论文标题
NCTE成绩单：基本数学课堂成绩单的数据集
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
论文作者
论文摘要
课堂话语是教学的核心媒介 - 分析它可以为教学提供一个窗口，并推动开发新工具以改善教学。我们介绍了最大的数学课堂成绩单数据集，并演示了这些数据如何帮助改善教学。该数据集由1,660 45-60分钟长的4年级和五年级的基础数学观测值组成，该观察结果由国家教师有效性中心（NCTE）在2010 - 2013年之间收集。这些匿名成绩单代表了来自4个学区的317名教师的数据，这些学区为很大程度上为历史而言是边缘化的学生提供服务。成绩单附带丰富的元数据，包括对话话语动作的转交级注释，课堂观察分数，人口统计信息，调查回答和学生考试成绩。我们证明，我们的自然语言处理模型接受了我们的转向级注释，可以学会识别对话性话语的动作，并且这些举动与更好的课堂观察分数和学习成果相关。该数据集为研究人员，教育者和政策制定者提供了几种可能性，可以学习和改善K-12指导。该数据集可在https://github.com/ddemszky/classroom-transcript-analysis中找到。
Classroom discourse is a core medium of instruction - analyzing it can provide a window into teaching and learning as well as driving the development of new tools for improving instruction. We introduce the largest dataset of mathematics classroom transcripts available to researchers, and demonstrate how this data can help improve instruction. The dataset consists of 1,660 45-60 minute long 4th and 5th grade elementary mathematics observations collected by the National Center for Teacher Effectiveness (NCTE) between 2010-2013. The anonymized transcripts represent data from 317 teachers across 4 school districts that serve largely historically marginalized students. The transcripts come with rich metadata, including turn-level annotations for dialogic discourse moves, classroom observation scores, demographic information, survey responses and student test scores. We demonstrate that our natural language processing model, trained on our turn-level annotations, can learn to identify dialogic discourse moves and these moves are correlated with better classroom observation scores and learning outcomes. This dataset opens up several possibilities for researchers, educators and policymakers to learn about and improve K-12 instruction. The dataset can be found at https://github.com/ddemszky/classroom-transcript-analysis.
