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
复制标题
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:
影响因子:
--
通讯作者:
Karla Scornavacco
中科院分区:
文献类型:
--
作者:
Karla Scornavacco
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.
影响因子:
8.2
作者:
Sean Kelly;A. Olney;P. Donnelly;M. Nystrand;S. D’Mello
通讯作者:
Sean Kelly;A. Olney;P. Donnelly;M. Nystrand;S. D’Mello
影响因子:
2.3
作者:
Hofmann R
通讯作者:
Hofmann R
DOI:
10.1007/s11423-016-9455-4
发表时间:
2016
期刊:
Educational Technology Research and Development
影响因子:
--
作者:
Okumuş, Samet;Lewis, Lindsey;Wiebe, Eric;Hollebrands, Karen
通讯作者:
Hollebrands, Karen