Intersection of Adaptive Learning, Global Collaboration, and Knowledge Sharing Through Machine Learning in Higher Education

Abstract

The chapter explores the integration of adaptive learning, global collaboration, and knowledge sharing in higher education, highlighting their transformative impact. Adaptive learning, driven by machine learning algorithms, tailors educational content to individual student needs, ensuring engagement and mastery of subjects. Global collaboration allows students to connect with peers, faculty, and experts worldwide, promoting diverse perspectives and cross-cultural learning. Knowledge sharing, facilitated by digital platforms and machine learning, empowers learners to create, curate, and disseminate knowledge, fostering a culture of collaboration and innovation. The chapter also discusses the challenges and ethical considerations in implementing machine learning in education, emphasizing privacy and data security. It also explores how educators can use data-driven insights to enhance pedagogical strategies.