A FUCA based MCDM model with complex q rung orthopair fuzzy information for evaluating physical education programs

The assessment of physical education programs is associated with various contradictory standards, ambiguity, and subjective judgment of the experts, and the traditional methods of decision-making are inadequate. To overcome these shortcomings and the absence of robust AI-driven fuzzy decision frameworks in the physical education evaluation, the paper obtains a novel AI-based Complex q-Rung Orthopair Fuzzy Faire Un Choix Adequat (CqROF-FUCA) fuzzy model of multicriteria decision-making (MCDM) that is able to operate with uncertainty and hesitation, and benefit as well as cost factors at the same time. The main contributions of this study include the development of a novel CqROF-FUCA decision framework, the integration of artificial intelligence with CqROF information for enhanced uncertainty modeling, and its application to physical education program evaluation for improved decision support. To show its effectiveness, a case study is performed where five programs are considered by four decision-makers with the help of seven criteria. These findings show that wellness- and health-oriented programs perform best, demonstrating the framework’s strong performance and discrimination capabilities. The credibility and stability of the proposed method are validated through sensitivity analysis and benchmarking against available alternatives using CqROF. The research offers a usable AI-based decision-support system to the policymaker and school administrators to make evidence-based, effective, and sound program selection decisions in complex, uncertain settings.