Challenges and applications of multi-model learning analytics in “Decision Support for Physical Education Teaching” refers to a domain where learning analytics techniques are applied to enhance decision-making processes in physical education instruction. This case study explores the inauguration of a new educational initiative in a developing nation, illuminating the complex web of parties engaged in the process. The usage of Intuitionistic Fuzzy Z-Number Sets (IFZNS) becomes crucial while handling advanced problems in Multi-Attribute Decision Making (MADM). These sets provide a significant improvement over existing fuzzy set designs in handling higher degrees of uncertainty. The method we provide in this work called MARCOS, is intended to discourse MADM complications in IFZNS, predominantly in context while attribute weights are unknown. We derive attribute weights through the entropy measure. The study begins by investigating IFZNS, analyzing their scoring and accuracy, and clarifying the essential perception that underpins their operations. Next, we recommend a decision-making method to handle MADM cases by using IFZNS information. This work improves this field’s practical execution as well as its theoretical underpinnings. We use the Combined Compromise Solution (CoCoSo) approach to a comparison study to verify and prove the legitimacy of our results. This meticulous strategy agreements a systematic estimation of the advocated methodology’s efficiency and complements the existing argument on efficient decision-making in situations that are complicated and erratic.