That brings up several questions I would like to answer. Maybe I'll be right, or at least close. Mostly the questions are about the differences and practical usage of learning how you learn vs the generally considered intangible metacognition.
What is it?
"The idea of metalearning was originally used by John Biggs (1985) to describe the state of ‘being aware of and taking control of one’s own learning’." - http://en.wikipedia.org/wiki/Meta_learning
This is pretty close to what I mean. Taking control of your learning is done after you observe and learn about your learning. This is something that we don't really take into account when it comes to designing education, but I've seen it in games.
When playing a game, players will commonly try several different paths to improve their skill and observe the results. From there they apply the knowledge gained. When one doesn't work, another is tried.
I think taking control of one's learning is a matter of being empowered to do so. Being aware of your learning helps you know what should be done. Having the tools, resources, opportunities and/or resourcefulness makes it possible to to implement that knowledge.
What's the point?
"A student who has a high level of metalearning awareness is able to assess the effectiveness of her/his learning approach and regulate it according to the demands of the learning task. Conversely, a student who is low in metalearning awareness will not be able to reflect on her/his learning approach or the nature of the learning task set. In consequence, s/he will be unable to adapt successfully when studying becomes more difficult and demanding." - http://en.wikipedia.org/wiki/Meta_learning
It's obvious how knowing what works best can help improve results. Each person has their own sets of patterns that kick in while learning. For instance I'm one who sometimes needs an increase in difficulty rather than a decrease to get desired results. Knowing this I know that I should try pushing myself harder sometimes to improve myself. I also know that I do better with a lot of information, such as all the rules to a game before playing. With that information I can identify opportunities and resources that would normally work well for me. That however is only part of the point.
The other piece is that the number of students scales perfectly with the number of students. That means that is the students are able to identify good resources for them out of approved resources can help teachers and educational institutions.
How's it tangible?
Like other behavior patterns, data analysis usually helps. With a set of resources, learning paths and approaches that are known you can identify patterns based on results and reactions.
Take algebra and geometry for example. Generally most people are one of three types of people. Algebra people do better with equations, numbers and graphs. Geometry people do better with shapes. Some people deal with both equally well, to the point that some see them as the same thing expressed in different ways.
Which approach a person has is usually easy to figure out. Give them a math problem in both geometry and algebra style and ask which they prefer. Equations, shapes or neither/both tells you which type they are for that problem. Do it for a few different types of math problems and you can build a profile for how they currently prefer to handle those kinds of math problems.
How's it done?
It could be done in a test format, but I think there is a better way to do this. A learning profile that has the information that a test might give over time, because it changes with what you know. That would give a better picture of the learner's learning preferences.
Data analysis is fairly standard for profiling. This kind of profiling could be done based on several types of measurements. Raw results is one possibility, but hard to keep the variables under control. Reactions to resources and paths that are tagged for the style could be compiled and analyzed. Tests could be done and added to the mix, but they should be considered indicators rather than definitive evaluations.
With this kind of approach it should be noted that the results of tests and analysis HAS to be verified with the reality of the person's learning. That's why it's an indicator rather than a diagnosis. It could be right, close or totally off. If the learner says it's totally wrong, more needs to be done to verify and analyze the learning preferences. It's and indicator, a general guide.
Where could this lead?
Each individual could adapt their resource selections based on the results. As stated before, this could help people become more informed users.
Teachers could use it for each of their classes. One thing I've read a few times is how the curriculum standards make it so every class, every student is handle in much the same way. Using the learning profiles of the students could help teachers adapt the curriculum to their classes and help each student.
Resource providers and creators can learn from mass data to see which styles, paths and approaches could use more and/or better resources.
Hmmm... sounds like what should have been the case all along. Makes me think of the old assumption problem. Because it is assumed that everybody knows about the assumption and will follow it, it's neither discussed not remembered. Once forgotten it becomes missing and the system has problems.
What about Games?
Better resources is a logical build out. With a better understanding of how people learn there will be people making better resources for gamers and game creators alike.
Better game designs is always possible. With the common ways people learn nicely understood and plenty of examples to copy ... er, learn from, several types of game mechanics could be improved and expanded. In game resources and skill improvement methods makes a good place to start, but is nowhere near the limit.
Have fun, spread the word and tell me what you think,
Igen Oukan
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