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Crossley, 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
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Crossley, Scott A.; Salsbury, Tom; McNamara, Danielle S. – Language Testing, 2012
This study explores how second language (L2) texts written by learners at various proficiency levels can be classified using computational indices that characterize lexical competence. For this study, 100 writing samples taken from 100 L2 learners were analyzed using lexical indices reported by the computational tool Coh-Metrix. The L2 writing…
Descriptors: Semantics, Familiarity, Discriminant Analysis, Vocabulary Development
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Crossley, Scott A.; McNamara, Danielle S. – Journal of Second Language Writing, 2009
The purpose of this paper is to provide a detailed analysis of how lexical differences related to cohesion and connectionist models can distinguish first language (L1) writers of English from second language (L2) writers of English. Key to this analysis is the use of the computational tool Coh-Metrix, which measures cohesion and text difficulty at…
Descriptors: Second Language Learning, Discriminant Analysis, English (Second Language), Educational Technology