Generative Artificial Intelligence (GenAI) Competence and Digital Leadership as Pathways to Teacher Performance

Abstract

Artificial Intelligence (AI) is here to stay. Its rapid advancement has redefined various aspects of modern life, including education. The integration of AI in education has transformed how teachers teach, how students learn, and how leaders lead. This study examined the relationships between Generative Artificial Intelligence (GenAI) competence and teachers’ performance, specifically the mediating effect of digital leadership practices (DLP) in school and the moderating effects of professional profile variables. The study also proposed the GenAI –DLP Pathways Design. Using a cross-sectional survey method with descriptive-correlational and regression-based procedural analysis, the study administered a survey questionnaire to a stratified sample of 221 private secondary school teachers. Results revealed that teachers possess a high level of GenAI competence (M = 4.17, “Competent”) and demonstrate very satisfactory performance (M = 4.45). Statistical analysis confirmed strong positive relationships between GenAI competence and teacher performance (r (220) = .733, p < .01), between GenAI competence and digital leadership practices in school (r (220) = .752, p < .01), and between digital leadership practices in school and teacher performance (r (220) = .744, p < .01). Notably, digital leadership practices in school partially mediated relationship between GenAI competence and teacher performance, accounting for 45.601% of the total effect (β = 0.286, p <.001), while the profiles showed no significant moderating effect. These findings supported the proposed GenAI Competence - Digital Leadership Pathways design, which underscores the necessity of aligning individual GenAI skills with institutional leadership to enhance teacher performance.