Abstract

This paper proposes an AI-based personalized learning model for information technology education (APL-CS). The model is developed by integrating key theoretical approaches, including learner-centered learning, personalized learning, adaptive learning, and intelligent tutoring systems. Its architecture consists of a learner model, a content model, an AI engine, and a continuous feedback loop. The main contribution of this study lies in incorporating “error patterns” into the learner model and describing the personalization mechanism. The proposed model enhances the adaptability of learning systems and provides a foundation for future empirical research.

Keywords: Adaptive learning, artificial intelligence, information technology education, intelligent learning systems, personalized learning.