Deep Neural Network-Based Automated Essay Trait Scoring Model Incorporating Argument Structure Information 


Vol. 50,  No. 8, pp. 662-670, Aug.  2023
10.5626/JOK.2023.50.8.662


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  Abstract

Automated essay scoring is the task of having a model read a given essay and evaluate it automatically. This paper presents a method for automated essay scoring by creating essay representations that reflect argument structure of the essay using Argument Mining, and learning essay representations for each trait score. Results of our experiments indicated that the proposed essay representation outperformed representations obtained from pre-trained language models. Furthermore, it was found that learning different representations for each evaluation criterion was more effective for essay evaluation. The performance of the proposed model, as measured by the Quadratic Weighted Kappa (QWK) metric, improved from 0.543 to 0.627, showing a high level of agreement with human evaluations. Qualitative evaluations also showed that the proposed model demonstrated similar evaluation tendencies to human evaluations.


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  Cite this article

[IEEE Style]

Y. Lee and H. Kim, "Deep Neural Network-Based Automated Essay Trait Scoring Model Incorporating Argument Structure Information," Journal of KIISE, JOK, vol. 50, no. 8, pp. 662-670, 2023. DOI: 10.5626/JOK.2023.50.8.662.


[ACM Style]

Yejin Lee and Harksoo Kim. 2023. Deep Neural Network-Based Automated Essay Trait Scoring Model Incorporating Argument Structure Information. Journal of KIISE, JOK, 50, 8, (2023), 662-670. DOI: 10.5626/JOK.2023.50.8.662.


[KCI Style]

이예진, 김학수, "논증 구조 정보를 통합한 심층 신경망 기반 에세이 특성 자동 평가 모델," 한국정보과학회 논문지, 제50권, 제8호, 662~670쪽, 2023. DOI: 10.5626/JOK.2023.50.8.662.


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