Linking Processing Speed And White Matter: a bridge between Education and Neuroscience research

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Abstract/Contents

Abstract
In the first chapter of this thesis, I review the history of processing speed as a cognitive capacity since the late 19th century. In the second chapter of this thesis, I analyze the definitional and conceptual constraints surrounding the use of ‘processing speed’ in the behavioral psychology literature. Specifically, I evaluate the degree of diversity observed in operationalized definitions of processing speed advanced in recent literature, and then present three ways to reduce this diversity in order to unify scholarly conceptualizations of processing speed in the future. In the third chapter of this thesis, I assess a candidate for an anatomical/mechanistic grounding for characterizations of processing speed as a cognitive capacity. In the final chapter of this thesis, I summarize arguments presented in chapters two and three and discuss implications for future research, as well as the importance of the research paradigm more broadly.

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Type of resource text
Date created [ca. June 4, 2021]

Creators/Contributors

Author Shacklette, David William

Subjects

Subject Processing Speed
Subject White Matter
Subject Educational Neuroscience
Subject Stanford
Subject School of Humanities and Sciences
Subject Symbolic Systems
Genre Thesis

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User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
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This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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Preferred Citation
Shacklette, David William. (2021). Linking Processing Speed And White Matter: a bridge between Education and Neuroscience research. Stanford Digital Repository. Available at: https://purl.stanford.edu/yq219dn0952

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Master's Theses, Symbolic Systems Program, Stanford University

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