Practical Exploration of Big Data Technology in Improving the Efficiency of English Education Resource Allocation and Utilization

Abstract

In order to make full use of educational big data for English education resource allocation and utilization, this paper is based on the standard Bottle Sheath Optimization Algorithm, which generates a random number through the sine-cosine function to update the random positions of individual Bottle Sheaths to improve the randomness and population diversity of the leader search process, improve the Bottle Sheath position updating method, and enhance the algorithm’s ability to perform global search. This paper develops a resource allocation model that can be employed for English education resource allocation. For the vast majority of single-peak and multi-peak functions, the success rate of SCSSA’s solution is 100%, and the performance of SCSSA’s search is significantly better than that of the comparison algorithms (p<0.05), and all of its convergence curves have the fastest decline. After using the model for allocation, the student-teacher ratio of the five districts and counties was improved, with a cumulative decrease of 86.72% in the student-teacher ratio, and the gap in the student-teacher ratio between districts and counties was reduced. However, the model’s optimization effect on the allocation of English books is limited, suggesting that further support of human and financial resources is needed in the allocation process.

Keywords

• bottled sea-sheath optimization algorithm
• sine-cosine algorithm
• resource allocation model
• english education
• 97m80