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Assessing Learning Interventions among Blue-Collar Workers

Author

Listed:
  • Barbara Ofstad

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes)

  • Anne Bartel-Radic

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes, IEPG - Sciences Po Grenoble-UGA - Institut d'études politiques de Grenoble - UGA - Université Grenoble Alpes)

Abstract

The digital transformation requires continuous skill development for experienced workers in all industries, especially blue-collar employees. Therefore, it is essential to evaluate the effectiveness of learning interventions. This study applies the Kirkpatrick model to measure the satisfaction and outcomes of 710 blue-collar workers at a German high-tech company at different time points. We contribute to the literature by assessing learning in the under-researched context of blue-collar worker training in a high-tech industrial setting in Germany. Workers' training satisfaction strongly influences their perceived learning, and their behavior changes influence performance. The study also reveals differences related to training content: blue-collar workers give better grades to traditional training topics vs. to those related to future technologies. To increase satisfaction with future learning interventions, managers may want to emphasize the purpose of the trainings and bundle classic and future learning topics to anchor the learnings more credibly into workers' daily routines.

Suggested Citation

  • Barbara Ofstad & Anne Bartel-Radic, 2026. "Assessing Learning Interventions among Blue-Collar Workers," Post-Print hal-05790796, HAL.
    • Handle: RePEc:hal:journl:hal-05790796
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