TOWARD A THEORY OF HUMAN-AI PEDAGOGICAL SYNERGY: A CONCEPTUAL FRAMEWORK FOR REIMAGINING THE TEACHER'S ROLE IN THE AGE OF GENERATIVE AI

In this paper, we propose a conceptual framework for human–AI pedagogical synergy, redefining the teacher’s role in the era of generative AI. This study is to understand how human teachers and AI systems can work synergistically in education, rather than competitively or separately. It fills a gap in educational theory by redefining teaching roles, pedagogical boundaries, and human-AI interaction. Building on theories of hybrid intelligence and formative assessment (e.g. Black & Wiliam, 2009), we explore how generative AI tools can complement and extend teacher expertise rather than replace it. We identify core dimensions of collaboration—feedback generation, curriculum design, learner scaffolding, and ethical oversight—and illustrate how responsibilities can be distributed across human and AI agents depending on context, task complexity, and domain knowledge. Through illustrative educational cases, we show how AI can automate routine tasks like personalized feedback or content generation, thereby freeing educators to focus on higher-order pedagogical work: adaptive facilitation, critical thinking prompts, emotional support, and value-based assessment. We also discuss essential conditions for successful synergy: AI literacy, teacher agency, ethical safeguards, and pedagogically informed design. This framework aims to guide both researchers and educational practitioners in designing and implementing teacher?filled, AI?augmented learning environments that harness the strengths of both human judgment and AI precision to foster deeper learning outcomes.