Hello students.
This four-part online module deals with
leading edge thinking in education.
Specifically, how learning and teaching have been reconsidered
through complexity science perspectives
and related influences like systems thinking and ecology.
They sound challenging,
yet they're very practical perspectives
that ground teaching in 21st century realities.
My job here is to explain them to you
as clearly and concretely as possible.
Then engaging you in some online activities and reflections
that make use of - or enact - these perspectives.
First, a little personal background.
I've been an idea nerd for quite some time now.
As a university student, I was bothered by scientific approaches
that assumed they could get final and objective truth about the world
even though the theories and paradigms they used
seem to change every 20 years.
And that everything could be explained through mechanical reasoning.
In fact, I remember having a debate
with a philosophy grad student
whose supervisor thought that moral choices could be reduced
to propositions within a computer program.
Not surprisingly, this "morality computer" amounted to nothing.
At the same time, I was bugged by social science approaches
that confidently asserted that everything
was just a social construction.
And that issues like bodily health
learning exceptionalities, and so on
were ONLY a matter of individual experience,
cultural norms,
and power relations.
As if our physical, biological,
and ecological history had no influence.
Here's another good anecdote.
One of my relatives, during his graduate studies,
thought that the cold was just a state of mind.
And that he could walk barefoot in the Canadian winter.
Needless to say, he quickly had to rethink that one!
In any case, I was unsatisfied by both of these extremes.
Than I took a part-time Masters of Education
course and started to learn about complexity science
with a Canadian educator, Brent Davis
who was then starting to be recognized
as an international leader in that area.
The new approaches I'm describing here
can also be seen in the Fourth Moment
of a book he co-authored in 2015
called "Engaging Minds", third edition.
For me, complexity science and related approaches
like systems thinking and ecology
offered a way to get over the old dichotomies.
And take a more intelligent and realistic approach to life, education
and specific issues like:
What is learning?
And how can we support it?
How should we think about student exceptionalities
How can we organize classes in a way that
nurtures individual diversity
yet at the same time creates a learning-focused classroom collective?
So what is complexity science?
One good way to explain it is to contrast it
with traditional approaches that came before.
Scientists in the last 500 years had a lot of success
with mechanical, reductive approaches.
For example, you can understand a clock well
by taking it apart into its component pieces.
And you can precisely measure and predict
what a billiard ball will do if you hit it with another billiard ball.
These are examples of simple systems.
Educators have tried to apply this sort of thinking to teaching.
For example, through factory-like classrooms,
inflexible learning objectives.
standardized tests and behaviourist training.
The results have generally been poor.
The reason is that this sort of mechanical, simple system approach
does not work very well for living systems.
For example, you can't understand or predict my behaviour
by chopping me up into my component organs.
In fact, by taking this approach you would destroy
the very complex system you're trying to understand.
And as we parents know,
we can't exactly predict or control what a child will do
based on our input.
No matter how hard we try!
Scientists across disciplines are therefore begun to develop new ideas and tools
for understanding and dealing with complex living systems.
Whether they be organisms,
human brains,
social groups,
cities or ecosystems.
One idea is emergence.
Complex systems emerge from the interaction
of their component parts.
The way I emerge from my component organs.
Or the way social norms and changes
emerge from the interactions of individuals.
But unlike simple systems,
complex systems are more than the sum of their parts.
because something new emerges at the level of the whole system.
For example, my choices and actions
or new social trends.
Again, these cannot be understood or predicted
just by adding up component parts.
Two other new conceptual tools are
self-organization and adaptation.
Complex systems adapt to their experiences and contexts
the way species adapt to their environments.
Unlike machines,
which require an outside designer to design or fix them,
complex systems adapt themselves
in a self-organized way.
Examples include the way you've adapted your thinking
based on your experiences in education.
Other examples of self-organization and adaptation are:
the way our immune system reorganizes its activities
to adapt to new germs in our environment.
The way our brain and nervous system change themselves
based on our experiences;
for example, learning tennis or music.
At a more collective level,
they can be seen in the way companies reorganize their activities
based on supply and command conditions
and the marketplace.
It can also be seen in the way sport teams
have to adapt to new strategies and playing styles;
for example, in basketball the Golden Warrior's three-point shooting.
Or Barcelona's possession and passing approach to soccer.
Or the increased speed of modern hockey.
The way classroom interaction and culture change
when a new teacher arrives and employs active learning,
cooperative groups, and so on
can also be seen as an example
of self-organization and adaptation.
Finally, this sort of adaptive self-organization
can be seen as learning.
In fact, Jean Piaget - the godfather of constructivism -
used exactly these terms to ground his theory of learning.
So the last thing I want to emphasize
is that we should see learning in this complex, biological way.
That is, as adaptive re-organization of our beliefs,
our schemas, neurons, or social interactions.
Rather than seeing it as "taking in" knowledge
into our heads, as if our heads were containers.
Or being behaviorally trained like input-output machines.
What does this mean for understanding the world
generally and education specifically?
Those will be the topics of the next few submodules.
For now, let's do a fun activity
and try to help you consolidate your understanding
of these ideas.