Transformational Leadership, AI Assistance, and Teachers’Organizational Commitment: Evidence from China's Primary Education Reform
Under China's "double reduction" policy (reducing academic burden and workload), while the goal of education reform is to alleviate students' academic burden, the implementation of this policy has led to greater work pressure and professional distress for primary school teachers, particularly in terms of workload, emotional stress, and professional commitment.The increasing prevalence of teacher burnout and declining organizational commitment not only affects the quality of education but also has profound implications for teachers' career development and the sustainable development of schools.This study aims to explore the relationship between transformational leadership, AI-assisted instruction, and teacher burnout and organizational commitment.The theoretical framework integrates Meyer and Allen's three-dimensional organizational commitment model with Bass's transformational leadership theory, and employs a qualitative research method primarily based on interviews to systematically analyze teachers' psychological states and work behaviors.The results show that transformational leadership significantly alleviates teacher burnout and effectively enhances their organizational commitment to the school; simultaneously, AI-assisted instruction tools also play a positive role in reducing teachers' workload, improving teaching efficiency, and promoting teachers' emotional well-being.This research not only provides education administrators with strategies for improving teacher well-being amidst policy changes but also offers new practical pathways for the sustainable development of schools.
Authors
- Bity Salwana Alias (ORCID: https://orcid.org/0000-0001-8769-9341)
- Xiao Xiaolin
Institutions
- National Institutes of Biotechnology Malaysia (MY)
- National University of Malaysia (MY)
Publication Details
- Journal
- International Journal of Academic Research in Business and Social Sciences
- Published
- 2025-11-08
- DOI
- https://doi.org/10.6007/ijarbss/v15-i11/26872
- Primary Topic
- E-Learning and COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 0.00