Artificial Intelligence in Education: Tailoring Curriculum to Individual Student Needs through AI-Based Systems.

The integration of Artificial Intelligence (AI) in education is transforming the traditional learning landscape by personalizing curriculum and enhancing student engagement. This review paper explores the potential of AI-based systems to tailor educational experiences to individual student needs. Through a comprehensive analysis of recent literature, we examine various AI technologies--such as machine learning, natural language processing, and adaptive learning systems--that facilitate personalized learning paths. By analyzing case studies and empirical evidence, we highlight how these systems can assess student performance, identify learning gaps, and adapt instructional content accordingly. The review identifies key benefits of AI in education, including improved learning outcomes, increased motivation, and enhanced accessibility for diverse learners. However, challenges such as data privacy, algorithmic bias, and the need for teacher training are also addressed. Furthermore, we discuss the implications of AI integration for educators and policymakers, emphasizing the necessity of ethical frameworks and guidelines to govern the use of AI in educational settings. This paper concludes by suggesting directions for future research, including the exploration of AI's impact on collaborative learning and the potential for AI to support lifelong learning initiatives. By leveraging AI technologies, educational institutions can create more inclusive, effective, and responsive learning environments that cater to the unique needs of each student, ultimately fostering a more equitable educational landscape. This review aims to contribute to the ongoing discourse on the role of AI in education and provide insights for stakeholders looking to implement AI-driven solutions in curriculum design and instructional strategies. [ABSTRACT FROM AUTHOR]