At first sight, the famous circle of chairs pretends that non-formal education is an orderly system, full of predictable harmony. What an illusion!
» Non-formal education is chaos at its best.
The contrast between the image and the core of nonformal learning is a wonderful illustration of the dialectics between order and chaos, harmony and disorder. And indeed, educators have much to gain from chaos theory.
In Greek mythology, the world wide web reveals to us, khaos meant “gaping void” or “nothingness” and was — at least by some — thought to be the primary source of all things.
In contemporary mathematics, chaos describes dynamical systems with a sensitive dependence on initial conditions.
«Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?»
Lorenz described how small changes in the variables of his computer weather model grossly changed the predicted weather patterns and developed a model to calculate how even the tiniest variations of initial conditions can amplify and induce large variations in a system’s behaviour.
With his discovery he — according to the committee that awarded him the 1991 Kyoto Prize for basic sciences —
«profoundly influenced a wide range of basic sciences and brought about one of the most dramatic changes in mankindâ€™s view of nature since Sir Isaac Newton.»
Discovered by Henri PoincarÃ© in 1890, chaos boomed after Lorenz stumbled over it with his attempts at weather prediction in the 1960-ies. Chaos is now believed to have been observed in fluid dynamics, in magnetic fields, in molecular vibrations, and the solar system.
» Nonformal education needs to added to the list.
What makes a system chaotic?
To be classified as chaotic, a system needs to be not only sensitive to initial conditions, but also nonlinear. What is a nonlinear system you ask?
That might be understood easiest by looking at linear systems, so by looking at what nonlinear systems are not. A linear system always responds predictably: at a given place and time, several independent impulses always trigger the same reaction — whether they were applied separately or jointly. The sum of the responses is equal to the sum of the stimuli.
In nonlinear systems, this is not the case. The response of a system largely depends on the timing, order and combination of inputs. Clearly, for nonformal education this is the case.
Another way to approach the differentiation between linear and nonlinear systems is by their appearance. Linear systems appear the same, no matter how they are looked at. Nonlinear systems look different depending on your perspective. Again, this is true for any learning situation — how close or distant you are, or how involved or excluded in the proceedings, greatly determines how it all looks.
Nonlinear dynamical systems often behave in ways that seem completely random and are (seemingly) unpredictable — at least we cannot predict their behaviour with what we know. This unpredictability is called chaos.
To the day, weather systems remain a perfect example for such dynamics. Weather forecasts also help to clarify a common misperception of chaotic systems: chaos can, many people believe, not be determined. After all, how often has it rained when Mr Weatherman told us it wouldn’t?
But chaos can be understood. Or could be — if we knew enough about initial conditions, stimuli and responses; and if our knowledge was precise enough. Theoretically, chaotic systems are completely deterministic!
we knew enough!
Again, this holds true for non-formal education. If we knew enough about the people in advance — say about their history, their patterns of behaviour, and their ways of thinking, to name but a few aspects of relevance — we might be able to determine how a learning situation evolves.
To a certain extent we try this, of course: we ask particular questions in application forms, we develop pre-course questionnaires, we build curricula in certain ways and run complex, challenging activities not on the first day of an activity.
As in mathematics, we are not trying to find precise solutions or perfect responses (how hopeless would that be!), but rather to determine how the system depends on (which) initial conditions and whether the system can be transformed to a steady state, whatever that may look.
If we knew exactly the personalities and behavorial patterns of participants AND the entire range of external influences AND the complete diversity of deterministic factors, we might be able to predict better how a learning situation evolves.
But how silly would that be? Nobody wants that. And even if we ever knew all these things, we would still only know the starting point — approximately. Our knowledge of the complete set of influential conditions for a learning system will never be exact enough; the complexity is simply too large.
I am not complaining: one of the principles of non-formal education is anyway to not control, but facilitate; to not demand, but offer; to not enforce, but enable.
In other words: prediction is, in our work, not only theoretically impossible, it is also philosophically not wanted. Nonformal education is deliberately fortuitous. But while things may be chaotic, they are certainly not random.
What can we learn from all this?
First thoughts go to the attempts of defining quality factors of non-formal education.
Seeing the wide range of factors that influence any learning situation — and there is not even agreement on what these factors are, not to speak of what their influence may be — it seems almost silly (and certainly vain) trying to define an endless list of quality criteria.
Can this be done at all?
Some people, for example, pay great attention to the quality of the venue. But haven’t we all experienced shitty courses in gritty places, and witty courses in shitty places?
Second thoughts go to toolboxes and the attempt to standardise educational methodology.
Keeping the unpredictability of learning systems in mind: can our response really be to have a limited set of tools at the ready?
I think not. A criteria for quality — returning to the previous question — emerging from this discussion may well be the ability of teams to develop new methodological approaches in response to a particular situation.
Third thoughts go to attitudes of educators.
What we do, at all times, is chaos control — no more, no less. Don’t we too often pretend we control the entire situation? We do not; we merely influence some aspects of a learning system’s chaotic behaviour.
A new, appreciative openness to surprises is needed. But being open to the unexpected is not enough: the unexpected is part of any learning system’s inherent logic — it makes these complex systems functional.
Final thoughts go to evaluation.
A defining characteristic of chaos is that the sum of the total is not equal to the sum of its different parts and their interaction. There is more to chaos than the naked eye can see.
Why then, do I ask, do we continue
to dissect educational activities?
Why then do we continue to look at the different aspects of a training — aims, objectives, outcomes, competences, methodology, support — and pretend that all of this taken together fully captures the activity?
It doesn’t; and according to chaos theory it never can.
It is the chaos of learning that makes our work so difficult and beautiful, and it is the ability to deal with chaos, complexity and ambiguity that makes for a good educator.
Chaos is a multidisciplinary science — it has been useful in such diverse disciplines as biology, economics, chemistry, physics, and more — and I believe that education has much to learn from (and give to) chaos theory.
How do you approach and experience chaos in learning?