Toward the automated analysis of teacher talk in secondary ELA classrooms
Toward the automated analysis of teacher talk in secondary ELA classrooms
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DOI：
10.1016/j.tate.2021.103584
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发表时间：
2021-12-04
影响因子：
3.9
通讯作者：
Kelly, Sean P.
中科院分区：
文献类型：
--
作者：
Dale, Meghan E.;Godley, Amanda J.;Kelly, Sean P.
教师谈话的质量对学生的学习有很大的影响，然而教师获得谈话反馈的机会面临时间和成本的限制。为了解决这个问题，我们开发了一种使用自动语音识别技术分析教师谈话的半自动方法，将其与传统方法进行比较，并使用它来分析127节中学英语语言艺术课程的教师谈话特征。我们发现新方法与传统方法一致，使我们能够可靠地识别相互关联但不同的谈话特征。这些特点往往反映了对话教学。我们的研究结果有助于未来对教学话语和技术驱动的教师学习机会的研究。(c) 2021 Elsevier Ltd.版权所有。
Qualities of teacher talk strongly affect student learning, yet opportunities for teachers to receive feedback on their talk face time and cost limitations. To address this, we developed a semi-automated method of analyzing teacher talk using Automated Speech Recognition technology, compared it to traditional methods, and used it to analyze teacher talk features in 127 secondary English Language Arts lessons. We found the new method aligned with traditional methods, allowing us to reliably identify interrelated but distinct talk features. These features often reflected dialogic instruction. Our findings contribute to future studies of instructional discourse and technology-driven teacher learning opportunities. (c) 2021 Elsevier Ltd. All rights reserved.