Jung, Yong JuDudek, JaclynYan, ShulongBorge, MarcelaKim, Soo HyeonLiao, JianShapiro, BenZimmerman, Heather Toomey2022-02-042022-02-042020-06Jung, 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. The Interdisciplinarity of the Learning Sciences, 1, 438–445. https://doi.org/10.22318/icls2020.438https://hdl.handle.net/1805/27704This 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.enPublisher PolicyDiverse Learning SettingsQualitative DataEducationConference proceedings