分析流行的本科IT项目

Jai W. Kang, Qi Yu, Edward P. Holden, E. Golen, Michael J. McQuaid
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引用次数: 0

摘要

随着我们进入信息时代,计算资源变得相对便宜,其能力似乎是无限的。因此,数据科学领域已经成为工程师、科学家和IT专业人员的关键领域之一。在本文中,我们从现有的数据科学书籍(DS-BoK)中导出了数据分析知识体系(DA-BoK),作为在机构本科IT学位课程的整个课程中提供数据分析内容的一种手段。一系列的四个知识领域被细分为知识单元,这些知识单元可以通过四种嵌入类型(包括示例讲座、实验室、案例研究和项目)引入到现有的IT课程中。本文以我们的三个IT项目为例,介绍了如何通过每种嵌入类型在布鲁姆分类法的三个层次(即词汇、理解、应用)引入这些内容。最后,就如何改进拟议的数据分析嵌入式IT课程提供了见解和指导,以满足工业中现代数据分析管道的需求。
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Analytics Prevalent Undergraduate IT Program
As we enter age of information, computational resources have become relatively inexpensive and seemingly limitless in their capabilities. Consequently, the field of data science has emerged as one of the key areas in industry among engineers, scientists, and IT professionals alike. In this paper, we derive a Data Analytics Body of Knowledge (DA-BoK) from the existing Data Science BoK (DS-BoK) as a means to provide data analytics content throughout the curriculum of an institution's undergraduate IT degree programs. A series of four Knowledge Areas are subdivided into Knowledge Units that can be introduced into existing IT courses through four embedding types, including lectures by example, labs, case studies, and projects. A case study is presented using our three IT programs as examples of how this content can be introduced at three levels of Bloom's Taxonomy (i.e. vocabulary, comprehension, application) through each of the embedding types. Finally, insights and guidance are provided on how to improve the proposed data analytics embedded IT curriculum in order to meet the demands of the modern data analytics pipeline in industry.
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