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

Author

Listed:
  • Shelby J. Haberman

    (Educational Testing Service)

  • Sandip Sinharay

    (Educational Testing Service)

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.

Suggested Citation

  • Shelby J. Haberman & Sandip Sinharay, 2010. "The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring," Journal of Educational and Behavioral Statistics, , vol. 35(5), pages 586-602, October.
    • Handle: RePEc:sae:jedbes:v:35:y:2010:i:5:p:586-602
    DOI: 10.3102/1076998610375839
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    Cited by:

    1. Lili Yao & Shelby J. Haberman & Mo Zhang, 2019. "Penalized Best Linear Prediction of True Test Scores," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 186-211, March.

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