Research on the assessment of classroom teaching quality with q‐rung orthopair fuzzy information based on multiparametric similarity measure and combinative distance‐based assessment

The assessment of classroom teaching quality is critically important for producing a positive incentive and guidance role to improve service and management of universities, stimulating the enthusiasm of teachers, enhancing the teacher’s teaching ability, and improving the quality of talent training. In considering the case of teaching quality evaluation, the essential question that arises concerns strong ambiguity, fuzziness, and inexactness. The q‐rung orthopair fuzzy sets ( q‐ROFSs) dealing the indeterminacy characterized by membership degrees and nonmembership degrees are a more flexible and effective way to capture indeterminacy. In this paper, firstly, the new score function for q‐rung orthopair fuzzy number is initiated for tackling the comparison problem. Subsequently, a new distance measure for q‐ROFSs with multiple parameters is studied along with their detailed proofs. The various desirable properties among the developed similarity measures and distance measures have also been derived. Then, the objective weights of various attributes are determined via antientropy weighting method. Also, we develop the combined weights, which can reveal both the subjective information and the objective information. Moreover, two algorithms to solve q‐rung orthopair fuzzy decision‐making problem by combinative distance‐based assessment and multiparametric similarity measure are presented. Later, the feasibility of approaches is demonstrated by a classroom teaching quality problem, along with the effect of the different parameters on the ordering. Finally, a comparison between the proposed and the existing decision‐making methods has been performed for showing their effectiveness. The salient features of the proposed methods, compared to the existing q‐ROFS decision‐making methods, are as follows: (a) it can obtain the optimal alternative without counterintuitive phenomena and (b) it has a lower computational complexity.