ABSTRACT
Personalized digital learning systems can achieve far better educational results than are customary approaches since they instruct and customize instruction to each student's own understanding and learning style preference. These platforms employ AI techniques within. Individual abilities of students are matched to content through the utilization of the techniques. Through four primary questions, this research investigates the requirements and obstacles in implementing adaptive e-learning because it identifies personalization components, reviews research progress, uses AI benefits, and establishes future research directions. The paper stresses on the developing of frameworks that can address the technical implementation for AI applications. These frameworks should address too the ethical dimensions. Researchers, education practitioners, and policymakers are helped by this evaluation since it stresses their joint initiation of AI technologies that support sustainable, ethical, and inclusive learning approaches. For teachers plus for educational institutions, AI-improved learning platforms remain powerful resources. These systems effectively use information students generate so they can assess as well as give responsive feedback as learners learn, which eases individualized solutions and feedback systems for learners.
