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Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2017
The current study examined the degree to which the quality and characteristics of students' essays could be modeled through dynamic natural language processing analyses. Undergraduate students (n = 131) wrote timed, persuasive essays in response to an argumentative writing prompt. Recurrent patterns of the words in the essays were then analyzed…
Descriptors: Writing Evaluation, Essays, Persuasive Discourse, Natural Language Processing
Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.; Guo, Liang; McNamara, Danielle S. – Grantee Submission, 2014
This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…
Descriptors: Computational Linguistics, Essays, Scoring, Writing Evaluation