Data that contextualizes student interactions with online learning systems can be challenging to obtain. This study looks at the rhetorical strategies of a novel method for conducting in-the-moment Data-Driven Classroom Interviews (DDCIs). By using Ordered Network Analysis (ONA) to reanalyze data from Wei et al.'s (2025) Epistemic Network Analysis, we better account for the sequences in which these rhetorical strategies emerge during the interview process. Specifically, we examine how five rhetorical strategies by interviewers relate to five possible rhetorical strategies used in student responses. As with the previous study, results demonstrate minor differences in how students with high and low situational interest respond. Namely, whereas students with high situational interest show moderately higher levels of enthusiasm, students with low situational interest are more likely to respond to interviewers with an explanation. However, overall this study confirms that there are few interviewer-driven differences in these interviews, and it documents that interviewers are following guidelines to rely upon open-ended questions

翻译：获取能够情境化学生与在线学习系统互动的数据颇具挑战。本研究考察了一种新颖的即时数据驱动课堂访谈（DDCI）方法的修辞策略。通过运用有序网络分析（ONA）重新分析Wei等人（2025年）认知网络分析的数据，我们更好地解释了访谈过程中这些修辞策略出现的序列。具体而言，我们探究了访谈者五种修辞策略与学生回应中五种可能修辞策略之间的关联。与先前研究一致，结果显示高情境兴趣与低情境兴趣学生的回应方式存在细微差异。具体表现为：高情境兴趣学生展现出适度更高的参与热情，而低情境兴趣学生更倾向于以解释性话语回应访谈者。然而，本研究整体证实了这些访谈中由访谈者驱动的差异较小，并记录到访谈者遵循了依赖开放式问题的指导原则。