Fostering Innovative Teaching Practices in Oman: The Influence of Change-Oriented Leadership, Educational Supervisor Support, and Artificial Intelligence Self-Efficacy

• In Event: Frontiers of AI and Immersive Technology in Teaching and Learning

Proposal

Abstract:
This study investigates the impact of change-oriented leadership and educational supervisor support on fostering innovative teaching practices within Oman's public schools, with a particular focus on the mediating role of Artificial Intelligence (AI) Self-Efficacy. The research assesses both the direct and indirect effects of these factors on teacher innovation, in line with the increasing integration of AI in education.
A quantitative methodology was employed, with data collected from a sample of (n = 521) teachers across various public schools in Oman using validated instruments. Structural equation modeling was utilized as the primary analytical technique. The results revealed that change-oriented leadership and educational supervisor support significantly contribute to enhancing innovative teaching practices. Moreover, AI Self-Efficacy was found to be a crucial mediator, further strengthening the positive effects of leadership and support on teacher innovation.
The findings provide empirical evidence that principal leadership and educational supervisor support play a vital role in enabling teachers to effectively integrate advanced technologies like AI into their instructional methods. These results offer valuable insights for educational policymakers and school leaders in Oman, guiding the development of strategies that promote teacher innovation and advance the overall quality of the educational system.
Keywords:
Innovative Teaching Practices, Change-Oriented Leadership, Educational Supervisor Support, Teacher Innovative Work Behavior, AI Self-Efficacy, Public Schools, Oman

Relevance to CIES 2025:
As the field of education increasingly embraces the integration of Artificial Intelligence (AI) and innovative teaching practices, the findings of this study are particularly relevant to the Comparative and International Education Society (CIES) 2025 conference. The conference theme, which envisions education in a digital society, aligns well with this research's exploration of how change-oriented leadership, educational supervisor support, and AI self-efficacy can drive innovation in public schools. This study offers insights into how these factors can be leveraged to meet the global demand for educational systems that prepare students for a technology-driven future.

Need, Topic, Interest, or Issue Addressed:
The study addresses the pressing need for educational systems to innovate in response to the demands of a knowledge-based economy, particularly in the context of Oman's Vision 2040. This national agenda prioritizes the transformation of education to ensure technological advancement and alignment with international standards. The research focuses on how leadership and support structures within schools can facilitate the adoption of AI-driven teaching practices, thereby enhancing teacher innovation and improving student outcomes.

Methods and Guiding Frameworks:
The research employs a quantitative methodology, utilizing structural equation modeling (SEM) to analyze data collected from a representative sample of 520 teachers in Oman's public schools. The study is grounded in frameworks of change-oriented leadership and AI self-efficacy, which are essential for understanding how leadership and support mechanisms can foster innovation in teaching. These frameworks are applicable in various educational contexts, making the findings relevant for addressing similar challenges in other regions.

Successes and Lessons Learned:
The study found that change-oriented leadership and educational supervisor support significantly contribute to innovative teaching practices, with AI self-efficacy serving as a crucial mediator. These findings suggest that effective leadership and strong support systems are vital for fostering an environment conducive to innovation. However, knowing what is now known, more targeted professional development and resources for enhancing AI self-efficacy among teachers could further amplify these effects.

Impact and Assessment:
The impact of the study is evident in its contribution to understanding the dynamics of teacher innovation within the framework of AI integration in education. The research provides empirical evidence that leadership and support are critical in enabling teachers to effectively use AI in their classrooms, which in turn enhances teaching practices and student learning outcomes. The impact was assessed through the robust analytical approach of SEM, which allowed for a comprehensive examination of the relationships between the variables.

Conceptual/Theoretical Contribution:
The study builds on existing work in the fields of educational leadership and innovation by integrating the concept of AI self-efficacy into the discussion of teacher innovation. This theoretical contribution is particularly relevant in the linguistic, national, and geopolitical context of Oman, where educational reform is being driven by the national Vision 2040 agenda. The findings have significant implications for future practice, policy, and theory, particularly in how AI can be integrated into education to foster innovation.

Originality and Importance:
The study offers an original contribution by linking change-oriented leadership and AI self-efficacy to innovative teaching practices, providing new insights into how these factors interact. This research is important because it highlights the potential for AI to transform educational practices, offering a model that can be adapted to other contexts where similar challenges exist. The study advances our understanding of the critical role that leadership and support play in driving educational innovation, making it a valuable
contribution to the field.

Empirical Research Contribution:
The empirical framework guiding the research questions is grounded in the intersection of educational leadership and AI integration. The study uses a robust methodological approach, informed by existing literature on innovation in education, to collect and analyze data. The methods and results support the conclusion that leadership and support structures are key to fostering innovation, making the findings both original and critical for understanding how to effectively implement AI-driven teaching practices in schools.

Author

• Yasser F. Hendawy Al Mahdy, Sultan Qaboos University