Often, people seem to discuss schools as centres for optimising students' learning and teachers' teaching. However, I want to share a distinction I perceive: schools aren't optimisation centres but developmental systems. To help you understand my distinction, I’ll compare schools with different viewpoints of evolution. My view will come from an enactive cogsci perspective (e.g. Varela et al. 1991).
Natural selection doesn’t optimise species, learning doesn’t optimise cognition
There’s no doubt that natural selection occurs in nature, but how it does so has been debated over time. One view was that natural selection acted to select for traits. Mutations would arise over time, providing variants in the population, and selection would act to keep the most optimal every time. This way, individual traits of species were optimised for their environment until they matched it perfectly. This was the “adaptationist” view, which saw natural selection as an optimisation algorithm.
The view would come under scrutiny, however. Selection can’t possibly select for anything—it isn’t a force or a thing. Instead, it’s argued, that selection only acts as a filter. It discards what doesn’t fit the environment, whatever can’t surmount the obstacles to surviving and reproducing. On the other hand, whatever fits isn’t optimal, it’s just managed to surpass the difficulties put in its way. It satisfices the minimal requirements. It’s viable, but not optimal.
This is like learning itself. We discard ideas when we realise they’re wrong. But unless we bump into this problem, we’ll maintain our ideas. Think about a time you’ve realised that you had something wrong despite not being a problem in your life for years.
Therefore, while we do learn more through education, we aren’t optimised by it. Instead, we increase our ability to think and perceive, and, therefore, to navigate the world with more adaptive and adequate actions.
Species don’t evolve to, and students don’t adapt to, a pregiven environment
The adaptationist view saw species as arriving into a pregiven static environment that imposed its difficulties onto species, who were then optimised for it. Yet, the environment is never pre-given or static.
A horse, for example, eats grass. The grass forms its environment, but by eating it the horse changes its environment. Firstly, there'll be less grass and other species may grow in its place. But the grass, as an autonomous organism itself, responds to grazing and begins behaving in a new way. The horse, therefore, changes its own environment. Over time, due to the recurrent mutual interactions, species evolve to each other in a never-ending dance—not to a pre-determined optimal. The actions of the horse bring forth its environment as much as the environment brings forth the horse.
Schools too are complex systems that engage in a constant dance of adaptation between actors. Students don't parachute into a pregiven static school. Teachers and students are constantly adapting to each other and shaping each other. What we learn shapes our actions and our actions shape what we learn, in such a way that our schools, and our learning, are never-ending evolutionary processes.
Neither species, schools, or students are trivial systems
Genetics also played a role in dismounting the adaptationist view. For the adaptationist, natural selection acted—not just to optimise a whole organism—but optimised individual traits in isolation of each other. But genes don’t have a single role in a single trait. The genome is a complex system in itself. A single gene will have many different roles in different parts of the body. For example, attempting to optimise its role in, for example, the brain may make it less effective in the intestine, and the spleen, but be neutral in the skin, and so on.
Monocausality—the idea that an effect has a single (linear) cause—isn’t found in complex systems except for astonishingly rare instances. This makes experimentation on complex systems difficult. Ross Ashby explained this in the 1950s (1958, 11):
As I have said, we must beware of taking our strategies slavishly from physics and chemistry. They gained their triumphs chiefly against systems whose parts are homogeneous and interacting only slightly. Because their systems were so specialised, they have developed specialised strategies. We who face the complex system must beware of accepting their strategies as universally valid. It is instructive to notice that their strategies have already broken down in one case, which is worth a moment’s attention. Until about 1925, the rule “vary only one factor at a time” was regarded as the very touchstone of the scientific method. Then R. A. Fisher, experimenting with the yields of crops from agricultural soils, realised that the system he faced was so dynamic, so alive, that any alteration of one variable would lead to changes in an uncountable number of other variables long before the crop was harvested and the experiment finished. So he proposed formally to vary whole sets of variables simultaneously—not without peril to his scientific reputation. At first his method was ridiculed, but he insisted that his method was the truly scientific and appropriate one. Today we realise that the rule “vary only one factor at a time” is appropriate only to certain special types of system, not valid universally. Thus we have already taken one step in breaking away from the classical methods.
As schools are also complex systems, we can expect a change in one part of the system to reverberate through its parts in unpredictable ways. Rather than linear cause-effect, in complex systems feedback loops are the norm, leading to unforeseeable outcomes. Not just learning outcomes but also changes in relationships, perceptions, or habits, which then affect other things (e.g. see here).
It wouldn’t be wise to see one activity triumph with one teacher and then impose it on all others to enact with fidelity. Because it's difficult to fully discern the causes of success observed in a subject with specific students and particular teachers.
It’s likely to be a multitude of intertwined factors, which have evolved from a history of actions unseen by the observer. As such, several observers would likely discern distinct causal factors due to differing perceptions. Which factor is the one that causes a major effect? Which have minor effects? How do they interact? Do they all need to be present together for something to new to emerge? Or just several? Are they dependent on another undiscerned factor? What will emerge if we mandate just one of these precise activities?
Schools aren’t optimisation centres, but developmental systems
It's impossible to optimise a complex system, an observer can't even know what to optimise (Meadows 2008). As schools, students and teachers, are complex adaptive systems, there can’t be a claim of optimality for learning sequences, classroom regulation, teaching activities, or professional development. Imposing a teaching activity on teachers is limited to linear cause-effect thinking and an observer’s limited perception.
Therefore, mandating precise activities is fraught with difficulties. What's more, once an activity is mandated, teachers and students will adapt and respond in unforeseeable ways. The dance continually develops.
Rather than optimality, it would be more useful to discuss the viability of actions. Educational research and experience can be starting points for exploring and discussing viable pedagogy.
There are, for example, unviable ways to regulate a classroom discussion. There are unviable ways to sequence a curriculum and unviable ways of teaching certain concepts. Often, the viability of an action will depend on the total system, its interactions and their history.
For example, asking particular students to answer questions in front of their peers is viable within a certain culture that has arisen through other viable acts. But it can be unviable if students feel they are being judged and feel that their answers don’t influence the course of a lesson.
Teachers need to adapt to their own students and their circumstances. What’s viable for one teacher will have evolved through a history of adaptive interactions with their subject, students, and school. What’s viable, however, can be shared, discussed, and explored in a collaboration.
Empirically informed ideas on viability will likely align views somewhat while retaining variety within those views. Retrieval practice, for example, could be collectively understood as a viable pedagogical activity without stipulating how, or when, it must be enacted.
Discussing viability helps us stay focused on ensuring a quality education for our students. At the same time, it helps us keep in mind the impossibility of discerning all the causal factors and, therefore, the inability to precisely predict, or control, systems. It keeps us humble. Let's focus, then, on schools as viable developmental systems rather than something that must be optimised.
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References
Ashby, W.R. 1958. “Requisite variety and its implications for the control of complex systems.” Cybernetica 1 (2): 83-99.
Meadows, D.H. 2008. Thinking in Systems: A Primer, edited by D. Wright. USA: Chelsea Green Publishing.
Varela, F., Thompson, E., & Rosch, E. 2016. The Embodied Mind: Cognitive Science and Human Experience. Revised Edition. Ebook edition: MIT Press.