I find Karl Kapp reflecting most of my own views about behaviorism and cognitivism, and while Bill Kerr seems somewhat counterposed, possibly just for the sake of discussion, to his views, I like Kerr's analysis of the "state of the art" in learning theory as well as what he seems to view as a goal for such theories. One thing I find error with in Kerr's posts is the analogy of the "computer chess player" as a better system for, say, handling nuclear meltdown emergencies. It's not the machine, albeit it could be in some far away time or distant galaxy, that does the chess playing. It's a list of many previous games to check moves against that is denied the human opponent. If the human opponent had the same "mechanical help", it wouldn't be allowed for his "looking at the answers" or some such rationale. In fact, the machine doesn't really play the game at all, it just selects from a large program of previously played games. Our human could do that as well. The purpose of chess is to outwit an opponent. One opponent in a timed contest. Here, one human faces a pre-programmed catalog of games that took many - probably, hundreds of hours to prepare. That's not fair. And how could you program a computer for an unforseen, unexpected emergency!?
The protest here is not really that specifically, it's about comparing a human mind to a machine and defining it with finite bounds, an entity that could very well be limitless in capacity or any other value we place on minds. Then applying such a definition to learning theory.
I, for one, believe the human mind is infinite in its capacity to store information and as fast in processing information as we would have it be. I believe our minds are entirely of our own construction, albeit inherited, possibly, in some fashion by an originator far removed from us today in time. We assume something or have a consideration about something and so it is, even the make up of our very minds. I also believe, then, that learning depends very much, therefore, on how we choose to view things, our individual experiences, our talents and goals, for example. I also believe that considering our minds to occupy our brains might produce severe headaches!
Still, I think that there are similarities between people bearing on how we learn, and though the potentials might be limitless the practicalities seem to be emerging in the form of workable technologies in today's journals and discussions among educators.
http://billkerr2.blogspot.com/2007/01/isms-as-filter-not-blinker.html
http://karlkapp.blogspot.com/2007/01/out-and-about-discussion-on-educational.html
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Bill,
ReplyDeleteI agree with Kapp and Kerr in that no single learning theory or model can guide learning single-handedly. Kapp stated that learning is too "multi-faceted" and Kerr stated that each "ism is offering something useful". I agree with both of them.
Neena
Bill,
ReplyDeleteYou brought out some great points. I agree that every person's ability to learn is endless. I always got fustrated with these big 8th graders that can not read. When the fact is their lack of ability to read was not because the couldn't but because noone has taught them. If someone did whatever it took to teach that child to read, then they can learn to read.
I agree with what you said about putting your mind to something and making it happen. We have to teach our students about the importance of goal setting. That alone can be a motivation to continue and grow.
LaToya
As I read your post, my mind instantly made another connection to your nuclear plant analogy. I believe we can't program a machine to handle an unexpected emergency, just as we can't assume that all learners learn in the same way. When I was going through college for my bachlors in education, I was amazed at the number of senerio I had to read about what the teacher would say, and how the student would reply. Guess what happened when I first got into the classroom. The students hadn't read the script, and they weren't giving me the answers I was suppose to be getting. I was completely unprepared. With experience, I learned to differenciate my instruction to meet the needs of many learning styles.
ReplyDeleteBill,
ReplyDeleteSo you are saying that a machine cannot be programmed to account for every disaster, but machines learn from the master machine...the human brain.
We have artificial intelligence machines and neural networks that mimic the function of the human brain to solve problems, but both require input, guidance and programming from a human in order to function more efficiently.
The way that we make the machine smarter is humans have to account collectively for as many possible occurrences as we can fathom. The more people that add to the collective body of knowledge the better.
The same can be said for instruction for younger students. It takes many of the older humans and some younger ones to look beyond their own thinking to account for the infinite possibilities of learning. Just as a neural network uses the power of nodes to solve problems we have to do the same to expand and perfect learning.
The only limit to the solutions as we have seen for so many decades now is humans themselves.
DJH