CUSTOMIZING TUTORING TO INDIVIDUAL STUDENT NEEDS THROUGH ADAPTIVE AI

Abstract

This abstract explores the intersection of education and artificial intelligence (AI), focusing on the development and implementation of adaptive AI systems to personalize tutoring experiences for students. The traditional one-size-fits-all approach to education has long been recognized as insufficient in catering to the diverse learning styles and needs of individual students. With the advent of adaptive AI, there is an unprecedented opportunity to revolutionize the educational landscape by tailoring tutoring sessions to the unique requirements of each learner. The paper delves into the significance of personalized learning in improving student outcomes and engagement. The abstract explores how the systems can seamlessly integrate with existing educational frameworks, adapting to diverse curricula while providing personalized support. This delicate balance is crucial for ensuring that students not only receive tailored assistance but also adhere to broader educational standards and goals. Furthermore, the abstract highlights the ethical considerations surrounding AI in education, emphasizing the need for transparency, accountability, and privacy protection. As adaptive AI gathers and processes vast amounts of student data, there is a necessity to establish robust safeguards to protect sensitive information and ensure ethical use.