Predicting human scores of essay quality using computational indices of linguistic and textual features


Scott A. Crossley, Rod Roscoe and Danielle S. McNamara

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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.