appreciate about these stable statistical distributions of events is that they often have very stable and predictable average behaviors. . .[bold added].
So through careful observation and analysis, chaotic systems can be predictable, even if they are quite unpredictable on an immediate basis. I thought Clancy’s explication of chaos as actually deterministic was also enlightening. This idea that it’s present state determines its future also lines up with what we’ve examined in terms of the possibility of an underlying mathematical simplicity of complex systems.
In that post, “A Self-Organizing Criticality, Somewhere Between Boredom and Chaos,” we also examined Per Bak’s concept of a “self-organized criticality,” in which complex systems spontaneously transition between states of order and disorder, which Clancy echoes in the following quote about the brain:
The critical state can be quite useful for the brain, allowing it to exploit both order and disorder in its computations—employing a redundant network with rich, rapid chaotic dynamics, and an orderly readout function to stably map the network state to outputs. The critical state would be maintained not by temperature, but the balance of neural excitation and inhibition. If the balance is tipped in favor of more inhibition, the brain is “frozen” and nothing happens. If there is too much excitation, it will descend into chaos. The critical point is analogous to an attractor.
This notion that a complex system hovers somewhere in the balance between chaos and order is a fascinating one, especially when you connect it to the idea of a school. It reminds me of a joyous classroom of students engaged in meaningful and challenging work. There’s a warm buzz of controlled but spontaneous activity and creativity. Students can very easily go off the rails, and it’s the teacher’s job to hold them in that “hinterland between the inflexibilities of determinism and the vagaries of chaos,” as Barrow eloquently phrased it.
Order and disorder enjoy a symbiotic relationship, and a neuron’s firing may wander chaotically until a memory or perception propels it into an attractor. Sensory input would then serve to “stabilize” chaos. Indeed, the presentation of a stimulus reduces variability in neuronal firing across a surprising number of different species and systems, as if a high-dimensional chaotic trajectory fell into an attractor. By “taming” chaos, attractors may represent a strategy for maintaining reliability in a sensitive system. Recent theoretical and experimental studies of large networks of independent oscillators have also shown that order and chaos can co-exist in surprising harmony, in so-called chimera states.
This idea of attractors is also fascinating to me. As I read this passage on the subway on the way to class this morning on my little smartphone screen, I thought back to the idea of perceptual illusions and their relation to powerlessness. I also thought about the effect of isolation on the brain. And I wondered if this concept of “sensory input” stabilizing chaos that Clancy just outlined can be taken almost literally, as in how the loving touch of a mother has been shown to be important in brain development. And how beyond touch, the tone and manner in how adults and students speak to one another, the colors displayed on the wall, and all the other contextual factors of the environment can be so fundamental to “taming” the chaos that lies both in extreme isolation (ever been alone in the wilderness? Your mind goes nuts) or in overcrowded, confined spaces (the ghetto). Schools can provide that stabilizing influence.
Again, we find echoes of this idea of harmony and symbiosis in Barrow:
. . . Chaos and order have been found to coexist in a curious symbiosis. . . . At a microscopic level, the fall of sand is chaotic, yet the result in the presence of a force like gravity is large-scale organisation. . . Order develops on a large scale through the combination of many independent chaotic small-scale events that hover on the brink of instability. Complex adaptive systems thrive in the hinterland between the inflexibilities of determinism and the vagaries of chaos. There, they get the best of both worlds: out of chaos springs a wealth of alternatives for natural selection to sift; while the rudder of determinism sets a clear average course towards islands of stability.” (Bold added)
Now that I’ve geeked out on chaos, back to work . . .
A central tenet of viewing schools as ecosystems is the acknowledgement of the complexity of education, whether at the level of an individual classroom, a school, a district, a state, or beyond. This complexity relates well to the natural world, particularly ecology, hence the analogy of an ecosystem. Ecosystems are rich with interdependencies and relationships that are ever evolving, just as a school is teeming with social, emotional, and intellectual interconnections.
In an editorial on Nature, the inherent complexity of ecology is analyzed, with the argument that due to its complexity, grand unifying theories are impossible. As the author puts it, “It is doubtful that the generalities that underlie the complex patterns of nature will ever be phrased succinctly enough to fit on a T-shirt.”
We’ve explored the concept that in the face of such complexity, prediction becomes a quixotic effort, and that we would do better to focus on what is more immediately and tangibly before us.
Similarly, Nature argues that ecological predictions based on disassociated “universal laws” must to be put aside in favor of field-based knowledge and understanding based on context.
Useful practical predictions need not stem from universal laws. They may come instead from a deep knowledge of the unique workings of each ecosystem — knowledge gained from observation and analysis. Proposing sweeping theories is exciting, but if ecologists want to produce work useful to conservation, they might do better to spend their days sitting quietly in ecosystems with waterproof notebooks and hand lenses, writing everything down.
The more open the organisation is to external sources of energy, the easier it is to harness the forces of emergence rather than entropy.
2) Following a comment at the bottom of the aforementioned post, here’s another one entitled Managing Complexity, in which the author points out that the management of complexity requires leadership that goes beyond simply being able to execute well, but moreover must be able to develop adaptivity to that which is beyond prediction or control.
Simply getting a promotion does not make you a manager. Until you are ready to take responsibility for that which you cannot control, you are just someone with a title, not a leader.
3) Finally, a post from Steven Strogatz, Dangerous Intersection, which I discovered thanks to a newsletter link from Ed Yong, gives a mathematical exposition of how thresholds are crossed and what occurs when the straw that broke the camel’s back is placed.
. . . the stage is set for catastrophe whenever a line intersects a folded curve tangentially.