@inproceedings{sayed-etal-2025-feature,
    title = "Feature Engineering is not Dead: A Step Towards State of the Art for {A}rabic Automated Essay Scoring",
    author = "Sayed, Marwan  and
      Eltanbouly, Sohaila  and
      Bashendy, May  and
      Elsayed, Tamer",
    editor = "Darwish, Kareem  and
      Ali, Ahmed  and
      Abu Farha, Ibrahim  and
      Touileb, Samia  and
      Zitouni, Imed  and
      Abdelali, Ahmed  and
      Al-Ghamdi, Sharefah  and
      Alkhereyf, Sakhar  and
      Zaghouani, Wajdi  and
      Khalifa, Salam  and
      AlKhamissi, Badr  and
      Almatham, Rawan  and
      Hamed, Injy  and
      Alyafeai, Zaid  and
      Alowisheq, Areeb  and
      Inoue, Go  and
      Mrini, Khalil  and
      Alshammari, Waad",
    booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.arabicnlp-main.19/",
    pages = "231--245",
    ISBN = "979-8-89176-352-4",
    abstract = "Automated Essay Scoring (AES) has shown significant advancements in educational assessment. However, under-resourced languages like Arabic have received limited attention. To bridge this gap and enable robust Arabic AES, this paper introduces the $\textit{first publicly-available}$ comprehensive set of engineered features tailored for Arabic AES, covering surface-level, readability, lexical, syntactic, and semantic features. Experiments are conducted on a dataset of 620 Arabic essays, each annotated with both holistic and trait-specific scores. Our findings demonstrate that the proposed feature set is effective across different models and competitive with recent NLP advances including LLMs, establishing the state-of-the-art performance and providing strong baselines for future Arabic AES research. Moroever, the resulting feature set offers a reusable and foundational resource, contributing towards the development of more effective Arabic AES systems."
}