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

Year: 2025

Type: article

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.

Source: International Journal of Innovative Research and Scientific Studies

DOI: 10.53894/ijirss.v8i6.9666

Authors: Han Guo, Bity Salwana Alias, Mohd Izwan Mamud

Institution: National University of Malaysia

Language: English

Topic: School Leadership and Teacher Performance

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDGs: Quality education, Decent work and economic growth, Industry, innovation and infrastructure

Open Access status: diamond

Funder: Universiti Kebangsaan Malaysia