The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring

Shelby J. Haberman and Sandip Sinharay
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Shelby J. Haberman: Educational Testing Service
Sandip Sinharay: Educational Testing Service

Journal of Educational and Behavioral Statistics, 2010, vol. 35, issue 5, 586-602

Abstract: Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear regression model to automated essay scoring. Comparison of the performances of the linear regression model and the cumulative logit model was performed on a large variety of data sets. It appears that the cumulative logit model performed somewhat better than did the linear regression model.

Keywords: deleted residual; cross-validation; PRESS; regression (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:35:y:2010:i:5:p:586-602

DOI: 10.3102/1076998610375839

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