Enhanced IVIFN-ExpTODIM-MABAC Technique for Multi-Attribute Group Decision-Making Under Interval-Valued Intuitionistic Fuzzy Sets

The evaluation of English teaching quality is crucial for enhancing teaching effectiveness. It helps teachers understand their teaching methods and students' learning outcomes through systematic assessment, thereby guiding teachers to adjust their teaching strategies. Additionally, the results of the evaluation provide decision-making support for educational management at schools, optimizing curriculum design and resource allocation. Regular evaluations of teaching quality motivate teachers for continuous professional development, improve teaching standards, and ensure that students achieve maximum growth and progress in their English learning journey. The assessment of college English teaching quality employs multi-attribute group decision-making (MAGDM). Techniques like Exponential TODIM (ExpTODIM) and MABAC are utilized to facilitate MAGDM. During the evaluation process, interval-valued intuitionistic fuzzy sets (IVIFSs) are utilized to handle fuzzy data. This research introduces a novel method, the interval-valued intuitionistic fuzzy number ExpTODIM-MABAC (IVIFN-ExpTODIM-MABAC) tailored for MAGDM under the framework of IVIFSs. To demonstrate its efficacy, a numerical example evaluating college English teaching quality is presented. Key contributions of this study include: (1) Extending the ExpTODIM-MABAC method to include IVIFSs with an Entropy model; (2) Utilizing Entropy to ascertain weights within IVIFSs; (3) Proposing the IVIFN-ExpTODIM-MABAC approach for MAGDM under IVIFSs; (4) Validating the approach with a numerical example and various comparative analyses of college English teaching quality.

@article{Xie2024,
  title     = {Enhanced IVIFN-ExpTODIM-MABAC Technique for Multi-Attribute Group Decision-Making Under Interval-Valued Intuitionistic Fuzzy Sets},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {10},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Bin Xie},
  doi       = {10.14569/IJACSA.2024.0151037},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151037}
}