Where's the Structure? A Systematic Literature Review of Empirical Research on Human-AI Collaboration and Hybrid Intelligence for Learning

2026-05-30

AI Summary

Current human-AI collaborative learning lacks effective structural frameworks, limiting its efficacy in educational contexts. Addressing this gap, this study conducts a systematic literature review of 62 empirical studies to systematically distill structured design knowledge for human-AI collaborative learning. It clarifies the underlying collaborative processes, mechanisms, and representative application scenarios. The work not only proposes a structural model of collaborative learning within hybrid intelligence education but also identifies critical research gaps. By doing so, it establishes a theoretical foundation and provides a guiding framework for the future design and implementation of AI-enhanced collaborative learning systems.

Abstract

Artificial intelligence (AI) has been applied across educational contexts to support learning. One approach to such support is "human-AI collaboration" (also termed "hybrid intelligence"), where human(s) and AI components interact to promote human learning. However, as in human-to-human computer-supported collaborative learning (CSCL), unstructured interaction does not necessarily produce an effective learning experience. This paper reports a systematic literature review of empirical studies (N=62) on human-AI collaboration and hybrid intelligence for learning support. The review characterizes collaboration processes, their structures, and contexts of application. It also extracts emerging design knowledge and research gaps. Researchers and technology designers can use these findings as a starting point for structuring more effective AI-enhanced technologies for collaboration, in educational practice and future research.

Problem

• human-AI collaboration
• hybrid intelligence
• structured interaction
• learning support
• systematic literature review

Innovation

• human-AI collaboration
• hybrid intelligence
• systematic literature review
• structured interaction
• AI-enhanced learning