Online English Education Ability Evaluation System Based on RBF Algorithm

With the continuous development of information technology, online learning has become an important, universal, efficient, and convenient way in people's daily lives, and is widely used in the field of education. However, studying online education systems as an emerging phenomenon has only emerged in recent years and has achieved certain results. This article was based on the radial basis function (RBF) algorithm to evaluate and design control strategies for English remote video websites, as well as related data statistical analysis and processing. The main implementation is the construction of platform models and the establishment of functional models, selection of testing methods, and the organization of user feedback information, as well as the construction of backend database management functional modules. When calculating the value of the output layer, the same function as the radial basis function was used for calculation. Adopting the above methods can greatly improve the accuracy of testing. Afterwards, this article conducted performance testing on the system. The test results showed that the accuracy of the system could reach over 85%. The recall rate was over 83%, the response time was between 2s and 3s, and the resource utilization rate is over 94
^%
. Research on online English education ability evaluation system based on RBF algorithm has found that RBF algorithm can be used for predicting student performance in online English education environment. By analyzing and modeling students' historical learning data, the system can use RBF algorithm to predict students' performance on different tasks and question types, including grades, mastery of knowledge points, and learning progress.