Learning with Large, Complex Data and Visualizations: Youth Data Wrangling in Modeling Family Migration

Autor/inn/en	Kahn, Jennifer; Jiang, Shiyan
Titel	Learning with Large, Complex Data and Visualizations: Youth Data Wrangling in Modeling Family Migration
Quelle	In: Learning, Media and Technology, 46 (2021) 2, S.128-143 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kahn, Jennifer)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1743-9884
DOI	10.1080/17439884.2020.1826962
Schlagwörter	Visualization; Data Use; Data Interpretation; Decision Making; Demography; Migration; Genealogy; Socioeconomic Influences; Visual Aids; Information Literacy; Critical Theory; Summer Programs; Public Libraries; Middle School Students; High School Students; Adolescents; Human Geography; Story Telling + Suchen Sie Ihr Suchwort? Visualisation; Visualisierung; Data evaluation; Datenauswertung; Decision-making; Entscheidungsfindung; Demografie; Ahnenforschung; Genealogie; Sozioökonomischer Faktor; Anschauungsmaterial; Informationskompetenz; Kritische Theorie; Sommerkurs; Public library; Stadtbücherei; Öffentliche Bibliothek; Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; High school; High schools; Oberschule; Studentin; Adolescent; Adolescence; Adoleszenz; Jugend; Jugendalter; Jugendlicher; Humangeografie
Abstract	We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using screen-capture and video recordings, field notes, and artifacts, we analyzed youth's step-by-step decision-making and interaction with data interfaces in "data wrangling," which we define as the practices for selecting, interpreting, and integrating datasets in order to build meaningful data displays and tell a story with the data. We identify patterns in youth's "data wrangling trajectories" and propose a conceptual model for describing the stages (Find, Relate, Challenge, Build) of youth learning to construct models and tell stories about family migration. In addition, we highlight student struggles and opportunities for learning to be explored in future learning environment designs with large, complex datasets and data interfaces. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01