课堂互动的研究长期以来分为大规模观察和深入的民族志工作。我们提出了一个沿着三个维度映射该方法空间的框架——规模,持续时间,和模态——其中研究'的位置决定了它所揭示和掩盖的内容。我们通过对话教学的对比研究来说明这一点——Howe 等人。 (2019) 以及 Snell 和 Lefstein (2018)——以及对主要研究人员的采访, 围绕三个问题组织: 什么可以操作, 什么机制变得可见, 以及什么转化为实践。然后我们研究人工智能如何扩展这个空间以及该框架如何指导研究和工具设计。
Research on classroom interaction has long been divided between large-scale observation and in-depth ethnographic work. We propose a framework mapping this methodological space along three dimensions--scale, duration, and modality--where a study的 position shapes what it reveals and obscures. We illustrate it through contrasting studies of dialogic teaching--Howe et al. (2019) and Snell and Lefstein (2018)--and an interview with the lead researchers, organized around three questions: what can be operationalized, what mechanisms become visible, and what translates to practice. We then examine how AI is expanding this space and how the framework can guide research and tool design.
科目: 人工智能 (cs.AI); 计算与语言 (cs.CL); 计算机与社会 (cs.CY)
Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computers and Society (cs.CY)