Applying Rhetorical Structure Theory to Student Essays for Providing Automated Writing Feedback

Shiyan Jiang, Kexin Yang, Chandrakumari Suvarna, Pooja Casula, Mingtong Zhang, Carolyn Rosé

Abstract
We present a package of annotation resources, including annotation guideline, flowchart, and an Intelligent Tutoring System for training human annotators. These resources can be used to apply Rhetorical Structure Theory (RST) to essays written by students in K-12 schools. Furthermore, we highlight the great potential of using RST to provide automated feedback for improving writing quality across genres.
Anthology ID:
W19-2720
Volume:
Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019
Month:
June
Year:
2019
Address:
Minneapolis, MN
Editors:
Amir Zeldes, Debopam Das, Erick Maziero Galani, Juliano Desiderato Antonio, Mikel Iruskieta
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
163–168
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W19-2720/
DOI:
10.18653/v1/W19-2720
Bibkey:
Cite (ACL):
Shiyan Jiang, Kexin Yang, Chandrakumari Suvarna, Pooja Casula, Mingtong Zhang, and Carolyn Rosé. 2019. Applying Rhetorical Structure Theory to Student Essays for Providing Automated Writing Feedback. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019, pages 163–168, Minneapolis, MN. Association for Computational Linguistics.
Cite (Informal):
Applying Rhetorical Structure Theory to Student Essays for Providing Automated Writing Feedback (Jiang et al., NAACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W19-2720.pdf
Presentation:
 W19-2720.Presentation.pdf
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