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Peer reviewed
Direct linkCrossley, Scott A.; Roscoe, Rod; McNamara, Danielle S. – Written Communication, 2014
This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one…
Descriptors: Essays, Natural Language Processing, Computational Linguistics, Multivariate Analysis
Crossley, Scott A.; Weston, Jennifer L.; McLain Sullivan, Susan T.; McNamara, Danielle S. – Written Communication, 2011
In this study, a corpus of essays stratified by level (9th grade, 11th grade, and college freshman) are analyzed computationally to discriminate differences between the linguistic features produced in essays by adolescents and young adults. The automated tool Coh-Metrix is used to examine to what degree essays written at various grade levels can…
Descriptors: Writing (Composition), Sentence Structure, Nouns, Linguistics
McNamara, Danielle S.; Crossley, Scott A.; McCarthy, Philip M. – Written Communication, 2010
In this study, a corpus of expert-graded essays, based on a standardized scoring rubric, is computationally evaluated so as to distinguish the differences between those essays that were rated as high and those rated as low. The automated tool, Coh-Metrix, is used to examine the degree to which high- and low-proficiency essays can be predicted by…
Descriptors: Essays, Undergraduate Students, Educational Quality, Computational Linguistics
