@inproceedings{elbahnasawi-etal-2026-qayyem,
    title = "Qayyem: A Real-time Platform for Scoring Proficiency of {A}rabic Essays",
    author = "Elbahnasawi, Hoor Tamer  and
      Sayed, Marwan  and
      Eltanbouly, Sohaila  and
      Brahamia, Fatima Zahra  and
      Elsayed, Tamer",
    editor = "Durrett, Greg  and
      Jian, Ping",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-demo.53/",
    pages = "536--545",
    ISBN = "979-8-89176-392-0",
    abstract = "Over the past years, Automated Essay Scoring (AES) systems have gained increasing attention as scalable and consistent solutions for assessing proficiency of student writing. Despite recent progress, support for Arabic AES remains limited due to linguistic complexity and scarcity of large publicly-available annotated datasets. In this work, we present Qayyem, a Web-based platform designed to support Arabic AES by providing an integrated workflow for assignment creation, batch essay upload, scoring configuration, and per-trait essay evaluation. Qayyem abstracts the technical complexity of interacting with scoring server APIs, allowing instructors to access advanced scoring services through a user-friendly interface. The platform deploys a number of state-of-the-art Arabic essay scoring models with different effectiveness and efficiency figures."
}