Enhanced decision-making through an intelligent algorithmic approach for multiple-attribute college English teaching quality evaluation with interval-valued intuitionistic fuzzy sets

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jinxia Huo, Weidong Zhang, Zhenmin Chen
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Abstract

To establish a student-centered teaching quality assurance system in English teaching in universities, it is necessary to establish an educational philosophy of survival based on quality, achieve student-centered learning, optimize the allocation of English teaching resources, and reform evaluation standards; To address the problems in English teaching, we need to raise awareness of the construction of a “student-centered” teaching quality assurance system, carry out “student-centered” teacher training activities, and improve teachers’ professional skills; At the same time, we will establish a student-centered English curriculum system, promote the reform and innovation of teaching models, establish a diversified English teaching evaluation system, and ensure the high efficiency and quality of English teaching in universities. The college English teaching quality evaluation is the MAGDM. Recently, the TODIM and MABAC technique has been employed to manage MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are employed as a useful tool for portraying uncertain information during the college English teaching quality evaluation. In this paper, the interval-valued intuitionistic fuzzy TODIM-MABAC (IVIF-TODIM-MABAC) technique is built to manage the MAGDM under IVIFSs. At last, the numerical example for college English teaching quality evaluation is employed to show the IVIF-TODIM-MABAC decision technique. The main contribution of this paper is outlined: (1) the TODIM technique based on MABAC has been extended to IVIFSs based on Entropy technique; (2) the Entropy technique is employed to manage weight based on score values under IVIFSs. (3) the IVIF-TODIM-MABAC technique is founded to manage the MAGDM under IVIFSs; (4) a numerical example for college English teaching quality evaluation and some comparative analysis is supplied to verify the proposed technique.
利用区间值直观模糊集的多属性大学英语教学质量评价智能算法增强决策能力
在大学英语教学中建立以学生为中心的教学质量保障体系,需要树立以质量求生存的教育理念,实现以学生为中心的学习,优化英语教学资源配置,改革评价标准;针对英语教学中存在的问题,要提高对构建 "以学生为中心 "的教学质量保障体系的认识,开展 "以学生为中心 "的师资培训活动,提高教师的专业技能;同时,建立以学生为中心的英语课程体系,推进教学模式的改革与创新,建立多元化的英语教学评价体系,确保大学英语教学的高效率和高质量。大学英语教学质量评价是MAGDM。最近,TODIM 和 MABAC 技术被用于管理 MAGDM。在大学英语教学质量评估过程中,区间值直观模糊集(IVIFS)被用作描述不确定信息的有效工具。本文构建了区间值直观模糊 TODIM-MABAC(IVIF-TODIM-MABAC)技术来管理 IVIFS 下的 MAGDM。最后,以大学英语教学质量评价为例,展示了 IVIF-TODIM-MABAC 决策技术。本文的主要贡献概述如下:(1)基于 MABAC 的 TODIM 技术已扩展到基于 Entropy 技术的 IVIFS;(2)采用 Entropy 技术管理 IVIFS 下基于分值的权重。(3) 建立了 IVIF-TODIM-MABAC 技术来管理 IVIFS 下的 MAGDM;(4) 提供了一个大学英语教学质量评价的数值示例和一些比较分析来验证所提出的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.10
自引率
0.00%
发文量
22
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