Artificial Intelligence (AI) in Higher Education: Digital Adaptability, General Self-Efficacy, and Student Attitudes

Artificial intelligence (AI) has become increasingly visible in higher education, making it important to understand how students in this context evaluate AI in general. Although students’ attitudes toward AI have been widely examined, less is known about the relative roles of broad psychological resources and technology-related adaptive capacities in shaping these attitudes. This study examined whether digital adaptability and general self-efficacy were associated with students’ general attitudes toward AI and whether they showed distinct comparative associations within the tested model. Using a cross-sectional design, data were collected from 550 undergraduate and master’s students enrolled in technical programs at a large university. Correlational analyses, group comparisons, and hierarchical regression analyses were conducted, controlling for faculty and year of study. The findings showed that both digital adaptability and general self-efficacy were positively associated with students’ attitudes toward AI; however, only digital adaptability showed a statistically significant unique association within the regression model. This comparative pattern should be interpreted as association-based rather than as evidence of explanatory superiority. The results suggest that students’ general attitudes toward AI are associated with adaptive digital resources, although the findings should not be interpreted as direct evidence regarding AI-supported learning environments, curriculum design, instructional strategies, or actual AI use.