AI and LMS: the Transformation of Adaptive and Predictive-Based Digital Learning Management

Abstract

This research aims to explore the transformation of the learning management system (LMS) driven by the integration of artificial intelligence (AI), especially in the context of adaptivity and predictability of learning. Using a qualitative method through a literature study approach (library research), this study examines various scientific works, research reports, and the latest documentation related to the implementation of AI in LMS. The results of the study show that the use of AI in LMS is able to create a more personalized, adaptive learning experience to individual needs, and predictive in anticipating learning difficulties and student success. AI-based systems enable real-time analysis of learning data, appropriate material recommendations, and early intervention of potential learning failures. In addition, this integration also makes it easier for educators to design more effective and efficient learning strategies. However, challenges were also found in the aspects of ethics, data privacy, and the readiness of digital education infrastructure in various countries, especially in developing countries. This study concludes that the transformation of AI-based LMS is a strategic opportunity in improving the quality of digital education, but requires a comprehensive integrated policy, technology, and pedagogical approach. Recommendations are given for technology developers, policymakers, and educational institutions in adopting AI-based LMS responsibly and sustainably.