Using Argument Mining to Assess the Argumentation Quality of Essays

Henning Wachsmuth, Khalid Al-Khatib, Benno Stein


Abstract
Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay’s organization and its argument strength.
Anthology ID:
C16-1158
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
1680–1691
Language:
URL:
https://aclanthology.org/C16-1158
DOI:
Bibkey:
Cite (ACL):
Henning Wachsmuth, Khalid Al-Khatib, and Benno Stein. 2016. Using Argument Mining to Assess the Argumentation Quality of Essays. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1680–1691, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Using Argument Mining to Assess the Argumentation Quality of Essays (Wachsmuth et al., COLING 2016)
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PDF:
https://aclanthology.org/C16-1158.pdf