Neutrosophic Modeling of Cognitive Political Dynamics for Teaching Effectiveness in University Thought and Politics Curriculum in Blended Learning Environments
Year: 2025
Type: article
Abstract: The interaction between thought formation and political orientation in blended learning environments is characterized by uncertainty, ambiguity, and incomplete information. Conventional analytical models often overlook these indeterminate aspects, resulting in partial or biased interpretations. This study proposes a novel neutrosophic based framework to quantitatively capture and analyze the cognitive–political dynamics within hybrid educational settings. The framework employs neutrosophic sets to represent three fundamental components of knowledge: truth (T), indeterminacy (I), and falsity (F), allowing for a richer representation of learner perspectives and political influences. The proposed methodology integrates multi-source data, including learner interaction patterns, discourse analysis, and cognitive mapping, into a multi-stage neutrosophic decision-making model. Detailed mathematical formulations are introduced, with all variables explicitly defined and demonstrated through complete, step-by-step numerical examples. Results indicate that the model effectively reveals subtle interdependencies between thought processes and political alignment, as well as hidden uncertainties that are often overlooked by traditional methods. The findings contribute to both educational theory and policy-making by offering a systematic tool for understanding and managing political and cognitive variability in blended learning.
Author: Xiaoqin Chen
Language: English
Topic: Fuzzy and Soft Set Theory
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6930893146
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