Despite the critical importance of education management assessment in assessing intelligent student management, the issue of erroneous result evaluation persists. Traditional evaluation techniques struggle to match the system’s accuracy and efficiency criteria because of the high complexity and massive quantity of data, rendering the assessment unrealistic. So, to assess and analyze education management in a novel way, this research suggests an ANN algorithm. In order to minimize interference elements in education management assessment, the indicators are split according to the needs of the evaluation, and the information system data is managed using database theory. The next step is to use database theory to assess intelligent student management assessment management, create an evaluation scheme for educational management, and then thoroughly examine the evaluation outcomes. When compared to more conventional evaluation methods, MATLAB simulations reveal that ANN algorithms provide superior accuracy, efficacy, and educational management efficiency when building intelligent student management evaluation information systems.