Online Teaching Quality Evaluation of Business Statistics Course Utilizing Fermatean Fuzzy Analytical Hierarchy Process with Aggregation Operator

Abstract

Due to the full-scale outbreak of COVID-19, many universities have adopted the way of online teaching to ensure the orderly development of teaching plans and teaching contents. However, whether online and offline teaching can develop homogeneously and how to ensure the teaching effect is a major challenge for colleges and universities. Therefore, it is urgent to construct a reasonable index system and evaluation approach for the quality of network teaching. Combined with the influencing factors and characteristics of online teaching, this study first puts forward a multi-index evaluation index system and then proposes a novel evaluation method for online teaching based on the analytical hierarchy process (AHP) and Dombi weighted partitioned Muirhead Mean (PMM) operator under Fermatean fuzzy (FF) environment. This presented method not only adapts to changeable evaluation information but also handles the elusive interrelationships among indexes, realizing the flexibility and comprehensiveness both in form and in the polyaddition process. The applicability and feasibility of this presented method are then discussed through the practical online teaching quality evaluation of a business statistics course case, and a group of tentative about the sensitivity analysis and comparative analysis further demonstrates the effectiveness and flexibility of the proposed method.

A Heterogeneous Information-Based Multi-Attribute Decision Making Framework for Teaching Model Evaluation in Economic Statistics

“…Because of this characteristic, in recent years, the teaching model of economic sta-tistics in North America, Britain, Japan, and other countries has paid more attention to the cultivation of data collection, processing, and analysis and has strengthened the statistical practice in the teaching process [25]. Under such a trend, statistical educators in China have actively discussed the research and innovation of teaching models, and numerous achievements of statistical teaching models have emerged [26].…”

“…In particular, the understanding and embodiment of the characteristics of the statistics specialty are insufficient, so it is difficult to directly evaluate the teaching model of economic statistics. (2) The teaching model of economic statistics presents the characteristics of multidimensiond, systematicness, and complexity [25,26]. In regard to the content, it involves the whole process of teaching, from theoretical knowledge to practical skills.…”

“…It refers to students' core professional qualities or skills. For students majoring in economic statistics, competitive ability includes data collection ability, the ability to analyze data with models, and the ability to use relevant statistical software [26]. This attribute uses the form of real numbers.…”

“…(2) Academic Research Creation of academic atmosphere (C3). This attribute reflects the ability to create an academic atmosphere [24,26]. C3 makes it difficult to give quantitative information directly, so it adopts the form of linguistic numbers to collect the information of the evaluator.…”

“…(3) Master of Knowledge Understanding of knowledge (C5). It refers to students' understanding and mastery and reflects students' knowledge understanding and mastery of economic statistics [26,30]. It also has the characteristics of subjectivity, and it is often difficult for evaluators to give accurate evaluation information.…”