Towards a computational assessment of freewriting quality

Jennifer L. Weston, Scott A. Crossley, Danielle S. McNamara

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

10 Scopus citations

Abstract

This study examines the linguistic features of freewrites and how those features relate to human scores of freewrite quality. Freewriting is a common prewriting strategy that has received little attention by researchers, particularly in terms of the linguistic features of good and poor freewrites. To address this issue, we developed a scoring rubric to assess the qualities of freewrites and how they are correlated with linguistic features. The results showed that many linguistic features positively correlated with human scores (e.g., referential cohesion, syntactic complexity, lexical difficulty), but the only significant predictors in a regression analysis were, number of words and noun overlap. Better freewrites are longer ones with lexical overlap between sentences. While these results fail to conclusively exclude other potentially important features of higher quality freewrites, this study is a first step toward computationally defining freewrite quality.

Original languageEnglish (US)
Title of host publicationProceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23
Pages283-288
Number of pages6
StatePublished - 2010
Externally publishedYes
Event23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23 - Daytona Beach, FL, United States
Duration: May 19 2010May 21 2010

Publication series

NameProceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23

Other

Other23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23
Country/TerritoryUnited States
CityDaytona Beach, FL
Period5/19/105/21/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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