Facing the urgent demand for high-quality talents in the intelligent transformation of logistics industry, the traditional teaching mode is not competent because of the disconnection between theory and practice. This paper puts forward and verifies an intelligent teaching mode of logistics management which combines Problem-Based Learning (PBL) and virtual simulation technology, and constructs a four-dimensional closed-loop teaching framework of "problem-simulation-data-optimization". By introducing enterprise's real inferior structure problem-driven learning, high-fidelity modeling and scheme verification are realized with the help of open source simulation platform, and comprehensive evaluation model and cognitive diagnosis mechanism are constructed based on learning process data, so as to realize dynamic optimization and personalized intervention of teaching content. The empirical research shows that this model has significantly improved students' ability of scheme design, systematic thinking and data-driven decision-making, and provided a low-cost and scalable intelligent teaching solution for logistics management education in colleges and universities.
Chunliang Lin (Sun,) studied this question.