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

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...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 115; no. 50; pp. 12630 - 12637
Main Authors Börner, Katy, Scrivner, Olga, Gallant, Mike, Ma, Shutian, Liu, Xiaozhong, Chewning, Keith, Wu, Lingfei, Evans, James A.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 11.12.2018
Subjects
Online AccessGet full text
ISSN0027-8424
1091-6490
1091-6490
DOI10.1073/pnas.1804247115

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Abstract 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.
AbstractList 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.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.
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.
Author Ma, Shutian
Wu, Lingfei
Evans, James A.
Börner, Katy
Chewning, Keith
Gallant, Mike
Liu, Xiaozhong
Scrivner, Olga
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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.
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Snippet Rapid research progress in science and technology (S&T) and continuously shifting workforce needs exert pressure on each other and on the educational and...
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SubjectTerms COLLOQUIUM PAPER
Computer applications
Data mining
Data Science - education
Demand
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
Title Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy
URI https://www.jstor.org/stable/26580135
https://www.ncbi.nlm.nih.gov/pubmed/30530667
https://www.proquest.com/docview/2159933090
https://www.proquest.com/docview/2155150315
https://pubmed.ncbi.nlm.nih.gov/PMC6294902
Volume 115
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