Prioritizing the teaching methods of ESD using an integrated fuzzy entropy–SAW algorithm (case study: technical and vocational schools)

Fatemeh Ghassami, Elham Yousefi, E. Salehi
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引用次数: 1

Abstract

Abstract The current environmental crisis has mainly a human-induced origin. In this regard, technical and vocational (T&V) graduates have an important role in the optimal use of environment and resources. Therefore, this research intends to find the best teaching method of education for sustainable development (ESD) in order to improve the behavior of those graduates toward the environment. For this purpose, the fuzzy entropy method was used to introduce and weight the sustainable development competency criteria of the T&V graduates. Then, the teaching methods were prioritized by applying a fuzzy Simple Additive Weighted (SAW) model. According to the results of the present paper, performance-based learning was the most appropriate method of ESD.
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基于模糊熵- saw集成算法的可持续教育教学方法优选(以技职学校为例)
当前的环境危机主要是人为造成的。在这方面,技术与职业(T&V)毕业生在优化利用环境和资源方面具有重要作用。因此,本研究旨在寻找可持续发展教育的最佳教学方法,以改善毕业生对环境的行为。为此,采用模糊熵法引入并加权了T&V毕业生的可持续发展能力标准。然后,应用模糊简单加性加权(SAW)模型对教学方法进行排序。根据本文的研究结果,基于绩效的学习是最合适的ESD教学方法。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
15
期刊介绍: Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.
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