This commentary highlights trade-offs in using large language models for literacy, suggesting cognitive strategies are needed for young learners.
This commentary critically complements a recent proposal that cognitive science can leverage Large Language Models (LLMs) to counter declining literacy. While recognizing the educational potential of LLMs, we highlight a significant trade-off: their inherent design reduces users' direct engagement with written text, undermining deeper literacy skills, especially in young learners. Acknowledging this tension is essential for developing pedagogically sound interventions. Cognitive scientists and educators must jointly anticipate which cognitive capacities may weaken, identify critical skills needed in emerging multimodal contexts, and collaboratively devise instructional strategies to preserve the cognitive benefits humans derive specifically from sustained interaction with written language.
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Guerra et al. (2025) studied this question.
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