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ERIC Number: EJ1298243
Record Type: Journal
Publication Date: 2021
Pages: 16
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1743-9884
EISSN: N/A
Learning with Large, Complex Data and Visualizations: Youth Data Wrangling in Modeling Family Migration
Kahn, Jennifer; Jiang, Shiyan
Learning, Media and Technology, v46 n2 p128-143 2021
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.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: Junior High Schools; Middle Schools; Secondary Education; High Schools
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 1341882