CKoBeLeP II – Digitalized Knowledge Work

Project Background

CKoBeLeP is a subproject within the Center for Digitalization and Technology Research of the Bundeswehr (dtec.bw), funded by the European Union as part of the NextGenerationEU initiative. The project is structured in two phases: CKoBeLeP I (2021–2024) and CKoBeLeP II (2025–2026). While Phase I focused on empirically investigating crowdwork and crowdworking platforms from vocational education and labor sociology perspectives, Phase II is dedicated to examining digitalized knowledge work within traditional organizational settings.

Phase I

The objective of CKoBeLeP I was to conduct an empirical analysis of crowdworking platforms and to support the development of platform-based work that aligns with principles of social sustainability and learning enhancement. The interdisciplinary research team explored competence-related and subjectivation effects, the role of crowdwork in career trajectories, and the design of platform work to foster learning. Particular attention was given to crowdworkers engaging in platform labor either as a secondary or primary form of employment.

Research and development activities were conducted in collaboration with selected crowdworking platforms and relevant stakeholders as practice partners. The following subprojects addressed specific facets aligned with the project’s overarching aims:

  • Individual Professionalism (Prof. Dr. Karin Büchter, HSU/UniBw H): Analysis of shifts in professional identity and educational paradigms in light of the specific demands and subjectivation processes inherent in crowdwork.
  • Knowledge, Competence, and Learning (Prof. Dr. Tobias Schlömer, HSU/UniBw H): Exploration of knowledge domains, core concepts, learning practices, and expertise among crowdworkers, emphasizing empowerment and the learning potential of platform-based work from a vocational education and training perspective, enriched by practice-theoretical approaches.
  • Subjectivation (Prof. Dr. Frank Kleemann, University of Duisburg-Essen): Examination of the subjective meaning of crowdwork, its integration into individual life contexts, and the learning practices it fosters, from a labor sociology standpoint.
  • Transitions and Communities of Practice (Prof. Dr. Martin Krzywdzinski, HSU/UniBw H & WZB): Investigation of career transitions among crowdworkers and the role of Communities of Practice in enabling learning processes, even within highly individualized work structures.

Phase II

CKoBeLeP II explores the extent to which the findings from Phase I—derived from crowdwork as a prototypical form of digital labor—are applicable to other types of digitalized knowledge work. The research centers on sectors such as Data Science and Commercial Professions, both of which are increasingly shaped by Artificial Intelligence (AI), Big Data, and Automation.

The aim is to identify both commonalities and sector-specific characteristics across various professional fields. This focus is particularly relevant for three reasons:

  • Crowdwork, as studied in Phase I, serves as a prototype for digital knowledge work.
  • The transformation of knowledge-based work through digitalization is exemplified in these domains.
  • The contrast between diverse professional groups offers valuable comparative insights.

Expanded Project Focus

The project investigates the evolution of commercial and data science competencies in the context of AI and Big Data through the following lenses:

  • The conceptual foundations and knowledge frameworks utilized by professionals in AI- and Big Data-driven decision-making processes.
  • The interplay between AI and Big Data applications and work practices, innovation dynamics, and leadership within organizations, including the evolving role of managers amid digital transformation.
  • The impact of cultural factors on the adoption and integration of AI and Big Data technologies.
  • The further development of the Relational Constellations concept in the context of increasingly divided and specialized labor.
  • The work processes and activities of data scientists in manufacturing environments, with a focus on standardization, routine formation, changes in the knowledge base, and the integration of emerging technologies.
  • Innovative strategies for digital transformation and leadership development, and their effective incorporation into operational workflows.

Project Partners

Helmut Schmidt University / University of the Federal Armed Forces Hamburg

University of Duisburg-Essen

ZUKUNFT.unternehmen gGmbH

  • Prof. Dr. Stephanie Birkner
  • Leon Schmidt

Project Team

Access the project team

Funding

Foerderhinweis
HSU

Letzte Änderung: 3. June 2025