Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs

Abstract

This article explores the transformative potential of artificial intelligence in special education, addressing the persistent challenges faced by students with diverse learning needs. In the article of implementation studies across various educational contexts, we explore how AI-powered applications create personalized learning experiences through adaptive algorithms, cognitive assessment capabilities, and data-driven content customization. The article shows accessibility features including multi-modal content delivery, assistive technology integration, adaptive user interfaces, and real-time feedback mechanisms. Empirical evidence demonstrates significant improvements in academic outcomes, engagement levels, and cost-effectiveness compared to traditional interventions, with particularly strong effects in mathematics and reading comprehension. The article concludes with an examination of ethical considerations including data privacy, optimal technology-human instruction balance, emerging AI capabilities, and policy recommendations for equitable implementation, providing a framework for the development and deployment of AI-powered educational technologies for students with special needs.