Abstract
This study assesses the potential for computational indices to predict human ratings of essay quality. The results demonstrate that linguistic indices related to type counts, given/new information, personal pronouns, word frequency, conclusion n-grams, and verb forms predict 43% of the variance in human scores of essay quality.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Abbott, R., Berninger, V., Fayol, M.: Longitudinal relationships of levels of language in writing and between writing and reading in grades 1 to 7. Journal of Educational Psychology 102, 281–298 (2002)
Berninger, V., Mizoka, D., Bragg, R.: Theory-based diagnosis and remediation of writing disabilities. Journal of School Psychology 29, 57–79 (1991)
McNamara, D.S., Crossley, S.A., McCarthy, P.M.: Linguistic features of writing quality. Written Communication 27, 57–86 (2010)
Graesser, A.C., McNamara, D.S., Louwerse, M.M., Cai, Z.: Coh-Metrix: Analysis of text on cohesion and language. Behavioral Research Methods, Instruments, and Computers 36, 193–202 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Crossley, S.A., Roscoe, R., McNamara, D.S. (2011). Predicting Human Scores of Essay Quality Using Computational Indices of Linguistic and Textual Features. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_62
Download citation
DOI: https://doi.org/10.1007/978-3-642-21869-9_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21868-2
Online ISBN: 978-3-642-21869-9
eBook Packages: Computer ScienceComputer Science (R0)