Traditional learning path planning methods often fail to meet the individualized needs of learners. In this paper, a dynamic learning path planning method based on neural network is studied by constructing a student model. Firstly, the construction method of the student model is designed, and the Item Response Theory (IRT) is used as a test method for the cognitive level of students, which realizes the dynamic acquisition of student information. A neural network-based cognitive collaborative filtering model was constructed, which models learners’ learning behaviors and interests, and customizes personalized dynamic learning paths for learners after assessing their cognitive levels and learning difficulties. The collaborative filtering algorithm in this paper performs better than the other four algorithms in terms of accuracy and coverage, and the accuracy and coverage rate of the generated knowledge point sequences reach 98.9% and 93.6% respectively, and the performance of the students in the experimental group has been significantly improved under the application of the dynamic learning path generation model of blended teaching in this paper, indicating that the effectiveness and feasibility of the personalized learning path generation model in this paper are excellent and are expected to be further promoted.