VQA support to Arabic Language Learning Educational Tool

August 05, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Khaled Bachir Delassi, Lakhdar Zeggane, Hadda Cherroun, Abdelhamid Haouhat, Kaoutar Bouzouad arXiv ID 2508.03488 Category cs.AI: Artificial Intelligence Cross-listed cs.SE Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
We address the problem of scarcity of educational Arabic Language Learning tools that advocate modern pedagogical models such as active learning which ensures language proficiency. In fact, we investigate the design and evaluation of an AI-powered educational tool designed to enhance Arabic language learning for non-native speakers with beginner-to-intermediate proficiency level. The tool leverages advanced AI models to generate interactive visual quizzes, deploying Visual Question Answering as the primary activity. Adopting a constructivist learning approach, the system encourages active learning through real-life visual quizzes, and image-based questions that focus on improving vocabulary, grammar, and comprehension. The system integrates Vision-Language Pretraining models to generate contextually relevant image description from which Large Language Model generate assignments based on customized Arabic language Learning quizzes thanks to prompting. The effectiveness of the tool is evaluated through a manual annotated benchmark consisting of 1266 real-life visual quizzes, with human participants providing feedback. The results show a suitable accuracy rates, validating the tool's potential to bridge the gap in Arabic language education and highlighting the tool's promise as a reliable, AI-powered resource for Arabic learners, offering personalized and interactive learning experiences.
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