A Fuzzy Neural Network-Based Evaluation Method for Physical Education Teaching Management in Colleges

Author:

Zhao Bo12,Liu Yanjin3ORCID

Affiliation:

1. Chengdu Sport University, Chengdu, Sichuan 610041, China

2. Sichuan Zhuoyi Dream Education Technology Co Ltd, Chengdu, Sichuan 610000, China

3. Sichuan International Education Development Research Center, Chengdu 611130, Sichuan, China

Abstract

A novel Fuzzy Neural Network (FNN) teaching quality assessment model of physical education (PE) is presented at colleges and universities to enhance the validity of PE teaching quality evaluation. It is being done to enhance the accuracy of quality evaluations of PE instruction. In the first phase, out of 4 aspects of teaching material, teaching method, teaching attitude, and teaching effect, a multi-index assessment process of university physical education teacher performance based on the analytic hierarchy process (AHP) is created. The effectiveness of college PE instructors is assessed using this approach. The FNN model is used to develop a teaching quality assessment model for college PE courses. The FNN’s parameter is the score data, and the FNN’s output vector is equipped with better college PE (excellent, good, average, and low). In terms of assessing the instructional excellence of PE courses in colleges and universities, FNN has been proven to have superior classification accuracy, specificity, sensitivity, and F1 score when compared to other methods. When compared to other countries, this is the case. The proposed approaches resulted in a score of 96% for accuracy, 95% for specificity, 90% for sensitivity, and an F1 score of 94% for performance. The effectiveness of the proposed approach is shown by comparing the outcomes to those of standard physical education teaching strategies.

Funder

Sichuan International Education Development Research Center

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3