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Learning with large, complex data and visualizations: youth data wrangling in modeling family migration
Journal article   Peer reviewed

Learning with large, complex data and visualizations: youth data wrangling in modeling family migration

Jennifer Kahn and Shiyan Jiang
Learning, media and technology, Vol.46(2), pp.128-143
2021-04-03

Abstract

critical data literacy data modeling data visualization Data wrangling family migration
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.

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Collaboration types
Domestic collaboration
Citation topics
6 Social Sciences
6.11 Education & Educational Research
6.11.295 Science Education
Web Of Science research areas
Education & Educational Research
ESI research areas
Social Sciences, general

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