Automated assessment of paragraph quality: Introduction, body, and conclusion paragraphs

Rod D. Roscoe, Scott A. Crossley, Jennifer L. Weston, Danielle S. McNamara

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

6 Scopus citations

Abstract

Natural language processing and statistical methods were used to identify linguistic features associated with the quality of student-generated paragraphs. Linguistic features were assessed using Coh-Metrix. The resulting computational models demonstrated small to medium effect sizes for predicting paragraph quality: introduction quality r2 = .25, body quality r2 = .10, and conclusion quality r2 = .11. Although the variance explained was somewhat low, the linguistic features identified were consistent with the rhetorical goals of paragraph types. Avenues for bolstering this approach by considering individual writing styles and techniques are considered.

Original languageEnglish (US)
Title of host publicationProceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24
Pages281-286
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

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ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Roscoe, R. D., Crossley, S. A., Weston, J. L., & McNamara, D. S. (2011). Automated assessment of paragraph quality: Introduction, body, and conclusion paragraphs. In Proceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24 (pp. 281-286). (Proceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24).