Published on March 2025 | Artificial Intelligence, Higher Education, Learning, Teaching Strategies, Literacy

Gender differences on the impact of AI self-efficacy on AI anxiety through AI self-competency: A moderated mediation analysis

Artificial Intelligence (AI) is taking the educational system by storm due to its various implications and endless possibilities. Nevertheless, the teachers, the schools, and most importantly, the students have different perspectives on using AI in their learning experience, especially when gender is involved. In this study, the proponents delve into determining whether gender differences moderate the impact of AI self-efficacy (AISE) on the influence of AI anxiety (AIA) on AI self-competency (AISC). Using a quantitative explanatory research design, the proponents investigated 1,006 students' perspectives regarding AI self-efficacy, AI anxiety, and AI self-competency during the second semester of the academic year 2024-2025. The investigation employed an adapted instrument to determine AI self-efficacy, AI anxiety, and AI self-competency among students. Statistical analysis employed mean and standard deviation and Hayes' Process Macro for the moderation and mediation analysis. In general, the students exhibited a moderate degree of self-efficacy and self-competency in AI, as well as a moderate level of anxiety. Additionally, the investigation revealed that AISE predicts AISC, and AISC is associated with decreased AIA. However, the direct influence of AISE on AIA was insignificant statistically, while the moderated mediation index was also insignificant. In conclusion, gender does not significantly influence how AISC mediates the relationship between AISE and AIA in the study. Based on findings of the study, the paper recommended essential programs and activities to help students prepare for AI integration into their learning experience.