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Towards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence

arXiv 2511.19580 ↗First posted 24 Nov 2025cs.CY cs.AI cs.HCcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 48 references that are in the map. First posted on arXiv 24 Nov 2025.

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12 of 48 references.

References · 12

  1. 2023The Learnability of In-Context Learningcited by 127
  2. 2024When combinations of humans and AI are useful: A systematic review and meta-analysiscited by 106
  3. 2025Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversationscited by 96
  4. 2025A Survey on Post-training of Large Language Modelscited by 54
  5. 2024TeachTune: Reviewing Pedagogical Agents Against Diverse Student Profiles with Simulated Studentscited by 25
  6. 2025A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Educationcited by 11
  7. 2024The Interplay of Learning, Analytics, and Artificial Intelligence in Education: A Vision for Hybrid Intelligencecited by 9
  8. 2024PromptHive: Bringing Subject Matter Experts Back to the Forefront with Collaborative Prompt Engineering for Educational Content Creationcited by 9
  9. 2021An AI-based Learning Companion Promoting Lifelong Learning Opportunities for Allcited by 4
  10. 2022A Hierarchical Framework for Collaborative Artificial Intelligencecited by 2
  11. 2024Adult learners recall and recognition performance and affective feedback when learning from an AI-generated synthetic videocited by 1
  12. 2025Evaluating Trust in AI, Human, and Co-produced Feedback Among Undergraduate Studentscited by 1

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