Alpha-Factor Neutrosophic Combination: A New Context for Teaching Quality in University Public Art Education Courses Grounded in General Education

Abstract

University public art education within the framework of General Education is 
designed to promote intellectual breadth, integrative learning, and civic–cultural 
engagement. Traditional evaluation models often fall short because they reduce artistic 
ambiguity to error and cannot consistently integrate diverse stakeholder perspectives. 
This study introduces Alpha-Factor Neutrosophic Fusion (AFNF), a novel assessment 
framework that reconceptualizes the classical α-parameter from multi-criteria decision 
making. Instead of functioning as a scalar discount, α is reformulated as a neutrosophic 
fusion vector α=(αT,αI,αF) acting on criterion-level neutrosophic evidence (T,I,F). This 
structure enables the systematic fusion of truth, indeterminacy, and falsehood in an 
aesthetic–epistemic manner, aligning more closely with the inherent character of art 
education. AFNF produces three meta-indices corresponding to Breadth (B), Integration 
(X), and Engagement (E), along with a bounded global score. The framework is formally 
specified with complete notation, axioms, and operators, and its mathematical properties,
including boundedness, monotonicity, neutrality–sensitivity, and invariance, are proven. 
A cross-sectional estimation algorithm and practical instruments are also described. The 
theoretical novelty of AFNF lies in its transformation of α into a neutrosophic aesthetic 
factor, making it possible to interpret ambiguity as a form of competence in art learning 
while providing a rigorous, auditable tool for quality evaluation in university settings. 

DOI: 10.5281/zenodo.17036986