Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach

Yeleny Zulueta-Veliz, Aylin Estrada-Velazco, Yoisbel Tabares-Leon
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Abstract

Student satisfaction provides a students' perception of their educational experiences in an educational setting. As online learning is growing, institutions and instructors have become more interested in knowing what factors influence students' satisfaction in online learning setting. This study presents a novel approach for evaluating students' satisfaction in online postgraduate courses through a fuzzy linguistic approach for computing with words which addresses. Our approach models the students' satisfaction as a linguistic variable which reflects the perceptual nature of this concept; it models the satisfaction evaluation as a linguistic multi-attribute decision-making problem; it gathers perceptions of students according to 14 attributes for 18 online courses; it offers a methodological framework based on the 2-tuple linguistic model for computing with words through which performs a linguistic multi-step incremental aggregation process that outputs at each step partial or global self-contained and informative results expressed in a common linguistic domain.
用模糊语言学方法评价研究生在线课程学生满意度
学生满意度提供了学生在教育环境中对其教育经历的感知。随着在线学习的发展,机构和教师对了解影响学生在线学习满意度的因素越来越感兴趣。本研究提出了一种新的方法来评估在线研究生课程的学生满意度,通过模糊语言的方法来计算词的地址。我们的方法将学生的满意度建模为一个语言变量,反映了这一概念的感性本质;将满意度评价建模为语言多属性决策问题;它根据18门在线课程的14个属性收集学生的看法;它提供了一种基于二元组语言模型的方法框架,用于单词计算,通过该模型执行语言多步骤增量聚合过程,在每一步输出部分或全局自包含的信息结果,并用公共语言域表示。
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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