Data science for informed citizen: Learning at the intersection of data literacy, statistics and social justice

Data science as a practical science has been conceived to address tangible problems in science, technology and society. Educating students in data science goes beyond teaching about algorithms, skills of manipulating data sets, selecting and applying appropriate analyses, and creating and interpreting visual representations of data. It also involves raising a critical understanding of how data are produced and how they can be used for particular purposes, including the role of context in interpreting data. It emphasizes developing an awareness for data ethics, and considering the implications for policy and society when powerful algorithms are used. Participation in democracy, in today’s digital and datafied society requires the development of a series of transversal skills which need to be fostered in educational institutions through critically oriented pedagogies that interweave technical data skills and practices together with statistical and media literacies. Based on an analysis of trends and needs to protect democratic values in a datafied society and on own reflections of teaching practices this paper gives recommendations on designing data science courses to develop informed citizen.

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Publication Details

Journal
Revista Internacional de Pesquisa em Educação Matemática
Published
2024-08-20
DOI
https://doi.org/10.37001/ripem.v14i3.3816
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Data science for informed citizen: Learning at the intersection of data literacy, statistics and social justice

Joachim Engel, Laura Martignon
Revista Internacional de Pesquisa em Educação Matemática
Statistics Education and Methodologies
article

Data science for informed citizen: Learning at the intersection of data literacy, statistics and social justice

Joachim Engel, Laura Martignon
article en

Abstract

Data science as a practical science has been conceived to address tangible problems in science, technology and society. Educating students in data science goes beyond teaching about algorithms, skills of manipulating data sets, selecting and applying appropriate analyses, and creating and interpreting visual representations of data. It also involves raising a critical understanding of how data are produced and how they can be used for particular purposes, including the role of context in interpreting data. It emphasizes developing an awareness for data ethics, and considering the implications for policy and society when powerful algorithms are used. Participation in democracy, in today’s digital and datafied society requires the development of a series of transversal skills which need to be fostered in educational institutions through critically oriented pedagogies that interweave technical data skills and practices together with statistical and media literacies. Based on an analysis of trends and needs to protect democratic values in a datafied society and on own reflections of teaching practices this paper gives recommendations on designing data science courses to develop informed citizen.

Revista Internacional de Pesquisa em Educação MatemáticaVol. 14(3)
Ludwigsburg University of Education (DE)
Openalex Percentile: Top 73%
Statistics Education and Methodologies
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