Neural Network Algorithm for English Teaching Evaluation

Wu, Wenming

doi:10.1007/978-981-16-4258-6_193

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…In addition to the evaluation of schools and teachers, there are also diverse subjects such as student self-evaluation. Reform of the evaluation system has made the content more extensive, the forms more diverse, the target requirements higher, and the methods more flexible, which requires teachers to pay attention to the quality of classroom teaching [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Optimization of English Classroom Quality Evaluation Model with AHP

Shuang

2022

Security and Communication Networks

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This work takes English classroom quality as the research object. Improving the quality of English classrooms is not only an unavoidable requirement for the current curriculum reform’s deepening and development, but also a necessary development trend of the evaluation system reform, and the call of the majority of classroom teaching position. The country invested financial, labor, and material resources, and students have also invested a lot of study time, but the English classroom effect is not satisfactory. The main issue is a lack of adequate evaluation of the teaching process as well as a scientific, fair, and practical technique for assessing classroom quality. This work combines AHP and BP networks to propose a method (AHP-IGA-BP) for evaluating the quality of English classrooms. The content of this work is as follows: (1) A hierarchical model and index system for English classroom quality evaluation based on AHP are constructed. Through the process of constructing a judgment matrix, single-level ranking, consistency check, and total-level ranking, the complete English classroom quality evaluation index weight is finally obtained, which realizes the transformation of subjective information into data with specific weight. (2) combine the original data with the aforementioned index weight data produced using AHP, as well as the neural network’s learning and training samples. Build a BP network structure to effectively evaluate the quality of English classrooms. (3) The BP network is optimized based on the improved GA algorithm.

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Section: Introductionmentioning

confidence: 99%

Optimization of English Classroom Quality Evaluation Model with AHP

Shuang

2022

Security and Communication Networks

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“…It is a feed-forward neural network with a strong global optimization ability. It is widely used in the fields of signal processing, image processing, and pattern recognition [26].…”

Section: Rbf Neural Networkmentioning

confidence: 99%

An Evaluation Method of English Teaching Based on Machine Learning

2022

Mathematical Problems in Engineering

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The evaluation of English teaching is becoming increasingly popular. An English teaching evaluation approach based on machine learning is developed in order to improve the accuracy of the English teaching evaluation and reduce the inaccuracy of the English teaching evaluation. Firstly, the specific meaning of the English classroom teaching evaluation is analyzed, the selection principle of the English classroom teaching evaluation index is designed, and the selection of the English teaching evaluation index is completed. Second, the machine learning technology is examined, and the analytic hierarchy process is used to produce the judgment of the English teaching assessment index. Then, using the principal component analysis, calculate the eigenvalues and eigenvectors of the evaluation indicators to determine the contribution of the English teaching quality assessment indicators. Finally, create the English teaching evaluation weight calculation model using the machine learning approach, and acquire the English teaching evaluation’s complete results using the fuzzy evaluation method. The experimental results show that when the number of iterations is 60, the normalized mean square error of the effectiveness of the method is 0.03, and when the number of tests is 30, the effectiveness of the method is 0.99; this shows that the method can improve the effectiveness of the English teaching evaluation. It can effectively reduce the error of the English teaching evaluation.

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“…e improvement of English course learning quality is an indispensable part of the modernization of national education, and the scienti c, rational, and timely improvement of English course learning quality evaluation plays a key role [1][2][3]. However, the limitations of traditional English course learning quality evaluation methods have made them controversial.…”

Section: Introductionmentioning

confidence: 99%

Generation and Research of Online English Course Learning Evaluation Model Based on Genetic Algorithm Improved Neural Set Network

Song

2022

Computational Intelligence and Neuroscience

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The rationality and timeliness of the comprehensive results of English course learning quality are increasingly important in the process of modern education. There are some problems in the scientific evaluation of English course learning quality and teachers’ own English course learning, such as the need for proper adjustment and improvement. Based on the improved network theory of genetic algorithm, this paper takes an online English course learning quality evaluation model and uses MATLAB 7.0 to write the graphical user interface of the neural set network English course learning quality prediction model. The model uses the genetic algorithm of adaptive mutation to optimize the initial weights and values of the neural set network and solves the problems of prediction accuracy and convergence speed of English course learning quality evaluation results. Simulation experiments show that the neural set network has a strong dependence on the initial weights and thresholds. Using the improved genetic algorithm to optimize the initial weights and thresholds of the neural set network reduced the time for the neural set network to find the weights and thresholds that meet the training termination conditions, the prediction accuracy was increased to 0.897, the prediction accuracy was 78.85%, and the level prediction accuracy was 84.62%, which effectively promoted the development of online English course learning in colleges and the continuous improvement of teachers’ English course learning level.

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Neural Network Algorithm for English Teaching Evaluation

Cited by 4 publications

References 2 publications

Optimization of English Classroom Quality Evaluation Model with AHP

Optimization of English Classroom Quality Evaluation Model with AHP

An Evaluation Method of English Teaching Based on Machine Learning

Generation and Research of Online English Course Learning Evaluation Model Based on Genetic Algorithm Improved Neural Set Network

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