SuperHyperSoft Framework for College English Blended Teaching Quality Evaluation in the New Era: Addressing Uncertainty and Complexity - Dahai Zhang (Neutrosophic Sets and Systems)
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.