Modeling Cross-Cultural Competence in Vocational Education  Internationalization Using Neutrosophic SuperHyperFunctions and Big Data Driven Cultural Clusters

Min Huang; Liang zhang; Fenghua Li

Authors

Min Huang Hunan Normal University, Hunan,410081, China
Liang zhang Hunan Mechanical & Electrical Polytechnic, Changsha, Hunan, 410151, China
Fenghua Li Hunan Mechanical & Electrical Polytechnic, Changsha, Hunan, 410151, China

Keywords:

Neutrosophic logic, SuperHyperFunction, vocational education, cultural clusters, nth power set, cross-cultural modeling, big data .

Abstract

In the global landscape of vocational education, cross-cultural competence is vital for
successful international collaboration and student engagement. However, most
traditional frameworks are too rigid to capture the evolving, uncertain, and multi-layered
nature of cultural identities. This paper introduces a novel approach that models cross
cultural competence using Neutrosophic SuperHyperFunctions. These functions allow for
the representation of dynamic cultural clusters extracted from big data sources, including
digital learning platforms and international student interactions. By structuring culture as
a system of nested and sometimes contradictory traits, we use nth-order powersets and
neutrosophic logic to define competence across individual, group, institutional, and
national levels. A comprehensive mathematical framework is established, including
formal definitions, axioms, and symbolic functions. Realistic, fully calculated case studies
demonstrate how this model captures the uncertainty and fluidity of real-world cross
cultural experiences. The proposed method offers an adaptive, data-integrated pathway
to support decision-making in curriculum design, teacher training, and policy formation
in vocational education internationalization.

DOI: 10.5281/zenodo.15786743