An improved GRA algorithm for teaching quality evaluation of college physical education based on the probabilistic simplified neutrosophic sets

课程 滞后 计算机科学 概率逻辑 质量(理念) 体育 简单(哲学) 集合(抽象数据类型) 数学教育 排名(信息检索) 教学方法 算法 人工智能 数学 心理学 教育学 统计 哲学 认识论 程序设计语言
作者
K. Gao,Fangqing Yu
出处
期刊:Journal of Intelligent and Fuzzy Systems [IOS Press]
卷期号:: 1-12
标识
DOI:10.3233/jifs-231728
摘要

With the emergence of various new teaching concepts and teaching models in colleges and universities, the original evaluation system can no longer fully meet the requirements of the current development of physical education curriculum teaching in colleges and universities. Thus, reducing the judgment and guidance of evaluation on physical education curriculum teaching shall result in the development of physical education curriculum teaching quality evaluation lagging behind the development of teaching and being in a passive position. Therefore, it is particularly important to establish a new evaluation standard system for the teaching quality of physical education courses. The teaching quality evaluation of college physical education (PE) is viewed as multiple attribute decision-making (MADM). In this paper, an enhanced probabilistic simplified neutrosophic grey relational analysis (PSN-GRA) method is designed for MADM. Then, in the environment of probabilistic simplified neutrophil set (PSNSs), the PSN-GRA method and CRITIC method are combined to rank the alternative schemes, and a numerical example of college physical education teaching quality evaluation proves the practicability of the new method and compares it with other methods. The results show that this method is simple, effective and simple in calculation.

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