Give Me More Feedback II: Annotating Thesis Strength and Related Attributes in Student Essays

Zixuan Ke, Hrishikesh Inamdar, Hui Lin, Vincent Ng


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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/P19-1390.pdf