Abstract
While the vast majority of existing work on automated essay scoring has focused on holistic scoring, researchers have recently begun work on scoring specific dimensions of essay quality. Nevertheless, progress on dimension-specific essay scoring is limited in part by the lack of annotated corpora. To facilitate advances in this area, we design a scoring rubric for scoring a core, yet unexplored dimension of persuasive essay quality, thesis strength, and annotate a corpus of essays with thesis strength scores. We additionally identify the attributes that could impact thesis strength and annotate the essays with the values of these attributes, which, when predicted by computational models, could provide further feedback to students on why her essay receives a particular thesis strength score.- Anthology ID:
- P19-1390
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3994–4004
- Language:
- URL:
- https://aclanthology.org/P19-1390
- DOI:
- 10.18653/v1/P19-1390
- Cite (ACL):
- Zixuan Ke, Hrishikesh Inamdar, Hui Lin, and Vincent Ng. 2019. Give Me More Feedback II: Annotating Thesis Strength and Related Attributes in Student Essays. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3994–4004, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Give Me More Feedback II: Annotating Thesis Strength and Related Attributes in Student Essays (Ke et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/P19-1390.pdf