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A Model of Learning Task-specific Knowledge for a new Task
Abstract
In this paper I will present a detailed ACT-R model of how the task-specific knowledge for a new. complex task is learned. The model is capable of acquiring its knowledge through experience, using a declarative representation that is gradually compiled into a procedural representation. The model exhibits several characteristics that concur with Fitts' and Anderson's theories of skill learning, and can be used to show that individual differences in working-memory capacity initially have a large impact on performance, but that this impact diminished after sufficient experience, which is consistent with Ackermans's theory of skill learning. Some preliminary experimental data support these findings.
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