AI-ASSISTED INSTRUCTIONAL LEADERSHIP AND TEACHER PEDAGOGICAL INNOVATION

Abstract

This study is a quantitative  research that examines the impact of instructional leadership with the use of artificial intelligence on pedagogical innovations among secondary school teachers, building on the recent and explicit shortage of research in the educational leadership field. Based on Hallinger's model of instructional leadership, the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technological Pedagogical Content Knowledge (TPACK) model, the study highlights five dimensions of AI-assisted instructional leadership: articulating an AI vision and strategy, providing AI resources and infrastructure, supporting AI-driven professional learning, offering pedagogical coaching with AI, and exercising ethical stewardship of AI, and how they relate to four dimensions of teacher pedagogical innovation: idea generation, idea promotion, idea implementation, and reflection and refinement. The secondary-school teachers were sampled using stratified random sampling of 372 and analyzed using descriptive statistics, Pearson correlation and multiple regression, which was based on four research objectives. The results show that AI-assisted instructional leadership has a significant positive impact on teacher pedagogical innovation (R² = 0.61, p < .001); AI-powered pedagogical coaching (β = 0.43) and AI-powered professional learning support (β = 0.38) are the most powerful predictors. The study adds empirical evidence to the body of literature that focuses on the classroom or the policy level of inquiry into AI in schools.