Scripts and Counterscripts in Community-Based Data Science: Participatory Digital Mapping and the Pursuit of a Third Space

Autor/inn/en	Van Wart, Sarah; Lanouette, Kathryn; Parikh, Tapan S.
Titel	Scripts and Counterscripts in Community-Based Data Science: Participatory Digital Mapping and the Pursuit of a Third Space
Quelle	In: Journal of the Learning Sciences, 29 (2020) 1, S.127-153 (27 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1050-8406
DOI	10.1080/10508406.2019.1693378
Schlagwörter	Data; Social Problems; Data Collection; Data Use; High School Students; Student Projects; Sciences; Pollution; Urban Planning; College Students; Urban Renewal; Data Analysis; Values; Expectation; Educational Technology; Geographic Information Systems; Maps + Suchen Sie Ihr Suchwort? Daten; Social problem; Soziales Problem; Data capture; Datensammlung; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Schulprojekt; Science; Wissenschaft; Schadstoffbelastung; Stadtplanung; Collegestudent; Stadtsanierung; Auswertung; Wertbegriff; Expectancy; Erwartung; Unterrichtsmedien; Map; Karte
Abstract	Data increasingly mediates how we understand the world. As such, there is growing interest in designing initiatives to help young people learn about data--not only the techno-mathematical skills necessary to work with data, but also the dispositions needed to participate in data-centric ways of knowing and doing. In this article, we argue that as this educational goal is pursued, it is important to attend to the normative scripts that are often associated with data, and how they relate to learners' perspectives and prior experiences. We do this by examining two initiatives that aimed to help young people learn about data and its "real-world" applications by engaging them in participatory mapping activities, directed toward the study of local community challenges. We argue that when there are mismatches between students' realities and how reality is described to work in data science, making the time and space to examine these contradictions can lead to a robust engagement with data science and its applications. These findings have implications for how we might better design tools and learning activities that connect data science with the broader contexts that frame young people's lives. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01