Xiong, W and Litman, D
(2010)
Identifying problem localization in peer-review feedback.
In: UNSPECIFIED.
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Abstract
In this paper, we use supervised machine learning to automatically identify the problem localization of peer-review feedback. Using five features extracted via Natural Language Processing techniques, the learned model significantly outperforms a standard baseline. Our work suggests that it is feasible for future tutoring systems to generate assessments regarding the use of localization in student peer reviews. © 2010 Springer-Verlag.
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