This study aims to present an in-depth analysis of the potential application of Deep Learning learning methods in improving reading literacy skills for elementary school students who face reading barriers. This literature review explores the application of Artificial Intelligence (AI)-based Deep Learning in the context of education, identifies the challenges faced by learners with reading difficulties, reviews existing teaching strategies, and researches case studies of Deep Learning implementation. In addition, this review literature discusses Deep Learning architectures relevant to natural language processing, the steps of developing and evaluating Deep Learning-based learning systems, ethical and practical considerations, and the resources and tools available. Key findings highlight the potential of Deep Learning in personalizing learning, providing intelligent guidance, automating assessments, and adaptive learning material generation. However, successful implementation requires careful consideration of pedagogical, ethical, and practical factors, as well as investment in teacher training and adequate infrastructure. With the Development of Deep Learning Learning Methods, it is hoped that early evaluation and implementation at the elementary school education level will be one of the keys to timely intervention and prevention before taking root and causing significant academic challenges in the future for students.
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