Integration in Multiple-Document Comprehension: A Natural Language Processing Approach

Allison N. Sonia; Joseph P. Magliano; Kathryn S. McCarthy; Sarah D. Creer; Danielle S. McNamara; Laura, K. Allen

doi:10.1080/0163853X.2022.2079320

Integration in Multiple-Document Comprehension: A Natural Language Processing Approach

Allison N. Sonia, Joseph P. Magliano, Kathryn S. McCarthy, Sarah D. Creer, Danielle S. McNamara, Laura, K. Allen

Psychology

Research output: Contribution to journal › Article › peer-review

Abstract

The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think aloud, self-explain, or evaluate the sources while reading and then write an integrated essay based on their reading. Natural Language Processing techniques were used to analyze the cohesion of the constructed responses at both within- and across-text levels. Both within- and across-text cohesion indices were positively related to essay quality; however, across-text cohesion indices exhibited stronger effects. Overall, this study provides evidence that the cohesion of constructed responses can serve as a proxy of the coherence of the mental representations that readers construct during multiple document processing.

Original language	English (US)
Pages (from-to)	417-438
Number of pages	22
Journal	Discourse Processes
Volume	59
Issue number	5-6
DOIs	https://doi.org/10.1080/0163853X.2022.2079320
State	Published - 2022

ASJC Scopus subject areas

Communication
Language and Linguistics
Linguistics and Language

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10.1080/0163853X.2022.2079320

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title = "Integration in Multiple-Document Comprehension: A Natural Language Processing Approach",

abstract = "The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think aloud, self-explain, or evaluate the sources while reading and then write an integrated essay based on their reading. Natural Language Processing techniques were used to analyze the cohesion of the constructed responses at both within- and across-text levels. Both within- and across-text cohesion indices were positively related to essay quality; however, across-text cohesion indices exhibited stronger effects. Overall, this study provides evidence that the cohesion of constructed responses can serve as a proxy of the coherence of the mental representations that readers construct during multiple document processing.",

author = "Sonia, {Allison N.} and Magliano, {Joseph P.} and McCarthy, {Kathryn S.} and Creer, {Sarah D.} and McNamara, {Danielle S.} and Allen, {Laura, K.}",

note = "Funding Information: This research was supported in part by IES Grants R305A180261, R305A180144, and R305A190063 as well as the Office of Naval Research (Grants: N00014-19-1-2424 and N00014-20-1-2627). Opinions, conclusions, or recommendations do not necessarily reflect the view of the Department of Education, IES, or the Office of Naval Research. Publisher Copyright: {\textcopyright} 2022 Taylor & Francis Group, LLC.",

year = "2022",

doi = "10.1080/0163853X.2022.2079320",

language = "English (US)",

volume = "59",

pages = "417--438",

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AU - Sonia, Allison N.

AU - Magliano, Joseph P.

AU - McCarthy, Kathryn S.

AU - Creer, Sarah D.

AU - McNamara, Danielle S.

AU - Allen, Laura, K.

N1 - Funding Information: This research was supported in part by IES Grants R305A180261, R305A180144, and R305A190063 as well as the Office of Naval Research (Grants: N00014-19-1-2424 and N00014-20-1-2627). Opinions, conclusions, or recommendations do not necessarily reflect the view of the Department of Education, IES, or the Office of Naval Research. Publisher Copyright: © 2022 Taylor & Francis Group, LLC.

PY - 2022

Y1 - 2022

N2 - The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think aloud, self-explain, or evaluate the sources while reading and then write an integrated essay based on their reading. Natural Language Processing techniques were used to analyze the cohesion of the constructed responses at both within- and across-text levels. Both within- and across-text cohesion indices were positively related to essay quality; however, across-text cohesion indices exhibited stronger effects. Overall, this study provides evidence that the cohesion of constructed responses can serve as a proxy of the coherence of the mental representations that readers construct during multiple document processing.

AB - The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think aloud, self-explain, or evaluate the sources while reading and then write an integrated essay based on their reading. Natural Language Processing techniques were used to analyze the cohesion of the constructed responses at both within- and across-text levels. Both within- and across-text cohesion indices were positively related to essay quality; however, across-text cohesion indices exhibited stronger effects. Overall, this study provides evidence that the cohesion of constructed responses can serve as a proxy of the coherence of the mental representations that readers construct during multiple document processing.

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Integration in Multiple-Document Comprehension: A Natural Language Processing Approach

Abstract

ASJC Scopus subject areas

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