We propose a learning analytics-based methodology for assessing the collaborative writing of humans and generative artificial intelligence. Framed by the evidence-centered design, we used elements of knowledge-telling, knowledge transformation, and cognitive presence to identify assessment claims; we used data collected from the CoAuthor writing tool as potential evidence for these claims; and we used epistemic network analysis to make inferences from the data about the claims. Our findings revealed significant differences in the writing processes of different groups of CoAuthor users, suggesting that our method is a plausible approach to assessing human-AI collaborative writing.

翻译：我们提出了一种基于学习分析的方法，用于评估人类与生成式人工智能的合作写作。以循证设计为框架，我们采用知识陈述、知识转化和认知存在等要素来识别评估主张；利用从CoAuthor写作工具收集的数据作为这些主张的潜在证据；并运用认知网络分析从数据中推断相关主张。研究结果表明，不同CoAuthor用户群体的写作过程存在显著差异，验证了我们方法用于评估人机合作写作的可行性。