Revolutionizing Moroccan Education with AI: A Path to Customized Learning

Abstract

This integrative literature review analyzes how AI, specifically Machine Learning (ML) and Large Language Models (LLMs), is used in Moroccan education. The study emphasizes the significance of modernizing traditional educational techniques. It investigates how artificial intelligence may personalize learning experiences, minimize educational disparities, and foster a culturally diverse and technologically sophisticated learning environment. The ILR uses a conceptual framework that highlights customized learning, equitable education, technological innovation, and a systematic methodology that incorporates extensive literature synthesis. The research process thoroughly examines multiple academic sources, including peer-reviewed articles, books, conference papers, and reports. The ILR identifies relevant patterns, barriers, and opportunities associated with integrating AI in Moroccan education by carefully studying and synthesizing data. The findings demonstrate the enormous potential of ML and LLMs in revolutionizing teaching methods, encouraging active student participation, and closing educational inequalities across Morocco. The paper finishes by underlining the need to incorporate AI into educational practice and identifying areas for future research. It emphasizes investigating how AI may help Morocco and other countries modernize their education systems.

Keywords:

Artificial intelligence, Machine learning, Large language models, Education, Morocco, Personalized learning, Educational disparities, Cultural inclusivity