Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909215456493568 |
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| author | Sun, Kun Wang, Rong |
| author_facet | Sun, Kun Wang, Rong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_01198 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression Sun, Kun Wang, Rong Computation and Language Artificial Intelligence 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. |
| title | Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2406.01198 |