Methodological Paradigms in AI-Driven Adaptive Education: An Analytical Review of Architectures, Technologies, and Governance

This report provides a comprehensive analytical review of the methods and methodologies that constitute the foundation of modern AI-driven adaptive education.It systematically deconstructs the architectural principles of Intelligent Tutoring Systems (ITS), explores the advanced computational methodologies of Cognitive AI, Generative AI, and Explainable AI (XAI), and analyzes their practical synthesis through a case study of the Aspire, Conquer, Excel (ACE) platform.Furthermore, the report critically examines the methodologies for evaluating the efficacy of these systems and delves into the crucial ethical frameworks required for their responsible implementation, focusing on student-centric models of governance.By synthesizing foundational theories with contemporary technological advancements and ethical imperatives, this paper charts the evolution of the field and delineates key trajectories for future research.