Mapping Sustainability to Cybernetic-Generative Artificial Intelligence-Based Education: An Innovative Neutrosophic Orbifold-Lattice Methodology
Year: 2025
Type: article
Abstract: The lightning-fast development of artificial intelligence (AI), notably generative artificial intelligence (Gen AI) technologies, has intrigued multiple disciplines, particularly education. In this context, Large Language Models (LLMs) serve as beneficial cognitive resources that address knowledge deficits and provide tailored educational support for learners and staff. For learners, LLMs are regarded as knowledgeable educators who offer prompt, focused responses and rationales to tricky queries. Whereby LLMs for staff, Strength enhancer, automating tedious tasks, and creating intelligent resources.Gen AI’s rapid growth offers enormous obstacles for educational systems, compelling them to discover solutions for these obstacles. Conceptually, cybernetics is leveraged for bridging the gap between Gen AI and the practice of education. Thereby, the objective of this study is to merge cybernetic with Gen AI (cyber-Gen AI) and showcase the relation between this merger and sustainability, resilience, and cognition. This objective is achieved through leveraging this merger in education systems to achieve sustainability and smartness. Practically, evaluating the role of cyber-Gen AI in education systems is imperative. Hence, a novel model of a Neutrosophic Orbifold-Lattice (NOL) model is proposed in this study. Experimentally, the innovative model is applied in a real case study to verify its accuracy in making decisions.
Authors: Mona Mohamed, Ahmed A. Metwaly
Institutions: Higher Technological Institute, Zagazig University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7117132213
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