Situating Data Science: Exploring How Relationships to Data Shape Learning
Situating Data Science: Exploring How Relationships to Data Shape Learning
复制标题
数据科学定位：探索与数据的关系如何塑造学习
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
J. Polman
中科院分区：
文献类型：
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作者：
Michelle Wilkerson;J. Polman
新兴的数据科学领域对科学和社会产生了巨大的影响。这导致了十多年来呼吁建立一个相应的数据科学教育领域。然而，仍然需要更深入地概念化数据科学教育领域在范围、责任和执行方面可能涉及的内容。本期特刊探讨了数据科学的一个显著特征--它关注的是从社会和环境背景中收集的数据，而学习者往往会发现自己深深地融入其中--这是如何对学习和教育产生严重影响的。学习科学在研究这种背景嵌入如何影响学习者对数据的参与方面具有独特的地位，这些数据包括概念、经验、社区、种族主义、空间和政治维度。这期特刊展示了学习者与数据建立的丰富层次的关系，并揭示了它们不仅是学习数据的实用机制，而且是将数据作为社会文本导航和将数据科学理解为一门学科的关键部分。总而言之，这些贡献提供了一个愿景，即学习科学如何为更具扩展性、更具代理能力和更具社会意识的数据科学教育做出贡献。
The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution. This special issue explores how one distinguishing feature of Data Science—its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded—suggests serious implications for learning and education. The learning sciences is uniquely positioned to investigate how such contextual embeddings impact learners’ engagement with data including conceptual, experiential, communal, racialized, spatial, and political dimensions. This special issue demonstrates the richly layered relationships learners build with data and reveals them to be not merely utilitarian mechanisms for learning about data, but a critical part of navigating data as social text and understanding Data Science as a discipline. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, agentive and socially aware Data Science Education.
影响因子：
3.8
作者：
Hardy, Lisa;Dixon, Colin;Hsi, Sherry
通讯作者：
Hsi, Sherry
学习用数据推理：我们是如何到达这里的以及我们知道什么？
影响因子：
3.8
作者：
Rubin, Andee
通讯作者：
Rubin, Andee