<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The right of education and discipline is an important way of school education and teaching management, teachers to fulfill the teaching and educating people, the implementation of the fundamental task of moral education. This paper firstly discusses the dilemma of exercising the right to discipline teachers in education, and also analyzes the legal nature of the right to discipline in education and the impact on the emotional performance of teachers and students in the process of exercising the right. Secondly, cochlear filtering combined with CNN and LSTM network is introduced to extract the speech characteristics of teachers in the process of exercising the right of education and discipline, and a hybrid neural network model is used to realize the recognition and prediction of students’ auditory emotions. Finally, in order to verify the effectiveness of the method of this paper, experimental test analysis was carried out, and a comprehensive rule of law guarantee proposal was given in the process of exercising the right of teachers’ educational discipline. The results show that the maximum value of the intensity of the teacher’s speech signal after processing using the cochlear filter is 78.28dB, and the difference with the original signal is only 0.32%. The accuracy of recognizing students’ auditory emotions reached 90.48% after over 50 iterations. Under the background of big data, the right to discipline teachers in education needs to be analyzed with the help of technology for the data analysis of the appropriateness of exercise, and it is united in a number of aspects, such as strengthening the legislation, standardizing the implementation, strengthening the supervision, and perfecting the relief, as a way to help the comprehensive rule of law operation of the right to discipline teachers in education.</p>
</abstract>

The right of education and discipline is an important way of school education and teaching management, teachers to fulfill the teaching and educating people, the implementation of the fundamental task of moral education. This paper firstly discusses the dilemma of exercising the right to discipline teachers in education, and also analyzes the legal nature of the right to discipline in education and the impact on the emotional performance of teachers and students in the process of exercising the right. Secondly, cochlear filtering combined with CNN and LSTM network is introduced to extract the speech characteristics of teachers in the process of exercising the right of education and discipline, and a hybrid neural network model is used to realize the recognition and prediction of students’ auditory emotions. Finally, in order to verify the effectiveness of the method of this paper, experimental test analysis was carried out, and a comprehensive rule of law guarantee proposal was given in the process of exercising the right of teachers’ educational discipline. The results show that the maximum value of the intensity of the teacher’s speech signal after processing using the cochlear filter is 78.28dB, and the difference with the original signal is only 0.32%. The accuracy of recognizing students’ auditory emotions reached 90.48% after over 50 iterations. Under the background of big data, the right to discipline teachers in education needs to be analyzed with the help of technology for the data analysis of the appropriateness of exercise, and it is united in a number of aspects, such as strengthening the legislation, standardizing the implementation, strengthening the supervision, and perfecting the relief, as a way to help the comprehensive rule of law operation of the right to discipline teachers in education.

Problem Analysis and Legal Protection of the Exercise of Teachers’ Educational Disciplinary Rights Based on the Background of Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The right of education and discipline is an important way of school education and teaching management, teachers to fulfill the teaching and educating people,...

Problem Analysis and Legal Protection of the Exercise of Teachers’ Educational Disciplinary Rights Based on the Background of Big Data

Data publikacji: 05 gru 2023

Zakres stron: -

Otrzymano: 06 mar 2023

Przyjęty: 15 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01350

Słowa kluczowe
Educational disciplinary rights, Cochlear filters, Speech feature extraction, Hybrid neural networks, Auditory emotions

© 2023 Junchen Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Problem Analysis and Legal Protection of the Exercise of Teachers’ Educational Disciplinary Rights Based on the Background of Big Data

Data publikacji: 05 gru 2023

Zakres stron: -

Otrzymano: 06 mar 2023

Przyjęty: 15 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01350

Słowa kluczoweEducational disciplinary rights, Cochlear filters, Speech feature extraction, Hybrid neural networks, Auditory emotions

© 2023 Junchen Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Educational disciplinary rights, Cochlear filters, Speech feature extraction, Hybrid neural networks, Auditory emotions