Abstract

The rapid integration of AI into education is reconfiguring the extent to which students can delegate cognitive labor during learning. This may increasingly widen the gap between AI-assisted performance and independent competence. To account for this gap, this paper develops cognitive debt as an analytical metaphor for the accumulating divergence between the two. This paper argues that AI delegation is productive when it reduces processing peripheral to the learning objective while preserving processing necessary for the development of independent competence; cognitive debt emerges when AI substitutes for the development of independent competence and may compound when underdeveloped competence impedes the evaluation of subsequent AI output. This paper further argues that AI becomes meaningfully different from conventional cognitive offloading when students not only delegate cognitive execution but also cognitive authority to AI. On this basis, the paper proposes calibrated dependence as a solution where students utilize AI while retaining cognitive authority and independent competence required to regulate both present and future delegation.

Keywords: Artificial Intelligence; cognitive debt; cognitive offloading; independent competence

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