A Study on Blended Teaching Model Evaluation for English Major Courses in Higher Education: An Uncertainty-Based Approach - Chunmei Xue (Neutrosophic Sets and Systems)
As businesses adopt remote work, online learning, and the digital workplace, the idea of blended learning keeps changing. Traditional trainer-led lectures and coaching sessions are still provided to learners, but they are combined with interactive, self-guided experiences that give employees practical training and allow them to operate as a team. The creation of a decision support system that facilitates the evaluation of blended learning of English courses in higher education for aiding students. In addition to qualitative metrics that show evaluation of blended learning, several quantitative metrics also influence blended learning performance. The purpose of this study is to evaluate blended learning performance using both qualitative and quantitative metrics. This study is performed to overcome the research gapes which ranking the alternatives without overcoming uncertainty in the decision making problem. So, the plithogenic sets and a multi-criteria decision-making (MCDM) approach are used within this context. Expert significance levels are determined using plithogenic sets. The performance rating of blended learning is determined using the plithogenic-simple weighted sum product (WISP) approach. The plithogenic-WISP hybrid model is thus created in this study, and an algorithm for this innovative decisionanalytic model is provided. To illustrate the usefulness of the suggested hybrid paradigm, a case study concentrating on blending learning evaluation is created. The findings of the study support the plithogenicWISP hybrid method's applicability and validate its robustness.