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From Assistance to Dependence: The Cognitive Cost of Artificial Intelligence in Education
1ORCID ID: 0000-0002-1392-1787, Assistant Professor, College of Nursing AIIMS Jodhpur, Rajasthan, India.
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.
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