Year: 2025
Type: article
Abstract: Under the background that physical education has been paid more and more attention, the cultivation of students' physical literacy has become the top priority of education.Teaching and helping students develop their core competencies at the same time.Under the background of big data application, the traditional teaching evaluation system of physical education in colleges and universities in our country is difficult to adapt to the social development trend, and gradually exposes more and more problems, which affects the good development of physical education in colleges and universities and universities.In order to define the physical education in-depth teaching and its growth, it is very important to formulate and implement the physiscal education in-depth teaching evaluation index system.Therefore, starting from the important evaluation technology to improve the evaluation indicators of physical education in physical education colleges, this study jointly proposes a triangular distribution function and a random simulation algorithm.On the other hand, the improved analytic hierarchy process (MCAHP) based on stochastic simulation algorithm has been proved to be effective in alleviating the subjective bias implicit in the scoring data extracted from the questionnaire, and in the process, the evaluation indicators of physical training and physical education have been greatly improved.For a good application, the superiority of the method in this paper can be seen through a large number of analysis and index analysis.Therefore, this paper revises the empirical analysis results of the importance of physical education teaching evaluation indicators in physical education colleges, in order to draw more accurate and scientific conclusions, and make suggestions for development.Research on the Evaluation Model of Physical Education in the Future.
Author: Huang, Shouqing
Institution: Wenzhou University of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4409604974