用语义对齐分析辅导对话中的动态变化，揭示师生角色差异。
Representation Learning to Study Temporal Dynamics in Tutorial Scaffolding
- 通过计算对话轮次与任务内容的语义相似度，量化辅导过程中的对齐程度。
- 学生对解题内容的语义对齐度与学习进展正相关，导师则早期更聚焦问题。
- 适用于评估远程辅导系统和大模型对话教学效果，尤其关注角色差异。
自适应辅导能提升学习效果，但缺乏在真实辅导对话中有效测量的方法，这一问题在远程人工辅导和基于大语言模型的系统兴起后更加突出。本文提出一种基于嵌入的分析方法，通过比对对话回合、问题陈述和正确解答的语义，捕捉辅导动态。具体采用余弦相似度衡量导师与学生贡献及任务相关内容之间的对齐程度。在包含1,576条真实数学辅导对话的Eedi Question Anchored Tutoring Dialogues数据集上应用该框架，发现任务对齐存在系统性差异，且参与者在不同阶段对问题与解题内容的依附模式各异。混合效应模型显示，角色特异的语义对齐可预测辅导进展，优于消息顺序、长度等基线特征。导师早期对问题内容的语义锚定更强；而学生对解决方案的语义对齐度虽低，但与进展呈温和正相关。结果支持辅导是一个持续的、角色敏感的语义基础过程。该方法为分析教学对话和评估会话式辅导系统提供了原理清晰的工具。
原文摘要 · Abstract (English)
Adaptive scaffolding enhances learning, yet the field lacks robust methods for measuring it within authentic tutoring dialogue. This gap has become more pressing with the rise of remote human tutoring and large language model-based systems. We introduce an embedding-based approach that analyzes scaffolding dynamics by aligning the semantics of dialogue turns, problem statements, and correct solutions. Specifically, we operationalize alignment by computing cosine similarity between tutor and student contributions and task-relevant content. We apply this framework to 1,576 real-world mathematics tutoring dialogues from the Eedi Question Anchored Tutoring Dialogues dataset. The analysis reveals systematic differences in task alignment and distinct temporal patterns in how participants ground their contributions in problem and solution content. Further, mixed-effects models show that role-specific semantic alignment predicts tutorial progression beyond baseline features such as message order and length. Tutor contributions exhibited stronger grounding in problem content early in interactions. In contrast, student solution alignment was modestly positively associated with progression. These findings support scaffolding as a continuous, role-sensitive process grounded in task semantics. By capturing role-specific alignment over time, this approach provides a principled method for analyzing instructional dialogue and evaluating conversational tutoring systems.
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