Methodological Foundations of Adaptive Artificial Intelligence

Abstract

This thesis examines methodological foundations for using adaptive artificial intelligence in education. The aim is to justify a conceptual model aligning adaptation mechanisms with core didactic principles. The methodology relies on a systems approach, pedagogical modeling, and learning analytics logic. Scientific novelty is presented through integrating evaluation criteria for adaptive decisions with requirements for instructional design and measurable learning outcomes.