Syntagmatic, paradigmatic, and automatic N-gram approaches to assessing essay quality

Scott A. Crossley, Zhiqiang Cai, Danielle McNamara

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

16 Scopus citations

Abstract

Computational indices related to n-gram production were developed in order to assess the potential for n-gram indices to predict human scores of essay quality. A regression analyses was conducted on a corpus of 313 argumentative essays. The analyses demonstrated that a variety of n-gram indices were highly correlated to essay quality, but were also highly correlated to the number of words in the text (although many of the n-gram indices were stronger predictors of writing quality than the number of words in a text). A second regression analysis was conducted on a corpus of 88 argumentative essays that were controlled for text length differences. This analysis demonstrated that n-gram indices were still strong predictors of essay quality when text length was not a factor.

Original languageEnglish (US)
Title of host publicationProceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25
Pages214-219
Number of pages6
StatePublished - Aug 20 2012
Event25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25 - Marco Island, FL, United States
Duration: May 23 2012May 25 2012

Publication series

NameProceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

Other

Other25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25
CountryUnited States
CityMarco Island, FL
Period5/23/125/25/12

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Crossley, S. A., Cai, Z., & McNamara, D. (2012). Syntagmatic, paradigmatic, and automatic N-gram approaches to assessing essay quality. In Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25 (pp. 214-219). (Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25).