Adaptive Learning Systems: Personalized Curriculum Design Using LLM-Powered Analytics

Abstract—Large language models (LLMs) are revolutionizing the field of education by enabling personalized learning experiences tailored to individual student needs. In this paper, we introduce a framework for Adaptive Learning Systems that leverages LLM-powered analytics for personalized curriculum design. This innovative approach uses advanced machine learning to analyze real-time data, allowing the system to adapt learning pathways and recommend resources that align with each learner’s progress. By continuously assessing students, our framework enhances instructional strategies, ensuring that the materials presented are relevant and engaging. Experimental results indicate a marked improvement in both learner engagement and knowledge retention when using a customized curriculum. Evaluations conducted across varied educational environments demonstrate the framework’s flexibility and positive influence on learning outcomes, potentially reshaping conventional educational practices into a more adaptive and student-centered model.

Our framework adjusts learning paths dynamically, recommending resources tailored to each learner’s performance and preferences. Through continuous evaluations, instructional strategies evolve, offering users relevant materials to enhance engagement and retention. The framework’s efficacy was confirmed through thorough evaluations in various educational contexts, demonstrating its capability to reshape traditional teaching practices into an adaptable learning paradigm.