Mutlu Cukurova (2026) — Handbook of AI and the Future of Education (forthcoming) 📄 Full text (arXiv)
Asks what is gained and lost when 'collaboration' is applied freely to human-AI interaction. Argues true collaboration requires symmetric/negotiated relationship, shared goals, low and shifting division of labor, interactive exchange, and mutual modeling. Introduces a 5-level diagnostic taxonomy: Transactional, Situational, Operational, Praxical, and Synergistic. Only Synergistic satisfies full collaborative conditions. Most current human-AI interaction is consultation, governance, delegation, or instruction.
Key Contributions
- Introduces a 5-level taxonomy of human-AI teaming; most current AI interaction is consultation/delegation, not true collaboration.
Related Pages
- ai-k12-evidence-base — Empirical evidence on AI in K-12 education outcomes
- intelligent-tutoring — Automated tutoring systems and their evaluation
- student-experience — Student perspectives on AI in education
- learning-analytics — Data-driven approaches to understanding learning
- llm-feedback-programming-classroom — LLM feedback in classroom settings
Citation
APA: Mutlu Cukurova (2026). What do you mean by human-AI collaboration: Prerequisite functions and the affordances needed to achieve it. arXiv:2606.15509. Handbook of AI and the Future of Education (forthcoming).