INVESTIGATING DATA LIKE A DATA SCIENTIST: KEY PRACTICES AND PROCESSES

Q3 Social Sciences

Statistics Education Research Journal Pub Date : 2022-07-04 DOI:10.52041/serj.v21i2.41

Hollylynne S. Lee, G. Mojica, Emily P. Thrasher, Peter Baumgartner

引用次数: 9

Abstract

With a call for schools to infuse data across the curriculum, many are creating curricula and examining students’ thinking in data-intensive problems. As the discipline of statistics education broadens to data science education, there is a need to examine how practices in data science can inform work in K-12. We synthesize literature about statistics investigation processes, data science as a field and practices of data scientists. Further, we provide results from an ethnographic and interview study of the work of data scientists. Together, these inform a new framework to support data investigation processes. We explicate the practices and dispositions needed and offer a glimpse of how the framework can be used to move the discipline of data science education forward.

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像数据科学家一样调查数据：关键实践和过程

随着呼吁学校在课程中融入数据，许多学校正在创建课程，并在数据密集型问题上考察学生的思维。随着统计教育学科扩展到数据科学教育，有必要研究数据科学的实践如何为K-12的工作提供信息。我们综合了有关统计调查过程，数据科学作为一个领域和数据科学家的实践的文献。此外，我们提供了数据科学家工作的民族志和访谈研究的结果。这些共同构成了支持数据调查过程的新框架。我们解释了所需的实践和倾向，并提供了如何使用该框架来推动数据科学教育学科向前发展的一瞥。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics Education Research Journal Social Sciences-Education

CiteScore

1.30

自引率

0.00%

发文量

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.