AI in Education: A Neutrosophic Graph Framework for Evaluating Challenges and Opportunities

The framework proposed in this paper evaluates key strengths, such as AI's ability to enhance personalized learning and automation of administrative tasks, while addressing significant weaknesses, including ethical concerns, privacy issues, and inequitable access to AI technologies. Opportunities created by AI, such as the potential for global accessibility to education, the development of innovative pedagogical models, and the creation of intelligent tutoring systems, are balanced against threats like the displacement of educational jobs, biases in algorithmic outcomes, and the risk of widening socioeconomic disparities. The use of SVNGs allows the study to establish causal relationships between various SWOT components, with the indeterminacy of connections between these factors represented graphically through neutrosophic graphs. Energy analysis is employed to assess the impact of AI in each quadrant—Strength-Opportunities (SO), Strength-Threats (ST), Weakness-Opportunities (WO), and Weakness-Threats (WT). By calculating the energy of each quadrant, the study quantifies the potential benefits and risks of AI integration into educational frameworks. The findings suggest that while the opportunities presented by AI outweigh some of its associated threats, a careful and strategic approach is required to ensure that its implementation is ethical, equitable, and effective.