Towards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence

2025-11-24

AI Summary

The widespread adoption of generative AI (GenAI) in education enhances instructional efficiency but concurrently risks undermining teacher autonomy, fostering cognitive atrophy, and accelerating occupational deprofessionalization. Drawing on systematic literature review, meta-synthesis, and empirical data, this study develops the first five-dimensional theoretical framework for teacher–AI collaboration—comprising transactional, contextual, operational, practical, and synergistic dimensions—and proposes a corresponding five-stage evolutionary pathway from task automation to human–AI co-decision-making. Its core contribution is the conceptualization of a “negotiated co-reasoning” collaboration model, grounded in complementary and mutually reinforcing competencies rather than substitution. Furthermore, the study advances an ethically grounded, empirically validated implementation model for human–AI collaboration, offering both theoretical foundations and actionable guidance for teacher professional development and the deep integration of educational intelligence.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Philosophy and Ethics of AI: Artificial General Intelligence
• Intelligent Robots: Embodied AI

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Generative artificial intelligence (GenAI) is increasingly used in education, posing significant challenges for teachers adapting to these changes. GenAI offers unprecedented opportunities for accessibility, scalability and productivity in educational tasks. However, the automation of teaching tasks through GenAI raises concerns about reduced teacher agency, potential cognitive atrophy, and the broader deprofessionalisation of teaching. Drawing findings from prior literature on AI in Education, and refining through a recent systematic literature review, this chapter presents a conceptualisation of five levels of teacher-AI teaming: transactional, situational, operational, praxical and synergistic teaming. The framework aims to capture the nuanced dynamics of teacher-AI interactions, particularly with GenAI, that may lead to the replacement, complementarity, or augmentation of teachers' competences and professional practice. GenAI technological affordances required in supporting teaming, along with empirical studies, are discussed. Drawing on empirical observations, we outline a future vision that moves beyond individual teacher agency toward collaborative decision-making between teachers and AI, in which both agents engage in negotiation, constructive challenge, and co-reasoning that enhance each other's capabilities and enable outcomes neither could realise independently. Further discussion of socio-technical factors beyond teacher-AI teaming is also included to streamline the synergy of teachers and AI in education ethically and practically.

Problem

• Addressing teacher adaptation challenges to GenAI integration in education
• Mitigating concerns about teacher agency reduction and professional devaluation
• Developing collaborative teacher-AI frameworks for enhanced educational outcomes

Innovation

• Five levels of teacher-AI teaming framework
• Collaborative decision-making through negotiation and co-reasoning
• Synergistic interactions to enhance capabilities and outcomes