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

Authors: 

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

Paper type: 
Poster

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.