Number of words versus number of ideas: Finding a better predictor of writing quality

Jennifer L. Weston, Scott A. Crossley, Philip M. McCarthy, Danielle S. McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This study examines the relation between the linguistic features of freewrites and human assessments of freewriting quality. This study builds upon the authors' previous studies in which a model was developed based on the linguistic features of freewrites written by 9th and 11th grade students to predict freewrite quality. The current study reexamines this model using number of propositions as a predictor instead of number of words because the number of propositions was expected to be a better proxy for number of ideas in contrast to simple text length. The results indicated that there were only slight advantages for using a measure for number of propositions, indicating that from an artificial intelligence perspective, the number of words was the better measure.

Original languageEnglish (US)
Title of host publicationProceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24
Pages335-340
Number of pages6
StatePublished - Sep 9 2011
Externally publishedYes
Event24th International Florida Artificial Intelligence Research Society, FLAIRS - 24 - Palm Beach, FL, United States
Duration: May 18 2011May 20 2011

Publication series

NameProceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24

Other

Other24th International Florida Artificial Intelligence Research Society, FLAIRS - 24
CountryUnited States
CityPalm Beach, FL
Period5/18/115/20/11

ASJC Scopus subject areas

  • Artificial Intelligence

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