Data science literacy: Toward a philosophy of accessible and adaptable data science skill development in public administration programs
| Author | Michael Overton,Stephen Kleinschmit |
| DOI | http://doi.org/10.1177/01447394211004990 |
| Published date | 01 October 2022 |
| Date | 01 October 2022 |
| Subject Matter | Curriculum Design in Public Administration Education: Challenges and Perspectives |
Curriculum Design in Public Administration Education: Challenges and Perspectives
Data science literacy:
Toward a philosophy of
accessible and adaptable
data science skill
development in public
administration programs
Michael Overton
University of Idaho, USA
Stephen Kleinschmit
University of Illinois at Chicago, USA
Abstract
Public administration is struggling to contend with a substantial shift in practice fueled by
the accelerating adoption of information technology. New skills, competencies and
pedagogies are required by the field to help overcome the data-skills gap. As a means to
address these deficiencies, we introduce the Data Science Literacy Framework, a
heuristic for incorporating data science principles into public administration programs.
The framework suggests that data literacy is the dominant principle underlying a shift in
professional practice, accentuated by an understanding of computational science, sta-
tistical methodology, and data-adjacent domain knowledge. A combination of new and
existing skills meshed into public administration curriculums help implement these
principles and advance public administration education.
Keywords
data science, data literacy, data-skills gap, research methods, statistics
Introduction
The principlesof data science touch every public sector institution that uses data to inform
decision-making(Secundo et al., 2017). As the scale and velocity of data increase, its use
Corresponding author:
Michael Overton, Department of Politics and Philosophy, University of Idaho, 875 Perimeter Drive, Moscow,
ID 83844, USA
Email: Moverton@uidaho.edu
Teaching Public Administration
ªThe Author(s) 2021
Article reuse guidelines:
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DOI: 10.1177/01447394211004990
journals.sagepub.com/home/tpa
2022, Vol. 40(3) 354–365
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