A Literature Review on Arabic Automatic Question Generation
DOI:
https://doi.org/10.59421/joeats.v3i1.2477الكلمات المفتاحية:
Question generation، Arabic language، Artificial intelligence، Contextsالملخص
This comprehensive literature review is dedicated to the field of Arabic Automatic Question Generation (AQG), which focuses on the development of computational models and algorithms for the automatic generation of questions. The review systematically covers key concepts in AQG, including question types and evaluation metrics. Additionally, it delves into the specific challenges associated with applying AQG techniques to the Arabic language, considering factors like complex morphology and dialectal variations. The review introduces a taxonomy of Arabic AQG approaches, classifying them into rule-based, template-based, and machine learning-based methods. It examines the pivotal role of datasets, resources, and evaluation methodologies in the training and assessment of AQG systems. Advancements in Arabic AQG are highlighted, and the review identifies emerging research directions, such as domain-specific question generation and integration into educational platforms.
In conclusion, the review provides valuable insights for researchers, developers, and educators interested in Arabic AQG. It addresses current advancements, challenges, and outlines potential future research directions, including the scarcity of labeled data and the necessity for domain-specific approaches. Overall, this review serves as a comprehensive resource in the realm of Arabic AQG.
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