This study focuses on the “blockchain + education” perspective, focusing on the integration of edge computing in the higher education resource sharing system. Through the benign interaction between blockchain and edge computing in the system data management system, the security and efficiency of data storage and transmission of shared resources in the system can be improved. In order to improve the performance of the system’s educational resource sharing, this paper utilizes the node identification model on the basis of the traditional PBFT consensus algorithm for the selection of master nodes and the monitoring of malicious nodes. Meanwhile, in order to ensure the balanced allocation of educational resources within the sharing system as much as possible, this paper utilizes the differential evolution (DE) algorithm for the balanced allocation of system resources and the educational resources within the system. The results of experiments and system tests show that the improved PBFT consensus algorithm (NR-PBFT) in this paper shows obvious superiority in tests such as throughput and latency. Although the educational resource allocation model performs poorly in the allocation of resources with larger technology such as digital books, the results for the allocation of teacher resources can effectively prove the effectiveness of the resource allocation model in this paper. In addition, the system test results also show that the system in this paper has good performance, and the introduction of edge computing can significantly reduce the packet loss rate of resource sharing, which has considerable application value.