Toward Automated Multi-trait Scoring of Essays: Investigating Links among Holistic, Analytic, and Text Feature Scores

• Yong-Won Lee ^[1] ; Claudia Gentile ^[1] ; Robert Kantor ^[1]
  1. [1] Seoul National University

     Seoul National University

     Corea del Sur

     
• Localización: Applied linguistics, ISSN 0142-6001, Vol. 31, Nº 3, 2010, págs. 391-417
• Idioma: inglés
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• Resumen

  • The main purpose of the study was to investigate the distinctness and reliability of analytic (or multi-trait) rating dimensions and their relationships to holistic scores and e-rater® essay feature variables in the context of the TOEFL® computer-based test (TOEFL CBT) writing assessment. Data analyzed in the study were holistic and multi-trait essay scores provided by human raters and essay feature variable scores computed by e-rater® (version 2.0) for two TOEFL CBT writing prompts. It was found that (i) all of the six multi-trait scores were not only correlated among themselves but also correlated with the holistic score, (ii) high correlations obtained among holistic and multi-trait scores were largely attributable to the impact of essay length on both holistic and multi-trait scoring, and (iii) some strong associations were confirmed between several e-rater variables and multi-trait rating dimensions. Implications are discussed for improving the multi-trait scoring of essays, refining e-rater essay feature variables, and validating automated essay scores.