英语作文自动评价技术发展现状及教学应用启示
Current Status of Automated Evaluation Technology for English Essay and Its Application Implications for Teaching
摘要: 作文自动评价(Automated Essay Evaluation, AEE)研究已历经半个多世纪的发展。十年前，基于神经网络的深度学习技术引入作文自动评价研究，自动评价模型经历了一轮新的快速多元发展。目前，自动评价系统已从最初的浅层特征统计、评分模拟，发展到了能更好“理解”文章深层语义、分析多维度特征并提供有效反馈的较成熟阶段，应用潜力持续提升。本文以研究最为广泛的英语作文自动评价系统为例，通过分析现阶段主流研究中任务目标的多元化发展特征、优点与不足，为实际教育场景了解和利用现有成果、规避现存不足提供参考，以期更好地服务教育实践。
Abstract: Automated Essay Evaluation (AEE) has been an active area of research for over half a century. Since 2016, the integration of deep learning techniques has further enhanced the performance of AEE models, while the research objectives have become significantly diversified through increased emphasis on evaluation transparency, practical utility, and applicability. Contemporary AEE systems have developed capabilities in “understanding” deeper semantic content, analyzing multi-dimensional linguistic features, and generating constructive feedback. The present paper examines the diversification of task objectives in current AEE researches, along with their respective strengths and limitations. It aims to provide practical insights to better understand and leverage existing advancements, thereby facilitating more effective utilization of cutting-edge research findings in educational practice.
文章引用：黄云龙, 曾伊美. 英语作文自动评价技术发展现状及教学应用启示[J]. 现代语言学, 2026, 14(6): 530-537. https://doi.org/10.12677/ml.2026.146553

参考文献

[1] Aljuaid, H., Alhothali, A., Alzamzami, O., Assalahi, H. and Aldosemani, T. (2025) ET-GNN: Ensemble Transformer-Based Graph Neural Networks for Holistic Automated Essay Scoring. IEEE Access, 13, 58746-58758. [Google Scholar] [CrossRef] 
[2] Faseeh, M., Jaleel, A., Iqbal, N., Ghani, A., Abdusalomov, A., Mehmood, A., et al. (2024) Hybrid Approach to Automated Essay Scoring: Integrating Deep Learning Embeddings with Handcrafted Linguistic Features for Improved Accuracy. Mathematics, 12, Article 3416. [Google Scholar] [CrossRef] 
[3] Tate, T.P., Steiss, J., Bailey, D., Graham, S., Moon, Y., Ritchie, D., et al. (2024) Can AI Provide Useful Holistic Essay Scoring? Computers and Education: Artificial Intelligence, 7, Article ID: 100255. [Google Scholar] [CrossRef] 
[4] Li, X., Yang, H., Hu, S., Geng, J., Lin, K. and Li, Y. (2022) Enhanced Hybrid Neural Network for Automated Essay Scoring. Expert Systems, 39, e13068. [Google Scholar] [CrossRef] 
[5] Sun, J., Peng, W., Song, T., Liu, H., Zhu, S. and Song, J. (2024) Enhanced Cross-Prompt Trait Scoring via Syntactic Feature Fusion and Contrastive Learning. The Journal of Supercomputing, 80, 5390-5407. [Google Scholar] [CrossRef] 
[6] Wang, J. and Liu, J. (2025) T-MES: Trait-Aware Mix-Of-Experts Representation Learning for Multi-Trait Essay Scoring. Proceedings of the 31st International Conference on Computational Linguistics, Abu Dhabi, 19-24 January 2025, 1224-1236.
[7] Wang, Y., Hu, R. and Zhao, Z. (2024) Beyond Agreement: Diagnosing the Rationale Alignment of Automated Essay Scoring Methods Based on Linguistically-Informed Counterfactuals. Findings of the Association for Computational Linguistics: EMNLP 2024, Miami, 12-16 November 2024, 8906-8925. [Google Scholar] [CrossRef] 
[8] Liu, Y., Han, J., Sboev, A. and Makarov, I. (2024) GEEF: A Neural Network Model for Automatic Essay Feedback Generation by Integrating Writing Skills Assessment. Expert Systems with Applications, 245, Article ID: 123043. [Google Scholar] [CrossRef] 
[9] Han, J., Yoo, H., Myung, J.H., et al. (2023) LLM-as-a-Tutor in EFL Writing Education: Focusing on Evaluation of Student-LLM Interaction. [Google Scholar] [CrossRef] 
[10] Shi, H. and Aryadoust, V. (2024) A Systematic Review of AI-Based Automated Written Feedback Research. ReCALL, 36, 187-209. [Google Scholar] [CrossRef] 
[11] Song, Y., Zhu, Q., Wang, H. and Zheng, Q. (2024) Automated Essay Scoring and Revising Based on Open-Source Large Language Models. IEEE Transactions on Learning Technologies, 17, 1880-1890. [Google Scholar] [CrossRef] 
[12] Chen, Y. and Li, X. (2024) PLAES: Prompt-Generalized and Level-Aware Learning Framework for Cross-Prompt Automated Essay Scoring. Proceedings of the Language Resources and Evaluation Conference, Torino, 20-25 May 2024, 12775-12786. [Google Scholar] [CrossRef] 
[13] Wang, J., Zhang, Q., Liu, J., Wang, X., Xu, M., Yang, L., et al. (2025) Making Meta-Learning Solve Cross-Prompt Automatic Essay Scoring. Expert Systems with Applications, 272, Article ID: 126710. [Google Scholar] [CrossRef] 
[14] Li, X. and Pan, W. (2025) KAES: Multi-Aspect Shared Knowledge Finding and Aligning for Cross-Prompt Automated Scoring of Essay Traits. Proceedings of the AAAI Conference on Artificial Intelligence, 39, 24476-24484. [Google Scholar] [CrossRef] 
[15] Tang, X., Chen, H., Lin, D. and Li, K. (2024) Incorporating Fine-Grained Linguistic Features and Explainable AI into Multi-Dimensional Automated Writing Assessment. Applied Sciences, 14, Article 4182. [Google Scholar] [CrossRef] 
[16] Utami, N. and Ruskanda, F.Z. (2023) Automated Scoring of English Essays in CEFR Levels Using LSTM and DistilBERT Embeddings. 2023 10th International Conference on Advanced Informatics: Concept, Theory and Application (ICAICTA), Lombok, 7-9 October 2023, 1-6. [Google Scholar] [CrossRef] 
[17] 张冰雪, 邵小波, 熊振海, 等. 一种结合BERT修剪的作文自动评分模型[J]. 软件, 2020, 41(12): 89-94, 106.
[18] Sethi, A. and Singh, K. (2022) Natural Language Processing Based Automated Essay Scoring with Parameter-Efficient Transformer Approach. 2022 6th International Conference on Computing Methodologies and Communication (ICCMC), Erode, 29-31 March 2022, 749-756. [Google Scholar] [CrossRef] 
[19] Ormerod, C. and Kwako, A. (2024) Automated Text Scoring in the Age of Generative AI for the GPU-Poor. Chinese/English Journal of Educational Measurement and Evaluation, 5, Article 5. [Google Scholar] [CrossRef] 
[20] 程相群. 面向高并发的作文自动评分系统的设计与实现[D]: [硕士学位论文]. 沈阳: 中国科学院大学(中国科学院沈阳计算技术研究所), 2022.
[21] Wang, Y. and Hu, R. (2021) A Prompt-Independent and Interpretable Automated Essay Scoring Method for Chinese Second Language Writing. In: Li, S., et al., Eds., Chinese Computational Linguistics, Springer, 450-470. [Google Scholar] [CrossRef] 
[22] Vanga, R.R., Sindhu, C., Bharath, M.S., Reddy, T.C. and Kanneganti, M. (2023) Autograder: A Feature-Based Quantitative Essay Grading System Using Bert. In: Tuba, M., Akashe, S. and Joshi, A., Eds., ICT Infrastructure and Computing, Springer, 71-81. [Google Scholar] [CrossRef]