AI-Driven Learning Management Systems: Transforming Classroom Teaching

The integration of artificial intelligence (AI) technologies brings with it numerous prospects that can reshape the learning paradigm, especially concerning Learning Management Systems (LMS). In this paper, I propose a cloudbased AI-enhanced LMS architecture to improve classroombased teaching with the integration of intelligent modules, including learning analytics, personalized learning prediction, adaptive content delivery, automated feedback, and interaction through natural language interfaces. The framework enables real-time analytics and dynamic feedback, automated customized pathways based on individual performance and engagement, and individual sense-making across the collective learning pathways. In this study, I show that the AI-enhanced LMS leads to better academic performance, higher completion rates, and improved engagement relative to traditional systems. In addition, a model to compensate for knowledge retention demonstrates the effect of AI-derived feedback on learning decay over time. The results suggest that AI-enabled LMS dramatically improves the precision of teaching, the quality of decisions by instructors, the retention of learning by students, and the teaching context, thus transforming the experience of teaching.