Spherical Fuzzy Z-Numbers-based CRITIC CRADIAS and MARCOS Approaches for Evaluating English Teacher Performance

Consider combining quantitative and qualitative data for these case studies, such as interviews with English teachers, student evaluations, classroom observations, and surveys. Contextual elements, including community support, resources, and school demographics, should also be taken into consideration. The assessment process in English teaching performance evaluation is very complicated and diverse, making it a perfect fit for use in the Multi-Attribute Group Decision Making (MAGDM) framework. The utilization of Spherical Fuzzy Z˘-Number Sets (SF Z˘NS) is essential in Multi-Attribute Group Decision Making (MAGDM) to handle intricate problems. These sets are significantly more capable of handling higher levels of uncertainty than the fuzzy set designs used today. Here, we provide a method, Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIAS), designed to address MAGDM problems in SF Z˘NS, particularly in cases when attribute weights are opaque. Attribute weights may be found by applying the CRITIC technique. The first section of the research covers the examination of spherical fuzzy Z numbers, their accuracy and scoring functions, and the main concept behind their functioning. We then propose the use of spherical fuzzy Z˘-Number data to handle MAGDM cases in a decision-making process. This work strengthens the topic’s theoretical underpinnings as well as its practical applicability. By conducting a comparison study, we apply the MARCOS approach to validate and illustrate the validity of our findings. This methodical approach guarantees a thorough evaluation of the suggested method’s effectiveness and adds to the current discussion on how to make wise decisions in difficult and uncertain situations.

@article{Niu2024,
  title     = {Spherical Fuzzy Z-Numbers-based CRITIC CRADIAS and MARCOS Approaches for Evaluating English Teacher Performance},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {3},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Jie Niu},
  doi       = {10.14569/IJACSA.2024.01503115},
  url       = {https://doi.org/10.14569/IJACSA.2024.01503115}
}