Some Challenges and Future Prospects for Teachers in The Context of Artificial Intelligence

Abstract

This study explores teacher professional development in the AI era by conducting an in-depth analysis of global educational policy frameworks, resource allocation, teaching competencies, and ethical considerations. Its key findings highlight five critical challenges faced by educators:1)The pressure to update knowledge and integrate interdisciplinary insights;2)The shift from traditional teaching methods to innovative approaches;3)The need to balance role definition with career advancement;4)The handling of ethical dilemmas and academic integrity issues;5)he ensuring of data privacy and security compliance.To tackle these challenges, future development strategies should focus on three dimensions: role evolution, human-machine collaboration, and continuous learning. Theoretically, this research delineates the scope of challenges in AI-enhanced teacher development, identifies their interconnections, and clarifies the components and relationships of future career trajectories. These findings lay a theoretical foundation and provide a research framework for exploring the interaction mechanisms between AI and teachers in education.From a practical standpoint, teachers should proactively embrace the pressures of knowledge renewal and interdisciplinary integration. They need to enhance their teaching competencies, adapt their instructional methods, clarify their professional roles, cultivate a mindset for continuous learning, and prioritize educational ethics and data privacy security. For policymakers, it is essential to formulate reasonable educational policy frameworks based on national educational realities, provide sufficient resource support, establish robust teacher training systems, and facilitate the role evolution and human-machine collaboration of educators. This will enable better adaptation to AI-driven educational environments and promote high-quality development in the education sector.​