Correction Detection and Error Type Selection as an ESL Educational Aid
CitationSwanson, Ben and Elif Yamangil. 2012. Correction Detection and Error Type Selection as an ESL Educational Aid. In Proceedings North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Montreal, Canada, June 3-8, 2012. Association for Computational Linguistics. 357-361.
AbstractWe present a classifier that discriminates between types of corrections made by teachers of English in student essays. We define a set of linguistically motivated feature templates for a log-linear classification model, train this classifier on sentence pairs extracted from the Cambridge Learner Corpus, and achieve 89% accuracy improving upon a 33% baseline. Furthermore, we incorporate our classifier into a novel application that takes as input a set of corrected essays that have been sentence aligned with their originals and outputs the individual corrections classified by error type. We report the F-Score of our implementation on this task.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12305804
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