Developmental, Contextual, and Profile-Based Heterogeneity in K–12 Students’ Artificial Intelligence Literacy

Artificial intelligence (AI) is increasingly embedded in students’ learning and everyday lives, making AI literacy an important competence in K–12 education. However, large-scale evidence remains limited on AI literacy differences, associated factors, and student profiles. This cross-sectional study used survey data from 141,988 students in Grades 6, 9, and 11 in Changchun, Northeast China. The study addressed three research questions: whether AI literacy differed by grade and student background; which family, academic, lifestyle, and media-use factors were associated with it; and whether profiles emerged across AI understanding, use, evaluation, and ethical awareness. Group comparisons, correlation and hierarchical regression analyses, and latent profile analysis were conducted. AI literacy was higher among students in the upper grades, urban students, and students from higher-socioeconomic-status families, while gender differences were small. Family socioeconomic status, academic achievement, discretionary time, sleep duration, physical activity duration and habit, online gaming habit, and mobile phone usage pattern were positively associated with AI literacy. Online gaming time and mobile phone use time were not independently associated with AI literacy. Four latent profiles were identified: overall low-level, overall high-level, high-exposure–low-reflection, and low-exposure–high-reflection. These findings support equitable, stage-appropriate AI literacy education that considers students’ backgrounds and profiles.