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This research assesses the effectiveness of state-of-the-art large language models (LLMs), including ChatGPT, Llama, Aya, Jais, and ACEGPT, in the task of Arabic automated essay scoring (AES) using the AR-AES dataset. It explores various…

Computation and Language · Computer Science 2025-01-29 Rayed Ghazawi , Edwin Simpson

Automated Essay Scoring (AES) plays a crucial role in assessing language learners' writing quality, reducing grading workload, and providing real-time feedback. The lack of annotated essay datasets inhibits the development of Arabic AES…

Computation and Language · Computer Science 2025-06-11 Chatrine Qwaider , Bashar Alhafni , Kirill Chirkunov , Nizar Habash , Ted Briscoe

Research on holistic Automated Essay Scoring (AES) is long-dated; yet, there is a notable lack of attention for assessing essays according to individual traits. In this work, we propose TRATES, a novel trait-specific and rubric-based…

Computation and Language · Computer Science 2025-06-03 Sohaila Eltanbouly , Salam Albatarni , Tamer Elsayed

Automated Essay Scoring (AES) holds significant promise in the field of education, helping educators to mark larger volumes of essays and provide timely feedback. However, Arabic AES research has been limited by the lack of publicly…

Computation and Language · Computer Science 2024-07-17 Rayed Ghazawi , Edwin Simpson

Advances in automated essay scoring (AES) have traditionally relied on labeled essays, requiring tremendous cost and expertise for their acquisition. Recently, large language models (LLMs) have achieved great success in various tasks, but…

Computation and Language · Computer Science 2024-10-07 Sanwoo Lee , Yida Cai , Desong Meng , Ziyang Wang , Yunfang Wu

Automated essay scoring (AES) aims to score essays written for a given prompt, which defines the writing topic. Most existing AES systems assume to grade essays of the same prompt as used in training and assign only a holistic score.…

Computation and Language · Computer Science 2023-08-30 Heejin Do , Yunsu Kim , Gary Geunbae Lee

The performance of Large Language Models (LLMs) is highly sensitive to the prompts they are given. Drawing inspiration from the field of prompt optimization, this study investigates the potential for enhancing Automated Essay Scoring (AES)…

Computation and Language · Computer Science 2025-10-13 Keno Harada , Lui Yoshida , Takeshi Kojima , Yusuke Iwasawa , Yutaka Matsuo

Automatic Essay Scoring (AES) is a well-established educational pursuit that employs machine learning to evaluate student-authored essays. While much effort has been made in this area, current research primarily focuses on either (i)…

Computation and Language · Computer Science 2024-01-12 Kaixun Yang , Mladen Raković , Yuyang Li , Quanlong Guan , Dragan Gašević , Guanliang Chen

Automatic Essay Scoring (AES) assigns scores to student essays, reducing the grading workload for instructors. Developing a scoring system capable of handling essays across diverse prompts is challenging due to the flexibility and diverse…

Computation and Language · Computer Science 2025-02-14 Zhaoyi Joey Hou , Alejandro Ciuba , Xiang Lorraine Li

Over the past years, Automated Essay Scoring (AES) systems have gained increasing attention as scalable and consistent solutions for assessing the proficiency of student writing. Despite recent progress, support for Arabic AES remains…

Computation and Language · Computer Science 2026-05-20 Hoor Elbahnasawi , Marwan Sayed , Sohaila Eltanbouly , Fatima Brahamia , Tamer Elsayed

Large Language Models (LLMs) have shown promise in Automated Essay Scoring (AES), but their zero-shot and few-shot performance often falls short compared to state-of-the-art models and human raters. However, fine-tuning LLMs for each…

Computation and Language · Computer Science 2024-07-09 Seungju Kim , Meounggun Jo

Automated Essay Scoring (AES) has gained increasing attention in recent years, yet research on Arabic AES remains limited due to the lack of publicly available datasets. To address this, we introduce LAILA, the largest publicly available…

Computation and Language · Computer Science 2026-01-27 May Bashendy , Walid Massoud , Sohaila Eltanbouly , Salam Albatarni , Marwan Sayed , Abrar Abir , Houda Bouamor , Tamer Elsayed

This study addresses the issues of semantic entanglement, unclear label structure, and insufficient feature representation in few-shot text classification, and proposes an optimization framework based on structured prompts to enhance…

Computation and Language · Computer Science 2026-03-02 Jiasen Zheng , Zijun Zhou , Huajun Zhang , Junjiang Lin , Jingyun Jia , Qi Wang

Mental health disorders pose a growing public health concern in the Arab world, emphasizing the need for accessible diagnostic and intervention tools. Large language models (LLMs) offer a promising approach, but their application in Arabic…

Computation and Language · Computer Science 2025-01-14 Noureldin Zahran , Aya E. Fouda , Radwa J. Hanafy , Mohammed E. Fouda

Due to their architecture and vast pre-training data, large language models (LLMs) demonstrate strong text classification performance. However, LLM output - here, the category assigned to a text - depends heavily on the wording of the…

Computation and Language · Computer Science 2025-12-04 Kylie L. Anglin , Stephanie Milan , Brittney Hernandez , Claudia Ventura

Individual feedback can help students improve their essay writing skills. However, the manual effort required to provide such feedback limits individualization in practice. Automatically-generated essay feedback may serve as an alternative…

Computation and Language · Computer Science 2024-04-25 Maja Stahl , Leon Biermann , Andreas Nehring , Henning Wachsmuth

Assessing soft skills such as empathy, ethical judgment, and communication is essential in competitive selection processes, yet human scoring is often inconsistent and biased. While Large Language Models (LLMs) have improved Automated Essay…

Computation and Language · Computer Science 2026-02-03 Ryan Huynh , Frank Guerin , Alison Callwood

Automated Essay Scoring (AES) plays a crucial role in education by providing scalable and efficient assessment tools. However, in real-world settings, the extreme scarcity of labeled data severely limits the development and practical…

Computation and Language · Computer Science 2026-02-03 Hongseok Choi , Serynn Kim , Wencke Liermann , Jin Seong , Jin-Xia Huang

A sufficient amount of annotated data is usually required to fine-tune pre-trained language models for downstream tasks. Unfortunately, attaining labeled data can be costly, especially for multiple language varieties and dialects. We…

Computation and Language · Computer Science 2021-02-04 Muhammad Khalifa , Muhammad Abdul-Mageed , Khaled Shaalan

Dialectal Arabic (DA) poses a persistent challenge for natural language processing (NLP), as most everyday communication in the Arab world occurs in dialects that diverge significantly from Modern Standard Arabic (MSA). This linguistic…

Computation and Language · Computer Science 2025-09-04 Abdullah Alabdullah , Lifeng Han , Chenghua Lin
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