Predicting Human Scores of Essay Quality Using Computational Indices of Linguistic and Textual Features
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.
KeywordsTextual Feature Word Frequency Personal Pronoun Linguistic Feature Intelligent Tutoring System
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