Transforming E-learning with Adaptive Technologies to Improve Personalized Learning

Education has been transformed by e-learning, which offers flexibility and accessibility. However, conventional online learning systems frequently fail to accommodate the tempo and preferences of individual learners. Thus, there is a need to adaptive learning technologies which utilizes Machine Learning (ML) and Artificial Intelligence (AI) and can transforming answer to our needs. This article explores how adaptive technologies change material delivery, assessment techniques, and learning paths in real-time depending on student performance and engagement. Our proposed work emphasizes the influence of learner outcomes, important innovations such intelligent tutoring systems, adaptive assessments, and predictive analytics. This also including data privacy concerns, implementation costs, and scalability over the various types of learners. Adaptive technologies help e-learning systems provide more effective, interesting, and learner-cantered instructional opportunities. This paper highlights the possibilities of adaptive e-learning to narrow knowledge gaps, increase retention, and encourage lifetime learning in many kinds of educational environments.