Developing Component Scores from Natural Language Processing Tools to Assess Human Ratings of Essay Quality

نویسندگان

  • Scott A. Crossley
  • Danielle S. McNamara
چکیده

This study explores correlations between human ratings of essay quality and component scores based on similar natural language processing indices and weighted through a principal component analysis. The results demonstrate that such component scores show small to large effects with human ratings and thus may be suitable to providing both summative and formative feedback in an automatic writing evaluation systems such as those found in Writing-Pal.

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تاریخ انتشار 2014