A novel MADM algorithm for teaching quality evaluation of college volleyball training based on 2-tuple linguistic neutrosophic numbers information operators

Abstract

Teaching quality is the foundation and lifeline of colleges and universities. To establish a distinctive university, we must adhere to the scientific concept of development, deepen teaching reform and improve teaching quality. The classroom teaching quality (CTQ) evaluation of college physical education (PE) is an essential part of the teaching process. Building a scientific, comprehensive, reasonable and effective evaluation system is crucial to improve the quality of college PE classroom teaching. This process is not easy and needs long-term efforts and persistence. The CTQ evaluation of college volleyball training is viewed as the multi-attribute decision-making (MADM). In this paper, we connect the geometric Heronian mean (GHM) operator and power geometric (PG) operator with 2-tuple linguistic neutrosophic sets (2TLNSs) to build the generalized 2-tuple linguistic neutrosophic numbers weighted power GHM (G2TLNWPGHM) operator. Then, the G2TLNWPGHM operator is used to tackle MADM with 2TLNSs. Finally, an example for CTQ evaluation of college volleyball training is used to show the proposed methods.