TOPSIS Method-Based Decision-Making Model of Simplified Neutrosophic Indeterminate Sets for Teaching Quality Evaluation

Abstract

Recently, colleges/universities have paid a lot of attention to the teaching quality
evaluation (TQE) of teachers in China. TQE is an essential way to improve teachers' teaching ability
and quality in the teaching process. Then, the TQE of teaching supervisors is a multi-attribute
decision-making (MADM) problem with vague, inconsistent, and indeterminate information. The
simplified neutrosophic indeterminate set/element (SNIS/SNIE) is an appropriate form to express
the indeterminate decision-making information in the TQE process. Therefore, this article presents
an improved ranking method based on maximizing deviations principle and technique for order of
preference by similarity (TOPSIS) for SNIS and applies it to evaluate teachers' teaching quality.
First, the Hamming distance between two SNIEs is defined. Then, attribute weights are obtained
by maximizing deviation method and the TOPSIS method-based decision-making model is
developed for the MADM applications with unknown attribute weights. Finally, we perform the
developed MADM model for a TQE case and compare it with existing related models to indicate
the feasibility and rationality of the proposed model with unknown attribute weights in the SNIE
circumstance.