Intelligent data driven assessment of physical education programs using circular intuitionistic fuzzy MAIRCA CRITIC model.

This study presents an intelligent multi-criteria evaluation framework for physical education (PE) systems by integrating the circular intuitionistic fuzzy (CIF) environment with a hybrid MAIRCA (multi-attributive ideal-real comparative analysis)-CRITIC(criteria importance through inter-criteria correlation) approach. Testing PE programs and establishing their effects and influences is usually done in vague and inaccurate circumstances. Hence, conventional models find it difficult to cope effectively. This should be overcome by creating a more sophisticated framework that uses circular intuitionistic fuzzy sets (CIFS) to model hesitation and conflicting information, thus supporting the robustness of the decision. Alternative ranking by the proximity of preferences is utilized using the MAIRCA method, and objective criteria weighting is realized due to contrast intensity and assessment of conflicts with the CRITIC method. The combination provides the opportunity to be subjective and objective in measurement with the combined approach and evaluation strategy. The model is considered in a practical situation where it deals with several PE programs, and the obtained outcomes show that it is more accurate, specifically in ranking, yet flexible in treating vague information. The framework is good at assisting educational policymakers, but also helps enhance and utilize resources in PE systems.