Coherence-Building in Multiple Document Comprehension

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

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

The current study examined the extent to which the cohesion detected in readers’ constructed responses to multiple documents was predictive of persuasive, source-based essay quality. Participants (N=95) completed multiple-documents reading tasks wherein they were prompted to think-aloud, self-explain, or evaluate the sources while reading a set of four texts. They were then asked to write a source-based essay based on their reading. Natural Language Processing techniques were used to automatically analyze the cohesion of the constructed responses at both within- and across-documents levels. Results indicated that within-document cohesion was negatively related to essay quality, whereas across-documents cohesion was positively related to essay quality. Further, these relations differed by instructional condition such that strategic instructions to either self-explain or evaluate sources seemed to promote across-text integration, compared to thinking aloud. Overall, this study indicates that the cohesion of constructed responses to text can provide insights into the coherence of the mental representations readers construct while reading multiple documents.

Original languageEnglish (US)
Pages931-937
Number of pages7
StatePublished - 2021
Externally publishedYes
Event43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021 - Virtual, Online, Austria
Duration: Jul 26 2021Jul 29 2021

Conference

Conference43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021
Country/TerritoryAustria
CityVirtual, Online
Period7/26/217/29/21

Keywords

  • cohesion
  • comprehension
  • natural language processing
  • writing

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

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