ArabIcros: AI-Powered Arabic Crossword Puzzle Generation for Educational Applications
Project Overview
The document highlights the innovative application of generative AI in education through the development of an AI-powered Arabic crossword puzzle generator that leverages advanced large language models (LLMs). This tool aims to enhance vocabulary, memory retention, and problem-solving skills in learners by transforming the learning experience into a more interactive and engaging process. By employing fine-tuning techniques and strategic learning methodologies, the generator produces high-quality clues and answer pairs, thereby enriching the educational landscape for Arabic language learners. The findings suggest that such AI-driven tools not only facilitate language acquisition but also foster a more enjoyable and effective learning environment, demonstrating the significant potential of generative AI in reshaping educational practices.
Key Applications
AI-Powered Arabic Crossword Puzzle Generator
Context: Educational context for Arabic language learners, targeting students and educators.
Implementation: The system uses large language models like GPT-4 and fine-tuning techniques to generate crossword clues based on provided text or keywords.
Outcomes: Enhances vocabulary, memory retention, and problem-solving skills in learners; fosters interactive learning experiences.
Challenges: Generating high-quality clues specific to the unique linguistic nuances of Arabic; ensuring the quality and appropriateness of clues.
Implementation Barriers
Technical Barrier
The complexity of generating accurate and contextually appropriate crossword clues in Arabic due to linguistic nuances.
Proposed Solutions: Utilizing advanced natural language processing techniques and conducting systematic evaluations of generated clues.
Project Team
Kamyar Zeinalipour
Researcher
Mohamed Zaky Saad
Researcher
Marco Maggini
Researcher
Marco Gori
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Kamyar Zeinalipour, Mohamed Zaky Saad, Marco Maggini, Marco Gori
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai