Cited by 65Digital literacy in educationStatistics Education and MethodologiesLiteracy, Media, and Education

Data and AI literacy for everyone

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Schüller, Katharina·2022·Statistical Journal of the IAOS

Abstract

The framework for data and AI literacy proposed in this contribution aims to create a common understanding of data and AI literacy so that it can be systematically included into curricula and educational standards of schools, teacher training, higher education, and further education. The purpose of the framework is to facilitate the respective set of skills and competencies to be taught as a transdisciplinary competence across all subjects from three perspectives: the application-oriented, the technical-methodological, and the socio-cultural perspective. The framework provides a pathway to establishing basic data literacy for everyone, to enable 21st Century citizens to deal with data and AI in a conscious and ethically sound manner. The framework can also serve as a reference for data and AI literacy programs for extracurricular and vocational training, to enable lifelong learning of data and AI literacy. Therefore, it can be a useful template for public statistical institutions planning to offer data literacy trainings for the public, responding to the challenges resulting from the changing roles and expectations of actors in a data-driven society. A detailed example for such an application, the app “Stadt | Land | Datenfluss”, demonstrates the benefit of the framework for the purpose of adult education.

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Crossref · 10.3233/sji-220941

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  • Data Literacy forms a foundation on which AI literacy can develop.

    “As Schüller (2022) argues in their conceptualization of Data Literacy, the ability to understand, interpret, and work with data forms a foundation on which AIL can develop.”

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Authors
Schüller, K.
Affiliations
STAT-UP Statistical Consulting & Data Science GmbH, Augustenstr. 5, 80333 Munich, Germany
Corresponding author
Schüller, Katharina
Venue
Statistical Journal of the IAOS
Published
2022-06-07
Volume
38
Issue
2
Pages
477-490
ISSN
  • 1874-7655 (ISSN-L)
  • 1875-9254
OpenAlex
W4224569182
Cited by
65
References
0
Citations by year
2026: 26 · 2025: 27 · 2024: 10 · 2023: 1 · 2022: 1
FWCI
8.32
Type
journal article
Language
en
Open access
Locations
Statistical Journal of the IAOS (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Digital literacy in education
  • Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
Keywords
data literacy, AI literacy, literacy framework, transdisciplinary competence, curriculum development, teacher professional development, lifelong learning, adult education, data ethics, data-driven society, extracurricular training, vocational education, 21st century skills

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