| Abstrakt: |
Artificial Intelligence (AI) has revolutionized various sectors, and education is no exception. This review paper explores the transformative role of AI-driven personalized learning in enhancing student success through adaptive technologies. Personalized learning, powered by AI, tailors educational experiences to individual students' needs, pace, and learning styles, offering a significant departure from traditional, one-size-fits-all approaches. By analyzing vast amounts of student data, AI systems can predict learning outcomes, identify knowledge gaps, and provide real-time feedback, creating a dynamic and responsive learning environment. This paper examines the key AI technologies, including machine learning algorithms, natural language processing, and intelligent tutoring systems, which facilitate adaptive learning. It discusses how these technologies create a more engaging, efficient, and personalized educational experience, thereby improving student retention, motivation, and academic performance. The paper also highlights case studies of successful AI implementations in educational settings, offering insights into best practices and challenges. Additionally, this paper addresses the ethical considerations and potential challenges, such as data privacy concerns and the digital divide, that may arise from the widespread adoption of AI in education. The implications of these challenges for educators, policymakers, and students are critically analyzed. By synthesizing existing research, this paper aims to provide a comprehensive understanding of how AI-driven personalized learning can be leveraged to enhance student success and transform the future of education. It concludes with recommendations for future research and strategies to overcome current barriers, ensuring equitable access to these advanced learning technologies for all students. [ABSTRACT FROM AUTHOR] |
