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Narratives, Networks, and Nuance: Ex...

Leachman, Molly Ann,

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Narratives, Networks, and Nuance: Exploring Text Comprehension Measurement Through Scoring Approaches, Machine Learning, and Meta-Analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Narratives, Networks, and Nuance: Exploring Text Comprehension Measurement Through Scoring Approaches, Machine Learning, and Meta-Analysis // Molly Ann Leachman.
Author:	Leachman, Molly Ann,
Description:	1 electronic resource (197 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 87-01, Section: B.
Contained By:	Dissertations Abstracts International87-01B.
Subject:	Early childhood education. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32047364
ISBN:	9798288802782

Narratives, Networks, and Nuance: Exploring Text Comprehension Measurement Through Scoring Approaches, Machine Learning, and Meta-Analysis /
Leachman, Molly Ann,

Narratives, Networks, and Nuance: Exploring Text Comprehension Measurement Through Scoring Approaches, Machine Learning, and Meta-Analysis /Molly Ann Leachman. - 1 electronic resource (197 pages)

Source: Dissertations Abstracts International, Volume: 87-01, Section: B.

This dissertation explores text comprehension through three distinct yet interrelated studies, each contributing to the understanding of text comprehension development and differences across measurement techniques. The first study investigates the relationship between three prevalent scoring methods for oral narrative retell assessments, analyzing their connection to underlying linguistic and cognitive constructs. Through exploring how different scoring techniques can capture diverse facets of language processing, we aim to clarify the importance of intentionality in educational and clinical practices. As the educational field continues to embrace technological advancements, the second study aims to employ modern-day natural language processing (NLP) approaches to automate rubric-based scoring of oral narrative retell assessments for Grade 2 students to enhance the efficiency and scalability of scoring, while maintaining consistency and objectivity across diverse educational settings. The third and final study extends the examination of comprehension skills into reading through a meta-analysis that explores the relationship between text reading fluency and reading comprehension. Through this large-scale meta-analysis, we explore how developmental stages, orthographic depth, and assessment task types influence the magnitude of this relation, providing a comprehensive view of the factors that impact the relation between the two key skills. All together, these studies underscore the necessity of precise and effective measurement tools when observing text comprehension.

English

ISBN: 9798288802782Subjects--Topical Terms:

518817
Early childhood education.
Subjects--Index Terms:

Assessment

Narratives, Networks, and Nuance: Exploring Text Comprehension Measurement Through Scoring Approaches, Machine Learning, and Meta-Analysis /
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520 $a This dissertation explores text comprehension through three distinct yet interrelated studies, each contributing to the understanding of text comprehension development and differences across measurement techniques. The first study investigates the relationship between three prevalent scoring methods for oral narrative retell assessments, analyzing their connection to underlying linguistic and cognitive constructs. Through exploring how different scoring techniques can capture diverse facets of language processing, we aim to clarify the importance of intentionality in educational and clinical practices. As the educational field continues to embrace technological advancements, the second study aims to employ modern-day natural language processing (NLP) approaches to automate rubric-based scoring of oral narrative retell assessments for Grade 2 students to enhance the efficiency and scalability of scoring, while maintaining consistency and objectivity across diverse educational settings. The third and final study extends the examination of comprehension skills into reading through a meta-analysis that explores the relationship between text reading fluency and reading comprehension. Through this large-scale meta-analysis, we explore how developmental stages, orthographic depth, and assessment task types influence the magnitude of this relation, providing a comprehensive view of the factors that impact the relation between the two key skills. All together, these studies underscore the necessity of precise and effective measurement tools when observing text comprehension.
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