Leveraging Entropy-EDAS Technique in Z-Number Decision-Making for Electrical Automation Programs' Teaching Quality Evaluation in Agricultural Colleges

The evaluation of teaching quality in electrical automation programs requires a systematic approach that integrates both quantitative metrics and qualitative insights. This multi-dimensional framework ensures a comprehensive understanding of program effectiveness, capturing both theoretical knowledge acquisition and practical skill development essential for this technically demanding field. The electrical automation programs teaching quality evaluation in agricultural colleges constitutes a multiple-attribute decision-making (MADM) challenge. Contemporary approaches utilize approaches like EDAS and entropy to address such MADM problems. In this specific evaluation, Z-numbers are applied to represent uncertain information. This study develops an integrated Z-number EDAS (ZN-EDAS) framework to handle MADM within a Z-number environment. To demonstrate the proposed approach's practicality, a numerical example concerning the electrical automation programs teaching quality evaluation in agricultural colleges is presented to show the ZN-EDAS approach.