Longitudinal Mixed Methods Study of Teacher Professional Identity Reconstruction in Ai Enhanced Decision Making Systems

This study investigates how teachers’ professional identities are reconstructed as their roles evolve within AI-enhanced decision-making systems, drawing on a longitudinal mixed-methods design based on capability trajectories. In the context of information-based education, traditional teacher identities face new challenges such as online public opinion management and interdisciplinary teaching, necessitating the establishment of an identity reconstruction framework based on capability development.