Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/6670
Title: Visualizing Qualitative Data: Creative Approaches for Analyzing and Demonstrating Lively Data from Diverse Learning Settings
Authors: Jung, Yong Ju
Dudek, Jaclyn
Yan, Shulong
Borge, Marcela
Kim, Soo Hyeon
Liao, Jian
Shapiro, Ben
Zimmerman, Heather Toomey
Keywords: Learning and Identity
Issue Date: Jun-2020
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Jung, Y. J., Dudek, J., Yan, S., Borge, M., Kim, S. H., Liao, J., Shapiro, B., & Zimmerman, H. T. (2020). Visualizing Qualitative Data: Creative Approaches for Analyzing and Demonstrating Lively Data from Diverse Learning Settings. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 1 (pp. 438-445). Nashville, Tennessee: International Society of the Learning Sciences.
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.
URI: https://doi.dx.org/10.22318/icls2020.438
https://repository.isls.org//handle/1/6670
Appears in Collections:ICLS 2020

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