Code/Syntax: Grasping Digitalization in the Working World

DOI

Digitalization and automation have increased substantially in recent years and are reshaping the working world. These fundamental changes alter employee training needs and training programs. They create new employment opportunities, may cause excessive demands or raise fears of job loss. The extent of the societal transitions induced by the ongoing digitalization call for high-quality research data. In this paper, we introduce a new multi-dimensional survey module on digitalization and its consequences for the working world, which has recently been implemented in the adult cohorts of the German National Educational Panel Study (NEPS). We show how well and for which employee groups the newly developed survey questions capture experiences with digital technologies at the workplace. We test for the applicability of the instrument with regard to gender, age, education, and job tasks and show that it predicts employee’s actual participation in further training. Moreover, we show the potential that results from the combination of the new survey module with further key strengths of the NEPS data such as its life-course or competence measures. The files provided here use data from the National Educational Panel Study (NEPS): Starting Cohort Adults, https://doi.org/10.5157/NEPS:SC6:12.0.0 . From 2008 to 2013, NEPS data was collected as part of the Framework Program for the Promotion of Empirical Educational Research funded by the German Federal Ministry of Education and Research (BMBF). As of 2014, NEPS has been carried out by the Leibniz Institute for Educational Trajectories (LIfBi) in cooperation with a nationwide network.

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Identifier
DOI https://doi.org/10.7802/2362
Source https://search.gesis.org/research_data/SDN-10.7802-2362?lang=de
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=98d3ba577c3be762afd633d90b88a0d7807070bae97e082187ed689edaf80ab7
Provenance
Creator Friedrich, Teresa; Laible, Marie-Christine; Pollak, Reinhard; Schongen, Sebastian; Schulz, Benjamin; Vicari, Basha
Publisher GESIS Data Archive for the Social Sciences; GESIS Datenarchiv für Sozialwissenschaften
Publication Year 2022
Rights Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.; Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden.
OpenAccess true
Contact http://www.gesis.org/
Representation
Discipline Social Sciences
Spatial Coverage Germany; Germany