中学生统计建模过程中关于分布的统计推理

Q3 Social Sciences
TUĞÇE BALKAYA, GAMZE KURT
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引用次数: 0

摘要

通过样本对总体进行统计推理可以通过对总体和样本之间的关系进行建模来实现。一种方法是在技术集成的环境中对真实数据情况进行建模。基于此,本研究旨在通过非正式统计模型与建模推理(RISM)框架下的非正式推理过程来研究中学生如何形成分布,并考察他们的统计建模过程。本文报告的案例研究侧重于学生在三个活动中设计的猜想和数据模型是如何演变的,以及它们如何包含一个基本的概率机制。结果表明,在建模过程中,学生通过推理更接近概率分布,掌握了更高层次的统计概念。因此,我们认为学生从理解经验分布转向了理解理论分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MIDDLE SCHOOL STUDENTS’ STATISTICAL REASONING ABOUT DISTRIBUTION IN THEIR STATISTICAL MODELING PROCESSES
Statistical reasoning about a population through samples can be achieved by modeling the relationship between population and sample. One way to do this is to model real data situations in a technology-integrated environment. With this view, we aimed to investigate how middle school students formed distributions and examined their statistical modeling processes through the informal reasoning process within the Reasoning with Informal Statistical Models and Modeling (RISM) framework. The case study reported in this paper focuses on how the conjecture and data models students designed throughout three activities evolved and how their inclusion of a fundamentally probabilistic mechanism matured. Findings show the students approached the distribution probabilistically with their inferences during the modeling process and grasped the statistical concepts they would encounter at a more advanced level. Therefore, we claim that students shifted from understanding empirical distributions to understanding theoretical distributions.
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来源期刊
Statistics Education Research Journal
Statistics Education Research Journal Social Sciences-Education
CiteScore
1.30
自引率
0.00%
发文量
46
期刊介绍: SERJ is a peer-reviewed electronic journal of the International Association for Statistical Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free. SERJ aims to advance research-based knowledge that can help to improve the teaching, learning, and understanding of statistics or probability at all educational levels and in both formal (classroom-based) and informal (out-of-classroom) contexts. Such research may examine, for example, cognitive, motivational, attitudinal, curricular, teaching-related, technology-related, organizational, or societal factors and processes that are related to the development and understanding of stochastic knowledge. In addition, research may focus on how people use or apply statistical and probabilistic information and ideas, broadly viewed. The Journal encourages the submission of quality papers related to the above goals, such as reports of original research (both quantitative and qualitative), integrative and critical reviews of research literature, analyses of research-based theoretical and methodological models, and other types of papers described in full in the Guidelines for Authors. All papers are reviewed internally by an Associate Editor or Editor, and are blind-reviewed by at least two external referees. Contributions in English are recommended. Contributions in French and Spanish will also be considered. A submitted paper must not have been published before or be under consideration for publication elsewhere.
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