Ein Framework für Data Literacy

Schüller, Katharina

doi:10.1007/s11943-019-00261-9

Cited by 19 publications

(39 citation statements)

References 5 publications

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“…Since its first release in German [22], the HFD Data Literacy Framework has been implemented in over two dozen curricula of data literacy programmes at German universities. Furthermore, it has been adapted to derive the curriculum for an app for adult education in Germany: "Stadt | Land | DatenFluss" SLDF.…”

Section: Discussionmentioning

confidence: 99%

Data and AI literacy for everyone

Schüller

2022

SJI

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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.

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Section: Discussionmentioning

confidence: 99%

Data and AI literacy for everyone

Schüller

2022

SJI

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“…In the first section, the video lecture embeds the geoaspect into the process model of added value from data (referring to Schüller et al 2019). It forms the basis of the whole series of teaching units and provides a perfect frame to show the benefits of geospatial over non-geospatial data in a methodological context (Fig.…”

Section: The Video Lecturementioning

confidence: 99%

Grundlegende Geodatenkenntnisse für wirtschaftliche Anwendungen

Jürgens

Redecker

2023

KN J. Cartogr. Geogr. Inf.

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Geospatial data literacy is of paramount importance in an increasingly digital business world. Especially in economic decision-making processes, the ability to judge the trustworthiness of pertinent data sets is inevitable for reliable decisions. Thus, geospatial competencies need to supplement the university’s teaching syllabus of economic degree programmes. Even if these programmes already have a lot of content, it is worth adding geospatial topics to educate students as skilled young experts, being geospatially literate. This contribution shows an approach on how to sensitise students and teachers with an economics background to understand the origin of geospatial data sets, their specific nature, their quality and how to gain geospatial data sets with a particular focus on sustainable economics applications. It proposes a teaching approach for educating students on geospatial characteristics of data, making them aware of spatial reasoning and spatial thinking. Especially it is vital to give them an impression of the manipulating nature of maps and geospatial visualisations. The aim is to show them the power of geospatial data and map products for research in their specific thematic field. The presented teaching concept originates from an interdisciplinary data literacy course geared to students other than geospatial sciences. It incorporates elements of a flipped classroom and a self-learning tutorial. This paper shows and discusses the results of the implementation of the course. Positive exam results imply that the teaching concept provides a suitable way to impart geospatial competencies to students belonging other than geo-related subjects.

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“…Auf nationaler Ebene bestehen Ansätze, Kompetenzrahmen für die Erfassung digitaler Kompetenzen zu finden, insbesondere etwa ein Future Skills Framework, das sich auf die Wertschöpfung aus Datenverarbeitung als kompetenzdefinierende Aufgabe für den Bereich der "Data Literacy" darstellt. 278 Data Literacy selbst wird definiert als "das Cluster effizienter Verhaltensweisen und Einstellungen für die effektive Durchführung sämtlicher Prozessschritte zur Wertschöpfung bzw. Entscheidungsfindung aus Daten".…”

Section: Aa) Ansätze Und Kompetenzrahmenunclassified

Digitalisierung und Kompetenzen

Catakli¹

2022

Verwaltung Im Digitalen Zeitalter

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Ein Framework für Data Literacy

Cited by 19 publications

References 5 publications

Data and AI literacy for everyone

Data and AI literacy for everyone

Grundlegende Geodatenkenntnisse für wirtschaftliche Anwendungen

Digitalisierung und Kompetenzen

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