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Examining instructional change at scale using data from diagnostic assessments built on learning trajectories
ZDM ( IF 2.0 ) Pub Date : 2021-04-16 , DOI: 10.1007/s11858-021-01259-w
Jere Confrey , Meetal Shah

This study investigated the process of instructional change required to translate data on student progress along learning trajectories (LTs) into relevant instructional modifications. Researchers conducted a professional development session on ratio LTs, which included analyzing 3 years of district-level data from Math-Mapper 6–8, a digital LT-based diagnostic assessment application, with fifteen 6th and 7th grade teachers. Teachers subsequently conducted a lesson study to enact what they had learned, allowing researchers to study how teachers used data on student progress along ratio equivalence LTs to design, implement, and evaluate the lesson study. Researchers applied a framework for LT-based data-driven decision making to analyze video data of the lesson study activities. Teachers successfully scanned data reports to pinpoint the LT levels at which to target modified instruction. In one instance, they focused too narrowly on a single item resulting in excessive lesson time on tasks on graph literacy external to the LT. In the other, their data interpretation was overly general and resulted in the design and implementation of a sequence of tasks that reversed the order implied in the LT and relied on the use of more sophisticated strategies from subsequent LTs. Results suggest a need for more data interpretation skills, a deep understanding of the learning theory underpinning LTs, and more precision in teacher discourse around LTs.



中文翻译:

使用基于学习轨迹的诊断评估中的数据大规模检查教学变化

这项研究调查了将学生沿着学习轨迹(LTs)的进度数据转换为相关教学修改所需的教学变更过程。研究人员针对比率LT进行了一次专业开发会议,其中包括分析了Math-Mapper 6-8(基于数字LT的诊断评估应用程序)中3年的区级数据,并与15名6、7年级的老师进行了比较。随后,教师进行了课程研究,以阐明所学内容,从而使研究人员可以研究教师如何沿比率等效LTs使用有关学生进度的数据来设计,实施和评估课程研究。研究人员为基于LT的数据驱动型决策应用了框架,以分析课程学习活动的视频数据。教师成功扫描了数据报告,以查明针对修改后的教学的LT级别。在一个实例中,他们过于狭focused地专注于单个项目,从而导致过多的课程时间集中在LT外部的图形素养任务上。另一方面,他们的数据解释过于笼统,导致设计和实施一系列任务,这些任务颠倒了LT中隐含的顺序,并依赖于后续LT中使用的更复杂策略的使用。结果表明,需要更多的数据解释技能,对基础知识支持的学习理论的深刻理解,以及围绕基础知识的教师话语的更加精确。另一方面,他们的数据解释过于笼统,导致设计和实施一系列任务,这些任务颠倒了LT中隐含的顺序,并依赖于后续LT中使用的更复杂策略的使用。结果表明,需要更多的数据解释技能,对基础知识支持的学习理论的深刻理解,以及围绕基础知识的教师话语的更加精确。另一方面,他们的数据解释过于笼统,导致设计和实施一系列任务,这些任务颠倒了LT中隐含的顺序,并依赖于后续LT中使用的更复杂策略的使用。结果表明,需要更多的数据解释技能,对基础知识支持的学习理论的深刻理解,以及围绕基础知识的教师话语的更加精确。

更新日期:2021-04-16
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