Data Literacies and Social Justice: Exploring Critical Data Literacies through Sociocultural Perspectives

Golnaz Arastoopour Irgens, Simon Knight, A. Wise, T. Philip, Maria C. Olivares, Sarah Van Wart, Sepehr Vakil, J. Marshall, Tapan S. Parikh, M. L. Lopez, Michelle Wilkerson, Kris D. Gutiérrez, Shiyan Jiang, J. Kahn
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引用次数: 10

Abstract

The ability to interpret, evaluate, and make data-based decisions is critical in the age of big data. Normative scripts around the use of data position them as a privileged epistemic form conferring authority through objectivity that can serve as a lever for effecting change. However, humans and materials shape how data are created and used which can reinscribe existing power relations in society at large (Van Wart, Lanouette & Parikh, 2020). Thus, research is needed on how learners can be supported to engage in critical data literacies through sociocultural perspectives. As a field intimately concerned with data-based reasoning, social justice, and design, the learning sciences is well-positioned to contribute to such an effort. This symposium brings together scholars to present theoretical frameworks and empirical studies on the design of learning spaces for critical data literacies. This collection supports a larger discussion around existing tensions, additional design considerations, and new methodologies.
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数据素养与社会正义:从社会文化角度探索关键数据素养
在大数据时代,解释、评估和做出基于数据的决策的能力至关重要。围绕数据使用的规范脚本将它们定位为一种特权的认知形式,通过客观性授予权威,可以作为影响变革的杠杆。然而,人类和材料塑造了数据的创造和使用方式,这可以在整个社会中重新定义现有的权力关系(Van Wart, Lanouette & Parikh, 2020)。因此,需要研究如何通过社会文化视角支持学习者参与关键数据素养。作为一个与基于数据的推理、社会正义和设计密切相关的领域,学习科学很好地定位于为这样的努力做出贡献。本次研讨会汇集了学者提出的理论框架和实证研究的学习空间设计的关键数据素养。这个集合支持围绕现有的紧张关系、额外的设计考虑和新的方法进行更大的讨论。
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