Computationally assessing expert judgments of freewriting quality

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

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This study examines the relationship between the linguistic features of freewrites and human assessments of freewrite quality. Freewriting is a prewriting strategy that has received little experimental attention, particularly in terms of linguistic differences between high and low quality freewrites. This study builds upon the authors' previous study, in which linguistic features of freewrites written by 9th and 11th grade students were included in a model of the freewrites' quality (Weston, Crossley, & McNamara; 2010). The current study reexamines this model using a larger data set of freewrites. The results show that similar linguistic features reported in the Weston et al. model positively correlate with expert ratings in the new data set. Significant predictors in the current model of freewrite quality were total number of words and stem overlap. In addition, analyses suggest that 11th graders, as compared to 9th graders, wrote higher quality and longer freewrites. Overall, the results of this study support the conclusion that better freewrites are longer and more cohesive than poor freewrites.

Original languageEnglish (US)
Title of host publicationApplied Natural Language Processing
Subtitle of host publicationIdentification, Investigation and Resolution
PublisherIGI Global
Pages364-381
Number of pages18
ISBN (Print)9781609607418
DOIs
StatePublished - Dec 1 2011

ASJC Scopus subject areas

  • Computer Science(all)

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