From AI Intuition to AI Literacy: A Dual Framework for K-12 Education

Abstract

AI literacy has become a central framework for guiding the integration of artificial intelligence in K-12 education, emphasizing conceptual understanding, practical application, critical evaluation, and ethical judgment. These competencies are essential for supporting informed and responsible use of AI systems. However, classroom practice suggests that students often learn to engage with generative AI through exploratory and experiential interactions, experimenting with prompts, observing system behavior, adapting strategies, and reflecting on outcomes, before they can fully articulate formal concepts or rules. To account for this experiential dimension of learning, this paper introduces AI intuition as a complementary educational construct. AI intuition is defined as an experiential, inductive form of understanding that develops through iterative interaction with AI systems and supports context-sensitive judgment under uncertainty. We propose a dual framework in which AI literacy provides explicit knowledge, critical criteria, and ethical guidance, while AI intuition develops through iterative experience and reflection. These two dimensions interact dynamically and reinforce one another. We discuss pedagogical implications for K-12 education and outline directions for future research on experiential learning with AI.