Modeling Organization in Student Essays

Isaac Persing, Alan Davis, and Vincent Ng.
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 229-239, 2010.

Click here for the PostScript or PDF version. The talk slides are available here.

Abstract

Automated essay scoring is one of the most important educational applications of natural language processing. Recently, researchers have begun exploring methods of scoring essays with respect to particular dimensions of quality such as coherence, technical errors, and relevance to prompt, but there is relatively little work on modeling organization. We present a new annotated corpus and propose heuristic-based and learning-based approaches to scoring essays along the organization dimension, utilizing techniques that involve sequence alignment, alignment kernels, and string kernels.

Dataset

The human annotation used in this paper is available from this page.

BibTeX entry

@InProceedings{Persing+Davis+Ng:10a,
  author = {Isaac Persing and Alan Davis and Vincent Ng},
  title = {Modeling Organization in Student Essays},
  booktitle = {Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing},
  pages = {229--239},
  year = 2010
}