The Effects of University Students' Digital Learning Competencies on AI Knowledge and Importance: Focusing on the Mediating Effect of AI beliefs

Objectives The purpose of this study is to investigate the effect of digital learning capabilities on the level and importance of AI knowledge among university students, and to statistically analyze the mediating effect of AI beliefs in this process. Methods For this study, we surveyed 309 students at four-year universities across the country. SPSS 25.0 and AMOS 23.0 were used to analyze the trend and normality of the study variables and correlation by Pearson's correlation. The measurement model was examined through confirmatory factor analysis, while the structural model was examined through structural equation modeling. The mediating effects were tested for statistical significance using the bootstrapping method with a two-sided test at a 95% confidence level. Results The main results are as follows: First, The research variables all showed values above 3.0; however, their importance was higher compared to the level of AI knowledge. We found a positive correlation between digital learning capabilities and AI beliefs, knowledge and importance of AI. Second, digital learning capabilities have a statistically significant impact on AI beliefs, AI knowledge level, and AI knowledge importance. AI beliefs have a statistically significant impact on the importance of training and knowledge in AI. Third, we find that AI beliefs partially mediate the effects of digital learning capabilities on knowledge and importance of AI. Conclusions Based on the results of this study, we would like to propose ways to respond to the changing learning environment, including AI education policies and teaching and learning methods, as AI is expected to play a key role in the future society.