This is one of those posts where, as I write it, half of my brain is quite convinced that I’m really onto something, and the other half is equally sure that I’m just rehashing something that everybody else has already worked out.
“What’s the difference between Recall and Re-creation?” – an interesting question that came up last year in a conversation about learning. I’ve played with it, in the back of my mind, ever since.
In one sense it’s a simple distinction. Back in high school, you might have mechanically solved a system of multi-variable linear equations, simply by recognizing the form and recalling the rubrics – that “Recall”. But given an unfamiliar style word problem, or having to derive a proof would have shifted things to the arena of Re-Creation. In over-simplified terms, Recall is about knowledge, and Re-Creation relies on both knowledge and understanding.
It seems, though, the Recall and Re-Creation are actually part of a continuum. If you look at how people learn, it seems to go something like this:
or possibly it is more realistically like this:
where Remixing and Creation are parallel but functionally similar.
some side comments are hidden in the toggle here:
As I was writing this, it hit me the first aspects of the diagrams seem to almost be akin to the Montessori three stage lesson (“This is a triangle.” “Can you find the triangle?” “What is this shape?” And by extension the Re-Creation aspect might be approaching “What makes something a triangle?”) The similarities actually makes reasonable sense, Montessori is about building knowledge and understanding – giving the precursor mental tools needed to allow meaningful exploration and creation.
When I look at the continuum as a whole, it makes me wonder if I’m just unconsciously revising Bloom’s Taxonomy. I rather hope not. I have always had a bit of an uneasy relationship with Blooms.* It seems to be easily subject to forced or clunky applications; the Creation bit always seemed to end up being a diorama or a “medieval newspaper” project on some history topic – I never learned much history from those, the brain was too full of executing the logistical side to worry much about history.
* coming from the science, and then information science world, Bloom’s is something I met (formally) much later in life and immediately recognized as the source of many a painful and pointless classroom experience. Now don’t get me wrong, there are marvelous teachers who integrate Bloom’s seamlessly (they are probably also adept re-mixers) but it is easy to use it to drive unconnected activities, piled one atop the other like a stair step of cake layers, or so many boxes to tick.
back to the regularly scheduled post, already in progress…
From Algorithm to Understanding
Obviously we don’t actually learn things in single incremental steps, there’s a lot overlap (bleed-through) and cycling back and forth, but on a fundamental level this seems to be useful mental model (for me, at least). Recognition and Recall seem to be pretty well established concepts (e.g. Oppenheimer on fluency and priming), where it got interesting to me was when that long-ago conversation looked at recall vs re-creation.
The difference might have a familiar example in math. I might know how to solve (algorithmically) a given class of equations, and I might even know pretty well when presented a real world problem which class of equations would apply to it. That’s all in the realm of Recall.
Where Re-Creation comes in might be in something like deriving the equations from fundamentals (I had a friend who was an astrophysicist whose adviser would, when approached with any problem would invariably start out with “Well, let’s see, V=iR…. and then derive from there. He was modeling Re-Creation – helping the students build a habit of approaching questions from a point of deeper understanding – even if it was probably a bit annoying for the student at that moment)
A successful removal of all the “green globs”. A further description is available at http://youtu.be/rdDwoUk4ojY?t=42m2s
Another fantastic example of re-creation is the old math game “Green Globs” where students were presented with a set of points on a a graph, and tried to create equations to hit as many “globs” as possible with as few equations as possible.
To be successful you had to understand equations and their behaviour well enough to develop what you needed. Re-Creation, then seems to be that point where one has sufficient knowledge, experience and skill that it is possible to begin to develop some sophisticated heuristics about the topic at hand.
In learning, just as in games, as we develop more sophisticated heuristics and can start seeing what avenues will likely be fruitful, and which ones should be avoided – reaching the point of being able to not just recall, but re-create is a turning point where there are real rewards in learning – that sense of potential and creativity start to take off.
Remixing and beyond
Remixing occupies a really interesting place in the learning continuum. At it’s best, it seems to occur at an intersection of knowledge, expertise and heuristics – all scaffolded by the work(s) being remixed. It’s not not merely a space for non-experts, but it is definitely a great approach to continue to refine knowledge and heuristics as it allows an individual to focus on limited array of aspects of creation.
This could be anything from writing fan-fiction (where a writer uses existing worlds and characters and can therefore focus attention build skills in plotting, dialogue and descriptions) to musicians taking familiar song and extracting some new subtle layers from it, or even developers who fork code (having the foundational work in place allows clearer focus on very specific goals). Being able to focus on a limited number of details is very helpful while a person is still building schema and heuristics; it allows attention and effort to be spent efficiently where there are skills and knowledge to be developed.
As expertise grows, there is less need for the scaffolding aspect of Remixing, but it is still a useful tool. At a fundamental level, most research papers are an exercise in remixing – the author is distilling the essence of prior information, trying to build new connections, but not building the world from scratch. The level and quality of distillation will vary greatly with the expertise of users – in research, a new student might make simple connections, an seasoned researcher might create detailed and complex synthesis of information, but both would advance in their understanding from the exercise.*
Obviously remixing isn’t new, but the tools we have now make it much easier – allowing more time and attention on the content rather than the mechanics.** Regardless the subject area, remixes can be a place to develop choice bits from the foundational work, or find surprising new connections. They are a scaffolded starting point for either creation or refinement – both of which are potential fruitful spaces for learning.
To be useful, since remixing is about building connections, heuristics, schema… it has to be something organic. That doesn’t mean unstructured, but it does mean that if you weigh it down with too many rubrics the value will get lost in the box checking. The real beauty of remixing is that it both develops and demonstrates expertise and rigour. A good remix, like creation cannot be fudged from the sample problems or highlighted terms in a text book.
*thanks to Chris Atherton (@finiteattention) for suggesting this concept.
** I remember my brother and a friend doing remix “documentaries” for Literature class assignments – a tedious task involving a cassette recorder, hand written scripts, and albums on a turntable for soundclips. The scripts were somewhat MontyPython-esque, and the execution was incredibly laborious in those days. But I still recall more literary details from those than from any papers I read on the topics.