AI Insight
This study of 1,000 Chinese university students investigated how artificial intelligence literacy influences innovative thinking capabilities. The research found that AI literacy significantly predicts innovative thinking both directly and indirectly through two mediating pathways: students' perception of their interactions with AI systems and their attitudes toward AI. When both mediators were included in the model, they fully mediated the relationship, with the chain pathway of AI literacy leading to interaction perception, then to attitudes, and finally to innovative thinking being particularly significant.
Why it matters
The findings suggest that enhancing AI literacy in higher education could be an effective strategy for developing students' innovative thinking skills, which are increasingly important in the modern workforce. Educational institutions may benefit from not only teaching AI technical skills but also fostering positive AI interactions and attitudes to maximize innovation outcomes.
Understand the Science
ObjectiveApart from progress in productivity, the rise of artificial intelligence (AI) technologies has increased requirements for talent cultivation in colleges and universities. Despite the rapid integration of artificial intelligence in higher education, the mechanisms through which AI literacy influences students’ innovative thinking remain insufficiently understood. Based on the social cognitive and technology affordance theories, this study discusses the promoting effect of AI literacy on college students’ innovative thinking and conducts an in-depth exploration of specific mechanisms of AI literacy that influence innovative thinking.MethodsThis study employed a stratified random sampling approach, recruiting students from four universities. A total of 1,000 university students were invited to complete an online questionnaire to ensure adequate statistical power. The study adopted four standardized scales, namely, Artificial Intelligence Literacy Scale, Innovative Thinking Scale, Perceived Interactivity of Learner-AI Interaction Scale, and Artificial Intelligence Attitude Scale. SPSS 26.0 was used for statistical analysis, PROCESS macro was employed to test the proposed chain mediation model, and the bootstrap method was used to verify the significance of different paths.ResultsThe results revealed significant gender differences in AI attitudes and significant grade-level differences in perceived AI interaction. Significant correlations were found between AI literacy and innovative thinking, perceived AI interaction, and AI attitudes (r = 0.139, p < 0.001; r = 0.366, p < 0.001; r = 0.436, p < 0.001). AI interaction perception and AI attitudes individually played mediating roles between AI literacy and innovative thinking, respectively. Meanwhile, AI interaction perception and AI attitudes played chain mediating roles between AI literacy and innovative thinking.ConclusionAI literacy can significantly positively predict the innovative thinking. It influences innovative thinking not only through the independent mediating roles of perceived AI interaction and AI attitudes but also through the sequential mediating pathway of AI literacy → AI interaction perception → AI attitudes → innovative thinking. The direct path is fully mediated once perceived AI interaction and AI attitudes are entered. These findings suggest that improving AI literacy is an effective strategy for enhancing university students' innovative thinking, and strengthening perceived AI interactions and attitudes may further amplify this effect.