梳理62项研究，揭示人机协作学习的结构化设计关键
Where's the Structure? A Systematic Literature Review of Empirical Research on Human-AI Collaboration and Hybrid Intelligence for Learning
- 系统综述62项实证研究，提炼人机协作模式与结构特征
- 发现无结构协作难以促进有效学习，需明确交互框架
- 为教育AI设计者提供可复用的协作结构指南
人工智能已在教育场景中用于支持学习，其中一种方式是“人机协作”（又称“混合智能”），即人类与AI组件互动以促进学习。然而，如同人与人之间的计算机支持协作学习（CSCL）一样，缺乏结构的互动未必带来有效的学习体验。本文报告了一项针对62项实证研究的系统文献综述，分析了人机协作的学习支持过程、其结构特征及应用场景。研究还提炼出新兴的设计知识并识别了研究空白。该成果可为教育实践和未来研究中的技术设计者提供起点，以构建更有效的智能化协作工具。
原文摘要 · Abstract (English)
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.
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