The cognitive paradox of AI in education: between enhancement and erosion
Summary
The article examines AI's dual role in education, discussing benefits for personalization and risks of cognitive offloading, using cognitive load theory, Bloom's Taxonomy, and self‑determinationTheory
Key quotes
Artificial intelligence (AI) is rapidly transforming learning through unparalleled levels of personalization, efficiency, and scalability (Govea et al., [2023]; Mahmoud and Sørensen, [2024]).
Cognitive offloading refers to the utilization of external aids to achieve cognitive tasks (Risko and Gilbert, [2016]).
According to Cognitive Load Theory, AI must decrease cognitive overload but sustain active cognitive engagement.
AI should complement and not replace human instruction, with students doing higher-order thinking as the efficiency and personalization strengths of AI are leveraged.
Claims using this source
The paper reviews empirical studies on AI‑assisted learning, highlighting mixed effects on memory retention, problem solving, and creativity. It proposes a roadmap for integrating AI in blended learning while preserving higher‑order cognitive skills. The authors call for balanced AI design that supports autonomy, competence, and relatedness.