Undergraduate teaching audit and evaluation using an extended MABAC method under q ‐rung orthopair fuzzy environment

Abstract

Undergraduate teaching audit and evaluation (UTAE) is a new type of evaluation pattern, which is extremely important for a university to improve its quality assurance system and enhance teaching quality. Selecting an optimal university for benchmarking through UTAE to promote the quality of teaching can be regarded as a complex multicriteria decision making (MCDM) problem. Furthermore, in the process of UTAE, experts' evaluations over the teaching quality of universities are often imprecise and fuzzy due to the subjective nature of human thinking. In this paper, we propose a new UTAE approach based on q-rung orthopair fuzzy sets and the multiattribute border approximation area comparison (MABAC) method for evaluating and selecting the best university for benchmarking. The introduced method deals with the linguistic assessments given by experts by using q-ROFSs, assigns the weights of audit elements based on the indifference threshold-based attribute ratio analysis method, and acquires the ranking of universities with an extended MABAC method. The feasibility and effectiveness of the proposed q-rung orthopair fuzzy MABAC method is demonstrated through a realistic UTAE example. Results show that the UTAE method being proposed is valid and practical for UTAE.

q ‐Rung orthopair fuzzy decision‐making framework for integrating mobile edge caching scheme preferences

“…Remark From Table 13, we will find that the vast majority of optimal MECSs are consistent with the proposed algorithm based on TAOV, which fit our normal perception. However, in addition to the above antilogarithm by negative and zero issue 33 and parameter selection issue, 43 there are still two diverse types of irrational or counterintuitive phenomenon in MCDM process when obtaining the optimal MECS, which are discussed in the following. …”

“…The q-ROF multiattribute border approximation area comparison (MABAC) method was successfully applied in undergraduate teaching audit and evaluation. 43 Rani and Mishra 44 investigated q-ROF weighted aggregated sum product assessment (WASPAS) framework for fuel technology selection. Tian et al 45 presented a revised TODIM based on prospect theory for choosing green supplier under q-ROF environment.…”

“…4. The existing methods used to solve MCDM problems have counterintuitive situations (caused by parameter selection 43 and caused by score function 42 and caused by AOs [12][13][14][15][16][17]19,[21][22][23][24][25][26][27]29,30 ), antilogarithm by negative and zero issue 33 and DBZ issue. 28 The DM's selection of the best option may not be worthwhile, or it may be impractical.…”

“…In the following, we give a comparison with some existing weight determining models, including objective weight determining models 20,37,43,44 and combined weight determining models. 33,39,40 1.…”

Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model

“…In order for the alternative A i to be chosen as the best from the set, it is necessary for it to belong, by as many as possible criteria, to the upper approximate area ( ) [ 43 ]. The higher value indicates that the alternative is closer to the ideal alternative, while the lower value q indicates that the alternative is closer to the anti-ideal alternative [ 44 ].…”