通过双极复杂的犹不决的模糊的Aczel-Alsina权力聚合运营商在高等教育系统中实施学习管理系统 (LMS):对中国的案例审查
Lijun Ma1, Zeeshan Ali2, Shi Yin3
1College of Land and Resources, Hebei Agricultural University, Baoding, China.
PloS one
|April 4, 2024
概括
本研究使用新型模糊集合理论确定了COVID-19期间学习管理系统 (LMS) 最关键的因素. 这些发现为优化教育技术以应对未来挑战提供了洞察力.
科学领域:
- 教育技术的教育技术
- 模糊的集合理论 模糊的集合理论
- 决策科学 决策科学 决策科学
背景情况:
- 学习管理系统 (LMS) 对于教育提供至关重要.
- 随着COVID-19的流行,人们需要优先考虑LMS的功能.
- 关键因素包括可访问性,混合学习,协作,评估和行政效率.
研究的目的:
- 在COVID-19大流行期间确定LMS最重要的因素.
- 引入和应用新的双极复杂犹模糊 (BCHF) 设置技术.
- 开发和评估LMS特征优先级的新决策运营商.
主要方法:
- 导出双极复杂的犹不决的模糊 (BCHF) 集合技术.
- 对代数和Aczel-Alsina运算定律的评估.
- 编制了 BCHF Aczel-Alsina 的功率平均和几何运算符 (BCHFAAPA,BCHFAAPWA,BCHFAAPG,BCHFAAPWG).
- 应用多属性决策 (MADM) 技术.
主要成果:
- 建议新的BCHF运营商用于决策.
- 应用MADM技术来优先考虑LMS因素.
- 将拟议的方法与现有运营商进行比较,以验证有效性.
结论:
- 该研究为评估和优先考虑LMS特征提供了一个强大的框架.
- 新型BCHF运营商在复杂的决策场景中表现出能力.
- 调查结果为教育技术的开发和实施提供了宝贵的见解.
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