BEYOND THE ALGORITHM ON HOW AI WILL REDEFINE HUMAN PROGRESS: FROM DIRECTION TO EMPOWERMENT

Abstract

This position paper presents a critical analysis of the evolution of Artificial Intelligence in Education (AIEd) through three distinct paradigms: AI-directed (learner-as-recipient), AI-supported (learner-as-collaborator), and AI-empowered (learner-as-leader). Through a comprehensive review of literature spanning three decades (1990-2021), the study examines the theoretical foundations, implementation approaches, and practical applications of each paradigm. The analysis reveals a progressive shift from technology-centered to learner-centered approaches, highlighting the transformation of learners' roles from passive recipients to active leaders in their educational journey. The paper identifies critical challenges in integrating AI with educational theories and proposes a framework for future AIEd development that emphasizes human agency, personalized learning, and ethical considerations. The findings suggest that successful AIEd implementation requires balancing technological advancement with pedagogical principles, while maintaining focus on human-centered learning experiences. This work contributes to the field by providing a structured framework for understanding AIEd's evolution and guiding future development toward more effective, learner-centered educational technologies.