Strategies and Practices of Intelligent Algorithms in Dynamic Allocation of Teaching Resources in Primary Education

Based on an analysis of the current state of teaching resources in primary education, this paper summarizes the challenges these resources are currently facing. In order to improve the above situation, it is proposed to introduce the theory of resource dynamic allocation strategy into primary education teaching. The fuzzy association algorithm, which leverages big data technology, extracts resource features, calculates the fuzzy association feature quantity of teaching resources, and facilitates the integration of these features in primary education through priority scheduling and dynamic allocation techniques. Based on the actual situation, determining the constraints and objective function, and finally completing the mathematical modeling work, the genetic algorithm can be used to solve the optimal dynamic allocation strategy of educational teaching resources. This paper used selected experimental data from simulation experiments to verify the dynamic allocation model of teaching resources. The recall of this paper’s method (0.261) is significantly higher than that of the other two methods (0.163, 0.155), and similarly, this paper’s method has superiority in utilization, load balancing, latency, efficiency, throughput, and practical satisfaction. This study is able to achieve efficient teaching resource allocation and provide better teaching resources for primary education teaching practice.