AI-ASSISTED INSTRUCTIONAL LEADERSHIP AND TEACHER PEDAGOGICALINNOVATION

Authors

  • Zahra Begum BS Psychology Fatima Jinnah Women College Skardu, Affiliated with Karakoram International University Gilgit Author
  • Syed Zaheer Abbas PhD Scholar, Department of Education, The University of Lahore, Punjab Pakistan Author
  • Syeda Siddiqa BS Psychology ,Fatima Jinnah Woman College affiliated with Karakoram International University Gilgit Author
  • Shahid Ali Master in Education,Department of Educational Development Karakorum International University Gilgit-Baltistan Author

Keywords:

AI-assisted instructional leadership, teacher pedagogical innovation, generative AI in education, school principals, digital leadership, TPACK, UTAUT, Hallinger, teacher innovative behaviour, secondary education

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.

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Published

2026-03-18

Issue

Section

Articles