@inproceedings{bashendy-etal-2024-qaes,
title = "{QAES}: First Publicly-Available Trait-Specific Annotations for Automated Scoring of {A}rabic Essays",
author = "Bashendy, May and
Albatarni, Salam and
Eltanbouly, Sohaila and
Zahran, Eman and
Elhuseyin, Hamdo and
Elsayed, Tamer and
Massoud, Walid and
Bouamor, Houda",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Abdelali, Ahmed and
Touileb, Samia and
Hamed, Injy and
Onaizan, Yaser and
Alhafni, Bashar and
Antoun, Wissam and
Khalifa, Salam and
Haddad, Hatem and
Zitouni, Imed and
AlKhamissi, Badr and
Almatham, Rawan and
Mrini, Khalil",
booktitle = "Proceedings of The Second Arabic Natural Language Processing Conference",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.arabicnlp-1.28/",
doi = "10.18653/v1/2024.arabicnlp-1.28",
pages = "337--351",
abstract = "Automated Essay Scoring (AES) has emerged as a significant research problem within natural language processing, providing valuable support for educators in assessing student writing skills. In this paper, we introduce QAES, the first publicly available trait-specific annotations for Arabic AES, built on the Qatari Corpus of Argumentative Writing (QCAW). QAES includes a diverse collection of essays in Arabic, each of them annotated with holistic and trait-specific scores, including relevance, organization, vocabulary, style, development, mechanics, and grammar. In total, it comprises 195 Arabic essays (with lengths ranging from 239 to 806 words) across two distinct argumentative writing tasks. We benchmark our dataset against the state-of-the-art English baselines and a feature-based approach. In addition, we discuss the adopted guidelines and the challenges encountered during the annotation process. Finally, we provide insights into potential areas for improvement and future directions in Arabic AES research."
}
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<abstract>Automated Essay Scoring (AES) has emerged as a significant research problem within natural language processing, providing valuable support for educators in assessing student writing skills. In this paper, we introduce QAES, the first publicly available trait-specific annotations for Arabic AES, built on the Qatari Corpus of Argumentative Writing (QCAW). QAES includes a diverse collection of essays in Arabic, each of them annotated with holistic and trait-specific scores, including relevance, organization, vocabulary, style, development, mechanics, and grammar. In total, it comprises 195 Arabic essays (with lengths ranging from 239 to 806 words) across two distinct argumentative writing tasks. We benchmark our dataset against the state-of-the-art English baselines and a feature-based approach. In addition, we discuss the adopted guidelines and the challenges encountered during the annotation process. Finally, we provide insights into potential areas for improvement and future directions in Arabic AES research.</abstract>
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%0 Conference Proceedings
%T QAES: First Publicly-Available Trait-Specific Annotations for Automated Scoring of Arabic Essays
%A Bashendy, May
%A Albatarni, Salam
%A Eltanbouly, Sohaila
%A Zahran, Eman
%A Elhuseyin, Hamdo
%A Elsayed, Tamer
%A Massoud, Walid
%A Bouamor, Houda
%Y Habash, Nizar
%Y Bouamor, Houda
%Y Eskander, Ramy
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Abdelali, Ahmed
%Y Touileb, Samia
%Y Hamed, Injy
%Y Onaizan, Yaser
%Y Alhafni, Bashar
%Y Antoun, Wissam
%Y Khalifa, Salam
%Y Haddad, Hatem
%Y Zitouni, Imed
%Y AlKhamissi, Badr
%Y Almatham, Rawan
%Y Mrini, Khalil
%S Proceedings of The Second Arabic Natural Language Processing Conference
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F bashendy-etal-2024-qaes
%X Automated Essay Scoring (AES) has emerged as a significant research problem within natural language processing, providing valuable support for educators in assessing student writing skills. In this paper, we introduce QAES, the first publicly available trait-specific annotations for Arabic AES, built on the Qatari Corpus of Argumentative Writing (QCAW). QAES includes a diverse collection of essays in Arabic, each of them annotated with holistic and trait-specific scores, including relevance, organization, vocabulary, style, development, mechanics, and grammar. In total, it comprises 195 Arabic essays (with lengths ranging from 239 to 806 words) across two distinct argumentative writing tasks. We benchmark our dataset against the state-of-the-art English baselines and a feature-based approach. In addition, we discuss the adopted guidelines and the challenges encountered during the annotation process. Finally, we provide insights into potential areas for improvement and future directions in Arabic AES research.
%R 10.18653/v1/2024.arabicnlp-1.28
%U https://aclanthology.org/2024.arabicnlp-1.28/
%U https://doi.org/10.18653/v1/2024.arabicnlp-1.28
%P 337-351
Markdown (Informal)
[QAES: First Publicly-Available Trait-Specific Annotations for Automated Scoring of Arabic Essays](https://aclanthology.org/2024.arabicnlp-1.28/) (Bashendy et al., ArabicNLP 2024)
ACL
- May Bashendy, Salam Albatarni, Sohaila Eltanbouly, Eman Zahran, Hamdo Elhuseyin, Tamer Elsayed, Walid Massoud, and Houda Bouamor. 2024. QAES: First Publicly-Available Trait-Specific Annotations for Automated Scoring of Arabic Essays. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 337–351, Bangkok, Thailand. Association for Computational Linguistics.