主动为随机测试建立模型的过程-基于案例研究洞察学习者的建模活动

IF 2 4区 教育学 Q2 EDUCATION & EDUCATIONAL RESEARCH
Susanne Podworny, Rolf Biehler
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引用次数: 2

摘要

摘要推理是科学和公民社会不可或缺的一部分,但研究表明,对许多人来说,推理是一个有问题的领域。一种更容易获得的推理方法是通过计算机模拟使用随机化测试。在小学职前教师通过了一个课程模块后,对他们进行了一项案例研究,该模块通过随机测试引入了推理推理。这项研究考察了三对小学职前教师如何在随机测试任务中使用动手和计算机支持的组件构建模型。我们的研究结果表明,在模型构建过程中有一个常见的顺序:规划、随机分配建模、设置样本量和替换以及运行模拟。我们的研究结果深入展示了TinkerPlots如何在建模过程中成为一种支持和约束媒介,建立在随机测试物理模拟的经验基础上。这些见解可用于重新设计随机测试的技术支持的学习轨迹。与其他案例研究一起,我们的发现为大学生的建模过程提供了很好的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The process of actively building a model for a randomization test – insights into learners’ modeling activities based on a case study
ABSTRACT Inferential reasoning is an integral part of science and civic society, but research shows that it is a problematic domain for many people. One possibility for a more accessible approach to inferential reasoning is to use randomization tests via computer simulations. A case study was conducted with primary preservice teachers after they had passed a course module that introduced inferential reasoning with randomization tests. The study examines how three pairs of primary preservice teachers construct models in a randomization test task with both hands-on and computer-supported components. Our findings suggest that there is a common sequence in the model building process: planning, modeling the random assignment, setting sample size and replacement, and running the simulation. Our findings show in depth how TinkerPlots can be a supportive and constraining medium in the modeling process, building on experiences with physical simulations of a randomization test. These insights can be used for redesigning technology-supported learning trajectories for randomization tests. Together with other case studies our findings provide a good sense of university students’ modeling processes.
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来源期刊
Mathematical Thinking and Learning
Mathematical Thinking and Learning EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
4.40
自引率
6.20%
发文量
18
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