Related Experiment Videos
AI literacy and college students' innovative thinking: chain mediating roles of AI interaction perception and AI
Xiangui Bu1, Wenqi Wang2, Xuesong Ji3
1School of Competitive Sports, Shandong Sport University, Rizhao, China.
Objective:
Apart 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.
Methods:
This 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.
Results:
The 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.
Conclusion:
AI 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.
Related Concept Videos
Non-equilibrium in the Cell
Intelligence
Introduction to Cognitive Psychology
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Role-Based Identity