AI-Driven Personalized Learning Strategy for Enhancing Holy Quran Memorization Through Memory Theories

Abstract

The practice of Quran memorization has been the core aspect of Islamic education for a while, and like any other endeavor, it comes with difficulties like uninterrupted attention, motivation, a relatively limited number of qualified teachers, and others. Additionally, the use of modern information technology (IT) in this area is still very shallow which prevents the application of modern technique aids to learning. This study seeks to examine how personal learning approaches that are powered by AI, together with cognitive learning theories and modern technology, could enhance memorization of the Holy Quran through tailored teaching methods at the levels of sensory input, short-term memory, and long-term memory. A qualitative analysis approach was used to review the available literature, case studies, and technological reports on the tools and methods of Quran memorization. The study analyzes tools for sensory learning and digital sensory learning such as EzHifz, Miro, and Quizlet and analyzes the application of gamification, spaced repetition, and mind mapping aimed at improving motivation, retention, and understanding. The results show the distance between teachers and students can be bridged by the use of aids alongside modern techniques in teaching. The research, therefore, recommends that an AI-powered tailored plan to learning frameworks can significantly change and improve techniques used in Quran memorization while any integration of AI into religious education frameworks must critically address ethical and cultural matters.