I read an excellent post by Lindsay Jordan related to #CCK11, the MOOC that I'm currently engaging. Following a comment by George Siemens, Lindsay makes a fine distinction between complexity and complicated: an airplane is complicated; the weather is complex.
I think I would rather say, however, that an airplane is complicated and creating the airplane is complex — not because the original statement is incorrect, but because it might give the wrong impression that complexity is of natural origins while complicated is of human origins. Rather, an airplane is complicated because it is a mostly static collection and arrangement of parts; whereas, creating the airplane is complex because it is mostly a dynamic interplay of people, ideas, materials, and processes. A specific airplane is a machine, complicated perhaps, but not growing. Creating airplanes is a living process, complex and growing.
As Edgar Morin points out so eloquently in his book On Complexity, we make a huge mistake when we try to reduce the complex to the merely complicated, or worse yet, to the simple. Actually, complicated and simple differ only in degree, whereas complex differs in kind from both. In one sense, both simple and complicated refer to a collection of fewer or greater elements in a particular, static arrangement. Complex refers to a collection of elements in an "infinite play of inter-retroactions" (Morin, 6).
Static entities, such as machines whether complicated or simple, are knowable, and once known, they remain known. Complex entities are not knowable in this manner. Rather, we engage complexities through what Morin calls a dialogic principle: we must constantly dialogue with the complex, for it is constantly shifting, growing, becoming. The complex is always in the middle, passing from this state to that. It is never static, thus never known definitively. Only through our interactions and our various connectivities can we know the complex, and we must constantly fire along these connections to activate feedback loops that inform, shape, and tweak our knowing of the complex entity.
From my experience, this distinction in knowing between the merely complicated and the truly complex makes a useful distinction between training to master a complicated concept or skill and teaching to master a complex discipline. Both training and teaching are exceedingly useful, and each is pre-eminent in its own right; however, they should not be confused with one another. When we are learning the one and only right answer, then we are involved in training. When we are learning to probe open-ended questions with open-ended answers, then we are involved in teaching. Sometimes the same class can be a mix of training and teaching, but we teachers should know when we are doing the one or the other.
And as George Siemens has pointed out elsewhere, we should always keep in mind that the right answer is especially short-lived these days, as the half-life of knowledge is continuing to shrink. Less and less of reality is static (or changing so slowly that it is practically static), thus less and less of our knowledge can be static. Rather, we must be constantly updating what we know so that it matches well with what is.
This is a very interesting question, the difference between complex and complicated. I was about to write, "it's essential that we know the difference", but then I thought the opposite! It's essential that we know, conceptually, that some things are complex and some things are complicated. But our approach to learning can't assume what we're learning is complex or complicated - we'll only know that in the process of discovery.ReplyDelete
We're naturally disposed to try to resolve complex, disordered things. We can't help that, and it's a great trait! What's changed now, though, is that we can expect more complexity, and need to develop a higher tolerance for living in it.
And while we're on the topic, do you know about the Cynefin Framework (youtube)? The video helpfully shows the difference between Complex, Complicated, Simple and Chaotic.
Thanks very much for the youtube connection to Cynefin. As we are discussing the differences between training and teaching in the classroom, we can examine those different types of learning. That some training or some teaching might not be best for certain learning is a useful perspective.ReplyDelete
Also, the Cynefin model can aid our discussion of levels of knowledge, such as differentiating between knowledge of data (the right answer) and knowledge of that same data in connection or relationship with other data. Teachers who are free to decide which of these they will value more can then set their course percentages accordingly.
Language and culture are disturbingly complex:ReplyDelete
I use the word Training for learning a skill. And teaching is about comprehension.
In my view complex means somewhere is uncertainty and one cannot make predictions. A complicated machine works in a predictable way. A complex system works but is shows surprises.
I really like the distinction you are making between "complex" and "complicated."ReplyDelete
Both of Jaap's comments seem particularly salient as well.
Learning is a complex experience, and as such, it would seem that no single model can fit every situation. However, a model that is learner-centered and content-informed would offer a broader flexibility in how we meet the challenge of education.
Thanks for the comment, and special thanks to Simon Fowler for the link to the Cynefin Framework. This captures quite nicely in visual terms some of the concepts I was trying to express in words.ReplyDelete
I agree with Simon that "we're naturally disposed to try to resolve complex, disordered things. We can't help that, and it's a great trait!" Science has made great progress by reducing complexity to simple, clearly defined areas of study. However, this reductionism removes the phenomena under investigation from the environment which gives them meaning. We must, therefore, be able to shift focus from specific to general. Indeed, it is this interplay between specific and general, individual and ecosystem, that begins to define complexity for me.