Research on Adaptive Learning Recommendation Algorithm for Vocational Education Based on Big Data Analysis

To achieve personalized recommendation for vocational education courses, this study designs an adaptive learning recommendation algorithm. It aims to meet the learning needs of learners at different stages. The study starts from the basic concept of big data-based adaptive learning. It reviews relevant models and work processes. Then it elaborates on the implementation process of this learning model. It also compares and analyzes its differences from traditional teaching. Applying big data adaptive learning helps students better master knowledge points. It improves academic performance and enhances learning enthusiasm. The system consists of three core components. They are a learning analysis module, an intelligent tutoring module, and a personalized recommendation engine. On this basis, a personalized teaching framework is constructed. The framework integrates learner profiling, precise content delivery, personalized learning path planning, and intelligent assessment with feedback.