利用网络可视化让小学生学习与本地相关的数据素养

IF 1.6 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Mengxi Zhou, Selena Steinberg, Christina Stiso, Joshua Danish, Kalani Craig
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引用次数: 0

摘要

本研究旨在探讨网络可视化如何为学习者提供利用本地和个人相关数据探索数据素养概念的机会。设计/方法/方法研究人员设计了六个与本地相关的网络可视化活动,以支持学生的数据推理实践,以理解数据中的聚合模式。文化历史活动理论(Engeström, 1999)指导了分析,以确定网络可视化活动如何介导学生对汇总数据集的新兴理解。研究结果表明,这种实施对学生对网络可视化概念的理解产生了积极的影响,因为他们能够识别和解释新网络中的关键关系。对视频数据的交互分析(Jordan and Henderson, 1995)揭示了活动如何促进学生解释网络数据能力提高的细微差别。在其他研究中指出的一些挑战,如学生倾向于关注熟悉的概念,也被指出为教师支持的对话,以帮助学生超越他们。原创性/价值据作者所知,这是作者所知的第一个支持小学生通过网络可视化探索数据素养的研究。作者讨论了网络可视化和本地/个人有意义的数据如何为跨课程学习数据素养概念提供机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using network visualizations to engage elementary students in locally relevant data literacy
Purpose This study aims to explore how network visualization provides opportunities for learners to explore data literacy concepts using locally and personally relevant data. Design/methodology/approach The researchers designed six locally relevant network visualization activities to support students’ data reasoning practices toward understanding aggregate patterns in data. Cultural historical activity theory (Engeström, 1999) guides the analysis to identify how network visualization activities mediate students’ emerging understanding of aggregate data sets. Findings Pre/posttest findings indicate that this implementation positively impacted students’ understanding of network visualization concepts, as they were able to identify and interpret key relationships from novel networks. Interaction analysis (Jordan and Henderson, 1995) of video data revealed nuances of how activities mediated students’ improved ability to interpret network data. Some challenges noted in other studies, such as students’ tendency to focus on familiar concepts, are also noted as teachers supported conversations to help students move beyond them. Originality/value To the best of the authors’ knowledge, this is the first study the authors are aware of that supported elementary students in exploring data literacy through network visualization. The authors discuss how network visualizations and locally/personally meaningful data provide opportunities for learning data literacy concepts across the curriculum.
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来源期刊
Information and Learning Sciences
Information and Learning Sciences INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
9.50
自引率
2.90%
发文量
30
期刊介绍: Information and Learning Sciences advances inter-disciplinary research that explores scholarly intersections shared within 2 key fields: information science and the learning sciences / education sciences. The journal provides a publication venue for work that strengthens our scholarly understanding of human inquiry and learning phenomena, especially as they relate to design and uses of information and e-learning systems innovations.
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