Automated Feedback on Discourse Moves: Teachers' Perceived Utility of a Big Data Tool

Automated Feedback on Discourse Moves: Teachers' Perceived Utility of a Big Data Tool
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话语移动的自动反馈:教师对大数据工具的感知效用

DOI:
10.3102/1887987
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发表时间:
2022
期刊:
Proceedings of the 2022 AERA Annual Meeting
影响因子:
--
通讯作者:
Karla Scornavacco
Karla Scornavacco
中科院分区:
--
文献类型:
--
作者:
Karla Scornavacco

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利用新技术提供课堂话语的自动反馈,为教育工作者提供了一个独特的机会,让他们对自己的教学进行自我反思,特别是确保教学环境对所有学生都是公平和富有成效的。需要更多关于教师如何体验自动化数据工具的信息,包括他们认为与日常教学相关和有帮助的内容。这项混合方法的研究探讨了21名数学教师在两年多的时间里对大数据工具的看法和参与,该工具分析了课堂录音,并近实时地生成有关他们话语实践的信息。研究结果显示,教师认为该工具具有实用性,但具体的反馈,教师认为最有用的改变随着时间的推移。此外,在这两年中使用该工具的教师随着时间的推移增加了他们对谈话动作的使用,这表明他们正在做出改变,因为他们对个性化反馈进行了审查。这些发现为开发基于人工智能的大数据工具提供了有希望的方向,这些工具有助于塑造教师的学习和教学,特别是具有强大感知效用的工具。
Using new technology to provide automated feedback on classroom discourse offers a unique opportunity for educators to engage in self-reflection on their teaching, in particular to ensure that the instructional environment is equitable and productive for all students. More information is needed about how teachers experience automated data tools, including what they perceive as relevant and helpful for their everyday teaching. This mixed-methods study explored the perceptions and engagement of 21 math teachers over two years with a big data tool that analyzes classroom recordings and generates information about their discourse practices in near real-time. Findings revealed that teachers perceived the tool as having utility, yet the specific feedback that teachers perceived as most useful changed over time. In addition, teachers who used the tool throughout both years increased their use of talk moves over time, suggesting that they were making changes due to their review of the personalized feedback. These findings speak to promising directions for the development of AI-based, big data tools that help shape teacher learning and instruction, particularly tools that have strong perceived utility.
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