In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3994–4004, Florence, Italy. Give Me More Feedback II: Annotating Thesis Strength and Related Attributes in Student Essays. Anthology ID: P19-1390 Volume: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics Month: July Year: 2019 Address: Florence, Italy Venue: ACL SIG: Publisher: Association for Computational Linguistics Note: Pages: 3994–4004 Language: URL: DOI: 10.18653/v1/P19-1390 Bibkey: ke-etal-2019-give Cite (ACL): Zixuan Ke, Hrishikesh Inamdar, Hui Lin, and Vincent Ng. 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. 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. Nevertheless, progress on dimension-specific essay scoring is limited in part by the lack of annotated corpora. 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.
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