A Neutrosophic Evaluation Method of Engineering Certification Teaching Effect Based on Improved Entropy Optimization Model and Its Application in Student Clustering

Abstract

To realize the all-around assessment of teaching quality in the context of engineering education accreditation, this study proposes a single-valued neutrosophic information entropy and a novel assessment method of teaching effectiveness. In this proposed assessment model, an optimization model is structured based on the minimum information entropy value of single-valued neutrosophic sets (SvNSs). In this study, the primary innovation is that by using the structured model, the attribute weights are extracted from the given deterministic information. The main work of this study is summarized as follows. Firstly, aiming at the engineering certification problem, this study proposes an improved single-value neutrosophic information entropy formula to enhance the effectiveness of the engineering certification results. Secondly, this paper establishes an optimization model based on the minimum information entropy value and provides a method for assigning weight values. Thirdly, this study proposes an improved evaluation method for teaching effect, which provides a novel idea for engineering certification. Thereafter, a case study is presented to demonstrate the effectiveness and practicality of the proposed model.

Keywords

• single-valued neutrosophic set
• single-valued neutrosophic information entropy
• engineering education certification
• student clustering