A Novel Single Valued Neutrosophic CRITIC-MAIRCA Model for Data Driven Evaluation in Physical Education Systems

Abstract Physical education is an important part of the cognitive, physical, and social development of students; yet it is hard to measure due to the subjective assessment, discrepancy between criteria, and the uncertainty itself. Traditional assessment methods do not effectively capture these complexities, leading to inconsistent and biased results. This paper aims to circumvent these drawbacks by introducing a new hybrid decision-making process model that assembles single-valued neutrosophic sets (SVNS) with multi-attributable ideal-real comparative analysis (MAIRCA) and a process for the importance of criteria based on intercriteria correlation (CRITIC) weighting. It embodies the values of truth, indeterminacy, and falsity in expert verdicts, and guarantees the objective weighting of criteria or criteria that depend on each other. As a case study, we demonstrate that the framework produces transparent, non-discriminatory rankings that exceed those of traditional approaches in school physical education programs. When compared, SVNS CRITIC-MAIRCA proves useful for reducing uncertainty and enhancing decision validity, thereby enabling a scalable decision-support system for education policy, resource distribution, and performance measurement. The proposed framework provides a flexible foundation for applying advanced multi-criteria decision-making (MCDM) techniques to other educational evaluation contexts where uncertainty and expert subjectivity are prominent.