Evaluation of English online teaching based on remote supervision algorithms and deep learning
Han Yong-qing
Abstract
The English online teaching automatic evaluation system is unstable in actual teaching evaluation. Therefore, how the automatic evaluation system can better adapt to high school teaching also needs a more in-depth theoretical and practical discussion. According to the actual needs of English online teaching, this article combines remote supervision and deep learning algorithms, builds a system structure for the English online teaching evaluation process, and simulates and analyzes the application of supervision algorithms in the teaching process. Moreover, this article evaluates the actions and status of the student’s learning process from the aspects of teacher evaluation and student evaluation, and also scores the teacher’s teaching process. In order to study the practical effect of this system in English online teaching, this paper designs experiments to evaluate the model online English teaching effect. The research results show that the model constructed in this paper has good performance.