Teacher-Student Dynamics in AI-Driven Language Education in the Post-Truth Era

Background: Artificial intelligence (AI) inaugurates a new educational era that compels a rethinking of established pedagogical paradigms. Within the epistemological uncertainty of the post-truth era, it has reconfigured teacher-student dynamics (TSD) in ways that challenge traditional assumptions about agency and authority in the classroom. Purpose: The article addresses the disruption of TSD under the evolving force of AI, with particular attention to tensions in learner–teacher agency asymmetry in the context of AI-mediated language education. Conceptual Contribution: Positioned within the genre of conceptual scholarship, the article introduces a model that delineates six interrelated dimensions of TSD disruption in the age of AI. The framework does not merely describe emerging shifts but systematizes them into an interpretive structure that traces the trajectory of TSD evolution. In doing so, it foregrounds the broader implications of these transformations for educational policy, pedagogical design, and research agenda in language education. Implications: The analysis contends that AI realities not only govern but also reshape the human texture of pedagogical interaction. Preserving the integrity of the language classroom requires learning designs that foreground dialogic engagement and epistemic trust, while constructively integrating AI innovations.