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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.
Katharina Schüller (2022) studied this question.