THE ROLE OF CONTEXTS IN SUPPORTING EARLY STATISTICAL REASONING IN DATA MODELING

Q3 Social Sciences Statistics Education Research Journal Pub Date : 2023-07-31 DOI:10.52041/serj.v22i2.448
Lucía Zapata-Cardona
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Abstract

Data modeling is an essential activity in a data-driven society, but such a topic and how the context shapes it has received limited attention. This paper reports on research that investigated the role of context in supporting early statistical reasoning in the data modeling process. The data were collected throughout sessions in which young children (7 year-old) worked out problem activities designed to stimulate data modeling. The problem activities started by reading children’s story books purposefully created as a strategy to provide contexts of interest. The stories were inscribed within culturally relevant contexts in which the characters deal with data in different formats. The data modeling problem activities were closely related to the stories described within the books. Special attention was put into the actions of organizing, structuring, visualizing, and representing data and the role of the context in the data modeling process. The main results suggest that the context of the problem activities for the data modeling process seems to facilitate statistical reasoning in young children. Additionally, the context of the problem activities helped participants to develop strategies to identify attributes of data, assess the model created, make sense of the data, and make informal inferences.
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上下文在支持数据建模中早期统计推理中的作用
数据建模是数据驱动社会中的一项重要活动,但这样一个主题以及上下文如何塑造它却受到了有限的关注。本文报告了一项研究,该研究调查了上下文在数据建模过程中支持早期统计推理的作用。数据是在幼儿(7岁)进行问题活动以刺激数据建模的整个过程中收集的。问题活动始于阅读儿童故事书,目的是提供感兴趣的背景。这些故事是在与文化相关的背景下书写的,在这些背景下,人物以不同的格式处理数据。数据建模问题活动与书中描述的故事密切相关。特别关注组织、结构化、可视化和表示数据的行为,以及上下文在数据建模过程中的作用。主要结果表明,数据建模过程中问题活动的背景似乎有助于幼儿的统计推理。此外,问题活动的背景帮助参与者制定策略,以识别数据的属性,评估创建的模型,理解数据,并进行非正式推断。
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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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