Abstract
In order to deal with the problems of low evaluation accuracy and long evaluation time in the traditional English classroom teaching quality monitoring and evaluation methods, this study proposes an English classroom teaching quality monitoring and evaluation method based on big data. According to the selection principle of English classroom teaching quality monitoring factors, this study analyzes the English classroom teaching quality monitoring factors, constructs the English classroom teaching quality monitoring index system, obtains the monitoring index data, filters and compresses the monitoring data, and takes the preprocessed English classroom teaching quality monitoring data as the evaluation index. This study uses the principal component analysis method to calculate the weight of the English classroom teaching quality evaluation index and constructs an English classroom teaching quality evaluation model. The simulation results show that the proposed method has high accuracy and short evaluation time.
Highlights
With the rapid development of higher education, the guarantee and improvement of its education quality have attracted the attention of the whole society
The current situation of multimedia teaching quality evaluation is analyzed, and the multimedia teaching quality evaluation index is constructed. en, the grey correlation analysis method is used to determine the weight of the multimedia teaching quality evaluation index, and the neural network is used to establish the classifier of multimedia teaching quality grade
In view of the problems existing in the above methods, this study proposes an English classroom teaching quality monitoring and evaluation method based on big data and verifies the effectiveness of this method through simulation experiments, which lays a certain foundation for English classroom teaching and the improvement of English achievement
Summary
Based on the collected monitoring data of English classroom teaching quality, this chapter is mainly divided into two parts: data filtering processing and data compression sensing processing. e former mainly removes the collected data noise, and the latter improves the efficiency of English classroom teaching quality evaluation [17]. e following is a specific analysis. E former mainly removes the collected data noise, and the latter improves the efficiency of English classroom teaching quality evaluation [17]. Input the collected English classroom teaching quality monitoring data x(t). Think independently, analyze, and solve problems v31 Respect teachers and be willing to help others v41 Collective sense of honor v42 same time, the congestion of a large number of data will cause data loss, which will reduce the efficiency of English classroom teaching quality evaluation. E monitoring data of English classroom teaching quality are expressed sparsely, and the formula is as follows: x′ ψs,. E function of the measurement matrix is to reduce the dimension of English classroom teaching quality monitoring data and ensure the minimum information loss of x. Where x represents the number of nonzero elements in x; α stands for thinning
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