SuperHyperSoft Framework for College English Blended Teaching Quality Evaluation in the New Era: Addressing Uncertainty and Complexity

Abstract

A Single-Valued Neutrosophic Set (SVNS) is a powerful tool for representing uncertainty, ambiguity, and 
incomplete or inconsistent information in real-world scenarios. This approach is particularly effective for 
handling uncertain measurements and data. Building on the concept of fuzzy set entropy, the SVN-entropy 
method has been developed to support multi-criteria decision-making (MCDM) processes. In this study, 
SVN-entropy is combined with the SuperHyperSoft (HSS) framework—an extension of HyperSoft sets—
 to evaluate different criteria and sub-criteria with varying values. The proposed method uses entropy to 
calculate criteria weights, which are then applied to assess the quality of College English Blended Teaching 
in the modern era. The study identifies eight main criteria, each with associated sub-criteria, to provide a 
comprehensive evaluation framework. This approach ensures a robust and precise assessment of blended 
teaching quality, leveraging advanced mathematical tools to handle complex and uncertain data 
effectively. 

DOI: 10.5281/zenodo.14708655