Please use this identifier to cite or link to this item:
Title: Exploring Network Visualization of Data in Elementary Classrooms
Authors: Zhou, Mengxi
Steinberg, Selena
Stiso, Christina
Danish, Joshua
Craig, Kalani
Keywords: Learning Sciences
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Zhou, M., Steinberg, S., Stiso, C., Danish, J., & Craig, K. (2023). Exploring network visualization of data in elementary classrooms. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 465-472). International Society of the Learning Sciences.
Abstract: This study aims to understand how elementary students can reason about data and data visualization through participation in thematic network visualization activities that integrate locally relevant, personally meaningful data. Young students constantly struggle to focus beyond individual data points to comprehend the overall trend for a complete dataset (Rubin, 2020). This study describes the design of a curriculum unit that incorporates a series of network visualization activities as building blocks to develop students’ reasoning skills on aggregate patterns of the entire dataset. Our analysis draws on Cultural Historical Activity Theory (Engeström, 1999) to identify mediators within four network visualization activities and explicate how they transformed students' progressive understanding of the aggregate dataset they were exploring to make inferences.
Description: Long Paper
Appears in Collections:ISLS Annual Meeting 2023

Files in This Item:
File SizeFormat 
ICLS2023_465-472.pdf702.94 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.