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The limits of large language models and the necessity of human cognition in K-12 education

2025/07/03 by Jiseung Yoo, Campbell F. Scribner
Neuroscience · Psychology · #Action Observation and Synchronization #Child and Animal Learning Development #Embodied and Extended Cognition

paper · pdf · doi:10.1080/00405841.2025.2528553

openalex publication_date 2025/07/03 · crossref created 2025/07/03 · crossref issued 2025/08/05 · crossref published 2025/08/05 · crossref published-online 2025/08/05 · crossref published-print 2025/10/02 · openalex created_date 2025/10/10 · crossref deposited 2026/01/05 · crossref indexed 2026/08/01 · openalex updated_date 2026/08/01

Abstract

This article explores the distinctive qualities of human cognition in comparison to large language models (LLMs), focusing on the implications of each for K-12 education. Drawing on insights from cognitive science and phenomenology, we argue that human cognition — grounded in embodied experience, social interaction, and self-consciousness — cannot be fully replicated by machine models. These unique qualities suggest the need for humanistic education: teaching rooted in action, subjectivity, and self-consciousness, aimed at the cultivation of virtue. This study contributes to the broader discussion on AI in education by emphasizing the irreplaceable aspects of human experience and highlighting what human-centric instruction looks like in the era of AI.

Citations