TY - GEN
T1 - Paragraph specific n-gram approaches to automatically assessing essay quality
AU - Crossley, Scott
AU - DeFore, Caleb
AU - Kyle, Kris
AU - Dai, Jianmin
AU - McNamara, Danielle S.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - In this paper, we describe an n-gram approach to automatically assess essay quality in student writing. Underlying this approach is the development of n-gram indices that examine rhetorical, syntactic, grammatical, and cohesion features of paragraph types (introduction, body, and conclusion paragraphs) and entire essays. For this study, we developed over 300 n-gram indices and assessed their potential to predict human ratings of essay quality. A combination of these n-gram indices explained over 30% of the variance in human ratings for essays in a training and testing corpus. The findings from this study indicate the strength of using n-gram indices to automatically assess writing quality. Such indices not only explain text-based factors that influence human judgments of essay quality, but also provide new methods for automatically assessing writing quality.
AB - In this paper, we describe an n-gram approach to automatically assess essay quality in student writing. Underlying this approach is the development of n-gram indices that examine rhetorical, syntactic, grammatical, and cohesion features of paragraph types (introduction, body, and conclusion paragraphs) and entire essays. For this study, we developed over 300 n-gram indices and assessed their potential to predict human ratings of essay quality. A combination of these n-gram indices explained over 30% of the variance in human ratings for essays in a training and testing corpus. The findings from this study indicate the strength of using n-gram indices to automatically assess writing quality. Such indices not only explain text-based factors that influence human judgments of essay quality, but also provide new methods for automatically assessing writing quality.
UR - http://www.scopus.com/inward/record.url?scp=84911912617&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911912617&partnerID=8YFLogxK
M3 - Conference contribution
T3 - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
BT - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
A2 - D'Mello, Sidney K.
A2 - Calvo, Rafael A.
A2 - Olney, Andrew
PB - International Educational Data Mining Society
T2 - 6th International Conference on Educational Data Mining, EDM 2013
Y2 - 6 July 2013 through 9 July 2013
ER -