Visualizing qualitative data: Creative approaches for analyzing and demonstrating lively data from diverse learning settings

Yong Ju Jung, Jaclyn Dudek, Shulong Yan, Marcela Borge, Soo Hyeon Kim, Jian Liao, Benjamin Rydal Shapiro, Heather Toomey Zimmerman

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

1 Scopus citations

Abstract

This structured poster session aims to showcase novel approaches of qualitatively analyzing and communicating lively data—data that is complex, nuanced, multimodal, and multi-voiced. Such data is rich but also messy, often defying the traditional text-based forms of description and presentation. Therefore, the session pairs creative techniques and methods to analyze, triangulate, and/or visualize qualitative findings across multiple data sources (e.g., video, digital and physical spaces, participant artifacts, and patterns of movement) from diverse learning contexts (e.g., museums, libraries, outdoor spaces, and classrooms)—beyond showing transcriptions. The visual format of the session supports our goal of sharing and communicating rich data stories for further discussion with diverse audiences.

Original languageEnglish (US)
Title of host publication14th International Conference of the Learning Sciences
Subtitle of host publicationThe Interdisciplinarity of the Learning Sciences, ICLS 2020 - Conference Proceedings
EditorsMelissa Gresalfi, Ilana Seidel Horn
PublisherInternational Society of the Learning Sciences (ISLS)
Pages438-445
Number of pages8
ISBN (Electronic)9781732467255
StatePublished - 2020
Event14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 - Nashville, United States
Duration: Jun 19 2020Jun 23 2020

Publication series

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

Conference

Conference14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020
Country/TerritoryUnited States
CityNashville
Period6/19/206/23/20

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Education

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