A Fuzzy Neural Network-Based Evaluation Method for Physical Education Teaching Management in Colleges. (24th November 2022)

• Record Type: Journal Article
• Authors: Zhao, Bo; Liu, Yanjin
• Other Names: Mumtaz Shahid Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2022(2022)
• Publication Date: 2022-11-24
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2022/2365320
• Languages: English
• ISSNs: 1687-5265

Abstract

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 F 1 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 F 1 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.