Research on Education Teaching Quality Analysis Based on the Neural Network Model

Author:

Zhu Ying1ORCID

Affiliation:

1. Zhejiang Institute of Economics and Trade, Hangzhou 310018, Zhejiang, China

Abstract

Universities emphasize quality review and monitoring. To effectively evaluate classroom teaching effectiveness, a trustworthy model of teaching quality evaluation is required. Due to the fact that teaching is a dynamic process, numerous elements influence teaching quality, and the link between assessment index and teaching effect is complex and nonlinear. There are numerous methods for measuring the quality of classroom instruction, but the vast majority of it relies on a single machine learning algorithm, making it difficult to construct an accurate and reliable mathematical model. In this paper, we employ the AdaBoost’s multicore neural network learning algorithm to learn several weak classifiers and combine them into a single strong classifier. We also transfer the classification probabilities into teaching quality outcomes to obtain the final teaching quality results. Our model offers a new, effective way for evaluating the quality of classroom instruction, and it can serve as a solid theoretical resource for reforming classroom instruction.

Funder

Fundamental Research Funds for Provincial Universities of Zhejiang Institute of Economics and Trade

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

Reference28 articles.

1. A new discussion on classroom teaching quality and evaluation criteria in higher education;Z. Zhao;Chinese Higher Education,2019

2. Research on the Evaluation Model of Teaching Quality in Colleges and Universities Based on gray System Theory;Y. Fan;University Education,2019

3. The construction of the evaluation system of the quality of practical teaching in higher education law majors;H. Tan;Higher Education Forum,2018

4. Research on the construction of project teaching quality evaluation index system;T. Zheng;Chinese Journal of Multimedia and Network Teaching,2019

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