Artificial intelligence integration in instructional leadership: Impact on teacher innovation and job satisfaction

Han Guo (), Bity Salwana Alias () and Mohd Izwan Mamud ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 6, 660-669

Abstract: This study explores the impact of AI-integrated instructional leadership on teacher innovation and job satisfaction in underdeveloped regions of China. Based on the Job Demands-Resources (JD-R) model, AI-integrated leadership is conceptualized as a job resource that offers timely feedback, reduces workload, and supports innovation. Data were collected from 366 junior high school teachers and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that AI-integrated leadership significantly enhances both teacher innovation and job satisfaction, with teacher innovation partially mediating this relationship. These findings extend the JD-R framework by positioning AI-supported leadership as a technology-mediated resource that promotes professional growth and psychological well-being. The study provides practical insights for school leaders and policymakers in resource-constrained settings, suggesting that the strategic application of AI can alleviate teacher burden, foster innovative practices, and improve overall job satisfaction.

Keywords: AI-Integrated leadership; Artificial intelligence; Instructional leadership; Principal leadership; Secondary school; Structural Equation Modeling; Teacher innovation; Teacher job satisfaction. (search for similar items in EconPapers)
Date: 2025
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