The impact of university students' computational thinking on AI literacy: A longitudinal study based on SEM-PLS.

Abstract

Artificial intelligence literacy is a core competency that underpins individual development. Although previous studies have demonstrated a cross-sectional association between computational thinking and artificial intelligence literacy, there has been little analysis of their longitudinal effects. This study utilized a sample of 216 undergraduate students from southern China and employed structural equation modeling (SEM-PLS) and paired-sample t-tests. Through a two-stage longitudinal data analysis, the study found that computational thinking has a significant positive effect on artificial intelligence literacy and that both competencies improved significantly over time. By tracking the evolution of these two competencies, this study offers a novel longitudinal perspective, confirms their synchronous development, and highlights the stability of their cross-sectional relationship, thereby providing theoretical foundations and methodological references for educational practice.