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According to William K. Estes Model of Learning, what role

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According to William K. Estes’ Model of Learning, what role does reinforcement play in learning? Can you provide a definition and example of this Model of Learning? Thanks.

Hi again! I'd like to help you with your question.

 

William Estes was a student of B.F. Skinner and like many students, took his teacher's viewpoints to an extreme. Estes is best known for groundbreaking mathematical formulas within learning theory...which are now used as a foundational basis for how we program psychological artificial reasoning and intelligence. He went beyond reinforcement, attempting to define the level and process involved in learning. Simply said, he wanted learning to be an exact formula that could be defined and measured.

 

The basic premise of his theory is that learning is not defined to simply instincts or maturation but as a direct result of behavioral change due to interactions within an environment of reinforcement. It is rather not a single theory but an integrated view of how human beings learn and process information. Estes believed that within operant conditioning, operant behaviors are strengthened by positive reinforcement and discouraged by negative reinforcement much as Skinner, But:

 

As a result of the very processed oriented view of Estes, the system is very empirical analytic and very machine like. Simply, the view is that information in the form of reinforcement is provided and certain expected responses result. Less than desirable responses can be almost mathematically interpreted and adjusted for during the learning process. (unlike other similar theories)

 

Estes work in learning is highly systematic and learning results can be expected in certain ratios and responses.

 

For example, to learn how to drive a stick shift car, Estes would first determine the intelligence and motivation of his subjects and design a system that established reinforcers for every desired behavior of the group and the expected shaping interventions... as the behaviors came close to the target outcome he would track the type and kind of reinforcement that was needed and adjust accordingly.

 

The subjects of our "learn to drive" experiment would be naturally shaped by the car's responses to their actions on the clutch and gear shift. If they remained motivated through desire and studiousness, their behavior would be shaped faster as the car moved more smoothly as their level of skill increased.

 

Basically, he is about as formula oriented as you can go behaviorally speaking. On his theory, learning in both the classroom and in life can be prepared and expected to a mathematically exacting level. As a result, his theory has an interesting place with difficult to train or teach groups, but it is especially useful for those who program machines to appear to be able to learn. "Fuzzy Logic" the newest artificial intelligence process, is highly based on Estes mathematical views of the reinforcement learning process.

 

I hope this has helped you,
Kate

 

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