Evolving Models of AI-Driven Teacher Professional Development: Theoretical Insights, Trends, and Future Directions

Teacher Professional Development (TPD) is widely recognized as a cornerstone of educational reform and instructional quality improvement (Dinh, Do, Tran, & Phan, 2020). Effective TPD programs enhance teachers' professional competencies, promote lifelong learning, and contribute to improved student outcomes (Garrett & Steinberg, 2023). However, traditional TPD models—often based on standardized, government-led training programs—have been criticized for their rigidity, lack of adaptability, and misalignment with real-world classroom demands (Darling-Hammond et al., 2017). These models predominantly focus on one-size-fits-all training workshops and certification-based learning, which fail to accommodate the evolving needs of modern educators, particularly in dynamic and technology-driven learning environments. Additionally, disparities in access to quality TPD programs across regions and countries have created significant challenges in ensuring consistent teacher upskilling and professional development worldwide.(Ganimian & Murnane, 2016) JEL Codes: I21, I28, O33 Keywords: Teacher Professional Development, AI in Education, Digital Learning, Competency-Based Training, Reflective Teaching, Teacher Knowledge Framework.