Development and influencing factors of artificial intelligence literacy and computational thinking in Chinese university students

This study investigates the developmental status and influencing factors of artificial intelligence (AI) literacy and computational thinking (CT) literacy among undergraduates in China's "four new" majors. Guided by the Technology Acceptance Model, Social Cognitive Theory, and Constructivist Learning Theory, the research employs a questionnaire survey to assess student's AI and CT literacy, as well as the impact of subject background and AI tool usage. Statistical analyses (t-test, ANOVA, Pearson correlation) revealed statistically significant positive associations between dimensions of AI literacy and CT; however, effect sizes were uniformly small (|r| < .10), indicating that these associations-while detectable in a large sample-have limited practical magnitude and should be interpreted with caution. Intelligent Thinking exhibited the comparatively strongest association with critical thinking, though the magnitude warrants cautious interpretation. Disciplinary differences are evident: new engineering students excel at algorithmic thinking, while new liberal arts students show strengths in human-machine collaboration. Moreover, group mean differences were observed across usage-frequency categories; however, we did not fit non-linear models, and further research is needed to verify any non-linear patterns. These findings are consistent with the co-development of AIL and CT and may inform the design of discipline-specific, differentiated educational strategies in higher education.