What do you say? A pilot study investigating student responses in Data Driven Classroom Interviews
Jaclyn Ocumpaugh, Zhanlan Wei, Amanda Barany, Xiner Liu, Andres Felipe Zambrano, Ryan Baker, Camille Gioradno

TL;DR
This pilot study analyzes student responses in Data-Driven Classroom Interviews using Ordered Network Analysis to understand rhetorical strategies and their relation to student engagement levels.
Contribution
It introduces the use of Ordered Network Analysis to reanalyze interview data, providing new insights into rhetorical strategies during classroom interviews.
Findings
Students with high interest show more enthusiasm.
Students with low interest tend to give explanations.
Few interviewer-driven differences observed.
Abstract
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…
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Taxonomy
TopicsOnline Learning and Analytics · Educational Assessment and Improvement · Statistics Education and Methodologies
