Students have different competencies, learning preferences, and prerequisite knowledge, but traditional LMS platforms provide largely the same learning experience to everyone. Many also struggle with university-level English learning, heavy workloads, and forgotten prerequisite concepts. We propose an AI-powered personalized learning companion that analyzes LMS activities and assessment results to build a student competence profile, identify weak areas, and provide course-grounded Q&A, personalized explanations, short videos, notes, exercises, quizzes, and prerequisite refreshers.

The solution is feasible using existing LMS data together with current LLM, RAG, and content-generation technologies, without training a new foundation model. The next step is to pilot the system in one course, evaluate its ability to improve learning outcomes and engagement, and then expand it to more courses with richer student profiles and cross-course prerequisite modeling.