
Contents
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Knowledge and Error in Skill Practice Knowledge and Error in Skill Practice
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A Model of Constraint-Based Learning A Model of Constraint-Based Learning
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Representing Declarative Knowledge as Constraints Representing Declarative Knowledge as Constraints
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Constraint-Based Error Detection Constraint-Based Error Detection
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Constraint-Based Learning Constraint-Based Learning
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Revisions for Type A Violations Revisions for Type A Violations
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Rule Revisions for Type B Violations Rule Revisions for Type B Violations
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Discussion Discussion
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Ordering Effects in Constraint-Based Learning Ordering Effects in Constraint-Based Learning
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Simulation Experiments Simulation Experiments
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Transfer Effects Transfer Effects
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Ordering Effects Ordering Effects
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Relationship between Transfer and Ordering Effects Relationship between Transfer and Ordering Effects
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Discussion Discussion
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Acknowledgments Acknowledgments
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References References
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11 The Effects of Order: A Constraint-Based Explanation
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Published:August 2007
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Abstract
This chapter presents a computational model that shows how information migrates from declarative to procedural knowledge and provides a powerful new learning mechanism for machine-learning algorithms. The model is used to examine the effects of learning three different counting tasks. The model predicts order effects that vary in several dimensions, including the number of times the model has to revise its knowledge and how long it will take to learn. Although some of these effects are quite large within a subtask, the overall effect is muted by other aspects of the task, including interaction. This model suggests that the complexity of a task's constraints is important for computing transfer between similar tasks. The model's behavior has been compared to human performance, and a general summary is provided.
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