The exploratory factor analysis (EFA) method is regarded as one of the most well-known statistical multivariate analysis methods, which is used to discover the underlying structure of a relatively large set of variables. The EFA has a wide range of applications due to its properties such as data reduction. In this paper, the fuzzy EFA (FEFA) method was developed to maintain the uncertain nature of the data related to the variables. The FEFA method is used to construct an e-learning service quality assessment model. Several assignment criteria have been classified to identify the strengths and weaknesses of an e-learning system, to provide an information system for educational institutions, and rank these information systems. The assessment measures of an e-learning service are determined from the students’ and users’ perspectives by exploring previous models and using open questionnaires. In addition, due to the typical uncertainty of assessment indicators, a questionnaire was designed with triangular fuzzy numbers to increase the value of the information collected from evaluating e-learning users. By implementing the developed FEFA, an e-learning assessment model was constructed with 13 latent variables including reliable infrastructure, benefits and financial support, government support, perception and knowledge, educational facilities, quality of holding classes, entrance conditions, meeting the needs of students, process of education, planning, flexibility of courses, professors’ opinion, and information exchange.

探索性因子分析（EFA）方法被认为是最著名的统计多元分析方法之一，用于发现相对较大的变量集的基础结构。EFA由于具有数据缩减等特性而具有广泛的应用范围。本文开发了模糊EFA（FEFA）方法来保持与变量相关的数据的不确定性。FEFA方法用于构建电子学习服务质量评估模型。已经对几种分配标准进行了分类，以识别电子学习系统的优点和缺点，为教育机构提供信息系统，并对这些信息系统进行排名。通过学习以前的模型并使用开放式问卷调查，从学生和用户的角度确定电子学习服务的评估方法。此外，由于评估指标的典型不确定性，设计了带有三角模糊数的问卷，以增加从评估电子学习用户中收集的信息的价值。通过实施已开发的FEFA，构建了包含13个潜在变量的电子学习评估模型，包括可靠的基础设施，收益和财务支持，政府支持，看法和知识，教育设施，举办课程的质量，入学条件，满足学生的需求，教育过程，计划，课程的灵活性，教授的观点以及信息交流。此外，由于评估指标的典型不确定性，设计了带有三角模糊数的问卷，以增加从评估电子学习用户中收集的信息的价值。通过实施已开发的FEFA，构建了包含13个潜在变量的电子学习评估模型，包括可靠的基础设施，收益和财务支持，政府支持，看法和知识，教育设施，举办课程的质量，入学条件，满足学生的需求，教育过程，计划，课程的灵活性，教授的观点以及信息交流。此外，由于评估指标的典型不确定性，设计了带有三角模糊数的问卷，以增加从评估电子学习用户中收集的信息的价值。通过实施已开发的FEFA，构建了包含13个潜在变量的电子学习评估模型，包括可靠的基础设施，收益和财务支持，政府支持，看法和知识，教育设施，举办课程的质量，入学条件，满足学生的需求，教育过程，计划，课程的灵活性，教授的意见和信息交换。