Zugang zu non-formalen Weiterbildungsmöglichkeiten der digitalen Kompetenzen für Erwachsene in Österreich.

Fröhlich, Dominik; Horvath, Louise; Brunner, Philipp; Swertz, Christian

doi:10.21243/mi-04-19-06

Cited by 1 publication

(1 citation statement)

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“…The Digital Competence Model is used to classify and compare digital competencies. It has been the basis for research on digital literacy needs (Evangelinos & Holley, 2016) and attitudes (Evangelinos and Holley, 2015), on social work practise (Zhu and Andersen, 2021), as well as practices and policies in different educational areas, such as primary and secondary education (Guitert et al, 2021;Hatlevik et al, 2015), vocational education and training (Burns et al, 2020), adult education (Fröhlich et al, 2019) and higher education (Zhao et al, 2021). Moreover, the European Reference Framework for Digital Competencies is used in labour markets studies (Kluzer et al, 2020) and to some the model even constitutes a foundational digital literacy for all (Murphy, 2018).…”

Section: Mode Of Use and Competencesmentioning

confidence: 99%

Assessing the Second-Level Digital Divide in Austria: A Representative Study on Demographic Differences in Digital Competences

Schmölz,

Geppert,

Schwarz

et al. 2023

DER

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The second-level digital divide concerns individual levels of digital competences and demographic indicators of digital gaps. In this paper, we have analysed empirical data that allow a thorough and differentiated look into the second-level digital divide with a rigorous methodological quantitative approach. We investigated the relationship between results from a self-assessment of one’s own digital competences, and a knowledge test about digital tools among Austrian citizens (N=1109). The study explores second-level digital divides in gender, education level, age, first language, and length of time living in the country regarding respective competence levels and areas, referring to the Digital Competence Model for Austria - DigComp 2.2 AT. Results show that the digital gender divide is paramount across all competence areas, while the age divide remains strong when comparing under 18-year-olds with over 60-year-olds. Moreover, positive effects are related to education level and first language.

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