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Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy

Börner, Katy ; Scrivner, Olga ; Gallant, Mike ; Ma, Shutian ; Liu, Xiaozhong ; Chewning, Keith ; Wu, Lingfei ; Evans, James A.

Proceedings of the National Academy of Sciences - PNAS, 2018-12, Vol.115 (50), p.12630-12637 [Periódico revisado por pares]

United States: National Academy of Sciences

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  • Título:
    Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy
  • Autor: Börner, Katy ; Scrivner, Olga ; Gallant, Mike ; Ma, Shutian ; Liu, Xiaozhong ; Chewning, Keith ; Wu, Lingfei ; Evans, James A.
  • Assuntos: COLLOQUIUM PAPER ; Computer applications ; Data mining ; Data Science - education ; Demand (economics) ; Education ; Employment ; Expert Testimony ; Higher education institutions ; Humans ; Job analysis ; Job Description ; Mathematical models ; Sackler on Modeling and Visualizing Science and Technology Developments ; Science ; Skills ; Social Sciences ; Social Skills ; Surveys and Questionnaires ; Technology ; Workforce
  • É parte de: Proceedings of the National Academy of Sciences - PNAS, 2018-12, Vol.115 (50), p.12630-12637
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Edited by William B. Rouse, Stevens Institute of Technology, Hoboken, NJ, and accepted by Editorial Board Member Pablo G. Debenedetti September 12, 2018 (received for review March 14, 2018)
    Author contributions: K.B., X.L., and J.A.E. designed research; K.B., O.S., S.M., L.W., and J.A.E. performed data analysis and visualization; O.S. and M.G. performed job and publication data modeling; S.M. and X.L. performed job and publication data entity extraction; K.C. performed job data modeling; L.W. and J.A.E. performed course data entity extraction; and K.B., O.S., M.G., S.M., X.L., K.C., L.W., and J.A.E. wrote the paper.
  • Descrição: Rapid research progress in science and technology (S&T) and continuously shifting workforce needs exert pressure on each other and on the educational and training systems that link them. Higher education institutions aim to equip new generations of students with skills and expertise relevant to workforce participation for decades to come, but their offerings sometimes misalign with commercial needs and new techniques forged at the frontiers of research. Here, we analyze and visualize the dynamic skill (mis-) alignment between academic push, industry pull, and educational offerings, paying special attention to the rapidly emerging areas of data science and data engineering (DS/DE). The visualizations and computational models presented here can help key decision makers understand the evolving structure of skills so that they can craft educational programs that serve workforce needs. Our study uses millions of publications, course syllabi, and job advertisements published between 2010 and 2016. We show how courses mediate between research and jobs. We also discover responsiveness in the academic, educational, and industrial system in how skill demands from industry are as likely to drive skill attention in research as the converse. Finally, we reveal the increasing importance of uniquely human skills, such as communication, negotiation, and persuasion. These skills are currently underexamined in research and undersupplied through education for the labor market. In an increasingly data-driven economy, the demand for “soft” social skills, like teamwork and communication, increase with greater demand for “hard” technical skills and tools.
  • Editor: United States: National Academy of Sciences
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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