Neutrosophic SuperHyper–Plithogenic Modeling for Consensus Optimization in Curriculum-Based Ideological–Political Educational Effectiveness

This paper proposes a new mathematical framework that fuses Neutrosophic SuperHyperFunctions with Plithogenic Probability theory to analyze and optimize ideological political education within college curricula. The model encodes truth, indeterminacy, and falsehood memberships into superhyper topological structures, enabling simultaneous representation of direct and indirect pedagogical influences. A plithogenic aggregation mechanism reconciles contradictory instructional attributes and produces a fused neutrosophic state vector for each curriculum unit. The framework introduces an Ideological Asymmetry Index and a polarization diffusion operator, both formally defined and supported by iterative convergence proofs. Application to a two-unit case study shows how repeated updates systematically reduce entropy and asymmetry while maintaining pedagogical diversity. Results demonstrate the model’s capacity to achieve measurable consensus, offering a robust, quantitative tool for curriculum designers and policymakers seeking to strengthen ideological–political education outcomes in higher learning environments.