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N-EDU: An Innovative Neutrosophic Logic Construction for Digital Transformation Effectiveness of College Ideological and Political Education with Mathematical Foundations and Applied Learning Dynamics.

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Bibliographic Details
Title: N-EDU: An Innovative Neutrosophic Logic Construction for Digital Transformation Effectiveness of College Ideological and Political Education with Mathematical Foundations and Applied Learning Dynamics.
Authors: Chen, Ye
Source: Neutrosophic Sets & Systems; 2025, Vol. 91, p704-715, 12p
Subject Terms: NEUTROSOPHIC logic, MATHEMATICAL proofs, DIGITAL transformation, COMPUTER logic, MATHEMATICS education
Abstract: This paper presents N-EDU, a new mathematical framework for Digital Ideological and Political Education (DIPE) based on neutrosophic logic. In N-EDU, both learners and educational content are described using neutrosophic triplets (T, I, F), where T is the degree of truth, I is the degree of uncertainty, and F is the degree of falsehood. We define two main operators: a fusion operator for combining content with a learner's current knowledge, and a debias operator for reducing misinformation. We also design a continuity gate using neutrosophic topology to prevent sudden increases in uncertainty during the learning process. The framework includes formal definitions, mathematical proofs, and case studies. Results show that N-EDU can increase truth, reduce falsehood, and keep uncertainty stable while remaining interpretable and practical for real-world use. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
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Abstract:This paper presents N-EDU, a new mathematical framework for Digital Ideological and Political Education (DIPE) based on neutrosophic logic. In N-EDU, both learners and educational content are described using neutrosophic triplets (T, I, F), where T is the degree of truth, I is the degree of uncertainty, and F is the degree of falsehood. We define two main operators: a fusion operator for combining content with a learner's current knowledge, and a debias operator for reducing misinformation. We also design a continuity gate using neutrosophic topology to prevent sudden increases in uncertainty during the learning process. The framework includes formal definitions, mathematical proofs, and case studies. Results show that N-EDU can increase truth, reduce falsehood, and keep uncertainty stable while remaining interpretable and practical for real-world use. [ABSTRACT FROM AUTHOR]
ISSN:23316055