Predicting Specificity in Classroom Discussion
This work addresses the need for automated tools to assess discussion quality in education, though it appears incremental as it builds on prior small-scale studies.
The paper tackled the problem of predicting specificity in classroom discussions, achieving state-of-the-art performance with interpretable features for pedagogical analysis.
High quality classroom discussion is important to student development, enhancing abilities to express claims, reason about other students' claims, and retain information for longer periods of time. Previous small-scale studies have shown that one indicator of classroom discussion quality is specificity. In this paper we tackle the problem of predicting specificity for classroom discussions. We propose several methods and feature sets capable of outperforming the state of the art in specificity prediction. Additionally, we provide a set of meaningful, interpretable features that can be used to analyze classroom discussions at a pedagogical level.