Neutrosophic Hyperprobabilistic Modeling of Learning Outcomes  in College Blended Physical Education Teaching Process

Yanmin Li; Shiqiang Dou

Authors

Yanmin Li Department of Public Teaching, Xizang Agricultural and Animal Husbandry University,Linzhi, Xizang, China
Shiqiang Dou National Bureau of Statistics Linzhi Survey Team, Linzhi, Xizang, China

Keywords:

Blended Physical, Neutrosophic Logic, Hyperprobability, SuperHyperFunction, Indeterminacy Modeling, Learning Outcome Evaluation, Educational Statistics, Complex Pedagogy .

Abstract

College Blended Physical Education (BPE), which combines in-person and
digital instruction, introduces significant variation and uncertainty in student
engagement, motor learning, and cognitive development. Traditional statistical models
fail to account for the multi-dimensional ambiguity, contradiction, and indeterminacy
inherent in such environments. This paper proposes a novel Neutrosophic
Hyperprobabilistic Framework to model the effectiveness of college BPE, integrating
Neutrosophic Triplets with SuperHyperFunction theory to capture hierarchical and
contradictory patterns in learning outcomes. The model introduces a hyperprobability
structure that quantifies the degrees of truth (T), indeterminacy (I), and falsehood (F) in
learner performance across blended modalities. A simulated case study demonstrates
how the model effectively maps variability across motor, cognitive, and emotional
domains. The results indicate that this framework surpasses classical statistical
approaches in interpretability and accuracy under complex educational settings. The
paper concludes with implications for adaptive curriculum design and future research in
uncertainty-aware pedagogy.

DOI: 10.5281/zenodo.16934502