本科数据分析课程的教学框架

David R. Firth, Jason H. Triche, David J. Lucus
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引用次数: 0

摘要

数据分析的爆炸式增长导致了对分析技能的巨大需求,而这一需求已经超过了这种技能的供应。为了应对这一挑战,世界各地的商学院都在提供数据分析的研究生和本科生课程。有越来越多的文献涉及研究生水平的课程,但很少有文献涉及本科课程。本文涵盖了本科数据分析课程导论教学中的基本主题、主题和普遍问题。我们提供了一个关于如何提供入门课程的总体框架。我们考察了三所AACSB认证学校的三个不同的入门课程。我们总结了常见问题、缓解计划和经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A framework for teaching an undergraduate data analytics class
The explosive growth of data analytics has led to a large demand for analytical skills which is outstripping the supply of this skillset. Business schools across the world are responding to this challenge by offering graduate and undergraduate programs in data analytics. There is a growing body of literature covering the graduate level programs, but very little literature covers the undergraduate courses. This article covers the basic topics, themes and universal issues in teaching the undergraduate introduction to the data analytics course. We provide an over-arching framework on how to deliver an introduction course. We examine three different introduction classes at three AACSB accredited schools. We conclude with common issues, mitigation plans, and lessons learned.
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