Data wrangling practices and process in modeling family migration narratives with big data visualization technologies

Shiyan Jiang, Jennifer B. Kahn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Big data technologies are powerful tools for telling evidence-based narratives about oneself and the world. In this paper, we examine the sociotechnical practices of data wrangling—strategies for selecting and managing datasets to produce a model and story in a big data interface—for youth assembling models and stories about family migration using interactive data visualization tools. Through interaction analysis of video data, we identified ten data wrangling practices and developed a conceptual model of the data wrangling process that contains four interrelated recursive stages. These data wrangling practices and the process of data wrangling are important to understand for supporting future data science education opportunities that facilitate learning and discussion about scientific and socioeconomic issues. This study also sheds light on how the family migration modeling context positioned the youth as having agency and authority over big data.

Original languageEnglish (US)
Title of host publicationA Wide Lens
Subtitle of host publicationCombining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings - 13th International Conference on Computer Supported Collaborative Learning, CSCL 2019 - Conference Proceedings
EditorsKristine Lund, Gerald P. Niccolai, Elise Lavoue, Cindy Hmelo-Silver, Gahgene Gweon, Michael Baker
PublisherInternational Society of the Learning Sciences (ISLS)
Pages208-215
Number of pages8
ISBN (Electronic)9781732467231
StatePublished - Jan 1 2019
Event13th International Conference on Computer Supported Collaborative Learning - A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, CSCL 2019 - Lyon, France
Duration: Jun 17 2019Jun 21 2019

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume1
ISSN (Print)1573-4552

Conference

Conference13th International Conference on Computer Supported Collaborative Learning - A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, CSCL 2019
CountryFrance
CityLyon
Period6/17/196/21/19

Keywords

  • Data science education
  • Data wrangling
  • Family migration
  • Modeling
  • Storytelling

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Education

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  • Cite this

    Jiang, S., & Kahn, J. B. (2019). Data wrangling practices and process in modeling family migration narratives with big data visualization technologies. In K. Lund, G. P. Niccolai, E. Lavoue, C. Hmelo-Silver, G. Gweon, & M. Baker (Eds.), A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings - 13th International Conference on Computer Supported Collaborative Learning, CSCL 2019 - Conference Proceedings (pp. 208-215). (Computer-Supported Collaborative Learning Conference, CSCL; Vol. 1). International Society of the Learning Sciences (ISLS).