From Assistance to Dependence: The Cognitive Cost of Artificial Intelligence in Education.

Background: The integration of Artificial Intelligence (AI) in education is reshaping how students interact with academic content, offering personalized support through intelligent tutoring systems, adaptive platforms, and AI-driven feedback tools. While AI enhances learning efficiency, motivation, and engagement, especially in STEM (Science, Technology, Engineering, and Mathematics) and language education, its cognitive implications require careful examination. Objective: This article explores AI's impact on core cognitive functions such as memory, critical thinking, metacognition, and motivation, using frameworks like Bloom's Taxonomy, Cognitive Load Theory, and Self-Determination Theory. Finding: Research shows that while AI can support learning and retention, overreliance may hinder deep cognitive engagement, original thinking, and self-regulated learning. Ethical concerns, including academic integrity, algorithmic bias, and privacy risks, further challenge the effective use of AI in educational settings. Real-world applications demonstrate AI's potential when used to supplement, not replace, human instruction. Conclusion: This study underscores the need for a balanced, evidence-based approach that prioritizes AI literacy, transparent practices, and pedagogically sound integration. By aligning AI use with cognitive and motivational theories, educators can ensure technology serves as a supportive tool, promoting sustainable learning while preserving essential human-centered educational values. Keywords: Artificial Intelligence, Cognitive Functions, Educational Technology, Motivation.