Learning Management Systems in Higher Education A Multidimensional Analysis of Technologies, Adoption, and Innovation
Learning Management Systems (LMSs) have become a core part of higher education because they bring course content, communication, assessment, learner support, and academic information into a common digital environment. This survey examines LMS development from traditional classroom practices and computer-assisted learning to web-based, cloud-based, and artificial intelligence-enabled platforms. The review also considers the major theories used to explain LMS adoption, the needs of students, instructors, administrators, and institutions, and the functional components that determine platform usefulness. Particular attention is given to learning analytics, adaptive learning, mobile access, gamification, interoperability, privacy, accessibility, and artificial intelligence. The literature indicates that LMS effectiveness is not determined by technology alone. User acceptance, instructional design, institutional support, digital skills, infrastructure, and responsible data practices strongly influence outcomes. Recent work also shows a shift from LMSs as content repositories toward intelligent learning ecosystems capable of supporting personalization and data-informed decision making. Based on the reviewed literature, the paper identifies continuing gaps in evidence about long-term learning outcomes, responsible AI integration, accessibility, cross-platform interoperability, and context-sensitive adoption. The review concludes with future directions for learner-centered, secure, inclusive, and intelligent LMS ecosystems.