Automated Chinese Essay Scoring from Multiple Traits

Yaqiong He, Feng Jiang, Xiaomin Chu, Peifeng Li


Abstract
Automatic Essay Scoring (AES) is the task of using the computer to evaluate the quality of essays automatically. Current research on AES focuses on scoring the overall quality or single trait of prompt-specific essays. However, the users not only expect to obtain the overall score but also the instant feedback from different traits to help their writing in the real world. Therefore, we first annotate a mutli-trait dataset ACEA including 1220 argumentative essays from four traits, i.e., essay organization, topic, logic, and language. And then we design a hierarchical multi-task trait scorer HMTS to evaluate the quality of writing by modeling these four traits. Moreover, we propose an inter-sequence attention mechanism to enhance information interaction between different tasks and design the trait-specific features for various tasks in AES. The experimental results on ACEA show that our HMTS can effectively score essays from multiple traits, outperforming several strong models.
Anthology ID:
2022.coling-1.266
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
3007–3016
Language:
URL:
https://aclanthology.org/2022.coling-1.266
DOI:
Bibkey:
Cite (ACL):
Yaqiong He, Feng Jiang, Xiaomin Chu, and Peifeng Li. 2022. Automated Chinese Essay Scoring from Multiple Traits. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3007–3016, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Automated Chinese Essay Scoring from Multiple Traits (He et al., COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.266.pdf