VQA support to Arabic Language Learning Educational Tool
Khaled Bachir Delassi (1), Lakhdar Zeggane (1), Hadda Cherroun (1), Abdelhamid Haouhat (1), Kaoutar Bouzouad (2) ((1) LIM Lab, Amar Telidji University, Laghouat, Algeria, (2) Computer Science Dept., USTHB, Algiers, Algeria)

TL;DR
This paper presents an AI-powered educational tool using Visual Question Answering to enhance Arabic language learning for non-native speakers, focusing on vocabulary, grammar, and comprehension through interactive visual quizzes.
Contribution
It introduces a novel AI-based system that leverages vision-language models and large language models to generate and evaluate Arabic language learning quizzes, addressing resource scarcity.
Findings
Achieved accurate visual quiz generation and evaluation.
Validated the tool's effectiveness with human feedback.
Demonstrated potential to improve Arabic language proficiency.
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…
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