The advent of Generative Artificial Intelligence (GAI) has revolutionized the field of writing, marking a shift towards human-AI collaborative writing in education. However, the dynamics of human-AI interaction in the collaborative writing process are not well understood, and thus it remains largely unknown how human learning can be effectively supported with such cutting-edge GAI technologies. In this study, we aim to bridge this gap by investigating how humans employ GAI in collaborative writing and examining the interplay between the patterns of GAI usage and human writing behaviors. Considering the potential varying degrees to which people rely on GAI usage, we proposed to use Dynamic Time Warping time-series clustering for the identification and analysis of common temporal patterns in AI usage during the human-AI collaborative writing processes. Additionally, we incorporated Epistemic Network Analysis to reveal the correlation between GAI usage and human writing behaviors that reflect cognitive processes (i.e., knowledge telling, knowledge transformation, and cognitive presence), aiming to offer insights for developing better approaches and tools to support human to learn effectively via such human-AI collaborative writing activities. Our findings reveal four major distinct temporal patterns in AI utilization and highlight significant correlations between these patterns and human writing behaviors. These findings have significant implications for effectively supporting human learning with GAI in educational writing tasks.

翻译：生成式人工智能（GAI）的出现彻底改变了写作领域，标志着教育领域向人机协作写作的转变。然而，人机交互在协作写作过程中的动态机制尚未得到充分理解，因此，如何利用此类前沿的GAI技术有效支持人类学习在很大程度上仍是未知的。本研究旨在弥合这一差距，通过探究人类如何在协作写作中运用GAI，并检验GAI使用模式与人类写作行为之间的相互作用。考虑到人们依赖GAI使用的程度可能存在差异，我们提出使用动态时间规整时间序列聚类方法，以识别和分析人机协作写作过程中AI使用的常见时间模式。此外，我们结合了认知网络分析，以揭示GAI使用与反映认知过程（即知识陈述、知识转化和认知临场感）的人类写作行为之间的相关性，旨在为开发更好的方法和工具提供见解，以支持人类通过此类人机协作写作活动进行有效学习。我们的研究结果揭示了AI利用的四种主要不同时间模式，并强调了这些模式与人类写作行为之间的显著相关性。这些发现对于在教育写作任务中利用GAI有效支持人类学习具有重要意义。