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Data Science for Undergraduates Opportunities and Options (2018) / Chapter Skim
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Summary
Pages 1-5

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 1...
... In future decades, all undergraduates will benefit from a fundamental awareness of and competence in data science. Recommendation 2.3: To prepare their graduates for this new data driven era, academic institutions should encourage the develop ment of a basic understanding of data science in all undergraduates.
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From page 2...
... A wide variety of instructional programs will be needed to prepare students for the data-enriched world of the coming years. Recommendation 2.2: Academic institutions should provide and evolve a range of educational pathways to prepare students for an array of data science roles in the workplace.
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From page 3...
... Academic institutions are stepping up to these educational challenges with a variety of programs and educational pathways. Several 4-year undergraduate institutions offer data science majors and/or minors -- serving not only those students pursuing data science as a career but also those students who want to acquire data skills while majoring in another field.
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From page 4...
... These challenges, among others, will need to be addressed to ensure the success of undergraduate data science students. Recommendation 5.1: Because these are early days for under­ graduate data science education, academic institutions should be prepared to evolve programs over time.
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From page 5...
... This should include developing and sharing measurement and evaluation frameworks, data sets, and a culture of evolution guided by high-quality evalu ation. Efforts should be made to establish relationships with sector specific professional societies to help align education evaluation with market impacts.
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Key Terms

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  • basic understanding
  • data skills
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  • offer data
  • growing data

  • data driven
  • developing data
  • science elements
  • science continues
  • science students

  • science majors
  • science courses
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  • science curriculum
  • science spans

  • science workforce
  • issues specific
  • entire academic
  • involve applying
  • core underlying


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