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arXiv · 2406.01198

Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression

Kun Sun·Rong Wang
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Abstract

Automated essay scoring (AES) involves predicting a score that reflects the writing quality of an essay. Most existing AES systems produce only a single overall score. However, users and L2 learners expect scores across different dimensions (e.g., vocabulary, grammar, coherence) for English essays in real-world applications. To address this need, we have developed two models that automatically score English essays across multiple dimensions by employing fine-tuning and other strategies on two large datasets. The results demonstrate that our systems achieve impressive performance in evaluation using three criteria: precision, F1 score, and Quadratic Weighted Kappa. Furthermore, our system outperforms existing methods in overall scoring.

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Kun Sun, Rong Wang. 2024-06-03. Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression. https://arxiv.org/abs/2406.01198

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