Modeling Organization in Student Essays
نویسندگان
چکیده
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.
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