{"title":"Data science literacy: Toward a philosophy of accessible and adaptable data science skill development in public administration programs","authors":"Michael Overton, Stephen W. Kleinschmit","doi":"10.1177/01447394211004990","DOIUrl":null,"url":null,"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, statistical 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.","PeriodicalId":44241,"journal":{"name":"Teaching Public Administration","volume":"40 1","pages":"354 - 365"},"PeriodicalIF":1.1000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/01447394211004990","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teaching Public Administration","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/01447394211004990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 7
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, statistical 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.
期刊介绍:
Teaching Public Administration (TPA) is a peer-reviewed journal, published three times a year, which focuses on teaching and learning in public sector management and organisations. TPA is committed to publishing papers which promote critical thinking about the practice and process of teaching and learning as well as those which examine more theoretical and conceptual models of teaching and learning. It offers an international forum for the debate of a wide range of issues relating to how skills and knowledge are transmitted and acquired within public sector/not for profit organisations. The Editors welcome papers which draw upon multi-disciplinary ways of thinking and working and, in particular, we are interested in the following themes/issues: Learning from international practice and experience; Curriculum design and development across all levels from pre-degree to post graduate including professional development; Professional and Taught Doctoral Programmes; Reflective Practice and the role of the Reflective Practitioner; Co-production and co-construction of the curriculum; Developments within the ‘Public Administration’ discipline; Reviews of literature and policy statements.