Intelligent Evolution of Educational Information Ecosystems: A Systems-Theoretical and Evolutionary Perspective

This paper analyzes the intelligent evolution of educational information ecosystems through the theoretical lenses of systems theory and evolutionary dynamics. By analyzing the transformative impact of artificial intelligence technologies – including deep learning algorithms, knowledge graphs, and natural language processing – on educational systems, the study identifies three key evolutionary characteristics: (1) the shift from AI as a supplementary tool to a systemic restructuring force that fundamentally reshapes educational processes; (2) the emergence of nonlinear evolutionary patterns manifested in decentralized knowledge production and personalized learning paradigms; (3) the inherent tensions between technological and educational logics, particularly in reconciling algorithmic standardization with educational personalization. Drawing on niche theory, it establishes an optimization framework that provides novel theoretical insights into the mechanisms of educational transformation in the AI era. In addition to advancing our understanding of how educational ecosystems evolve under technological intervention, this framework offers practical guidance for building more resilient and adaptive educational systems.