We tackle our research challenges through a design-based research methodology, which involves iteratively designing, testing and refining our frameworks in real-world industry-academia partnerships.

Our goal is to understand and enhance the learning and knowledge creation and transfer processes.

Our approach integrates insights from various fields, including educational sciences and workplace learning, with technological domains such as human-computer interaction, learning analytics, data visualization, and algorithmic design.

This methodology focuses on finding solutions for practical problems through an iterative and cyclical process, allowing for continuous refinement and improvement.

Adopting a design-based research approach allows us to develop a framework that fosters collaborative knowledge creation and transfer within complex socio-technical systems and which will influence the design of future workplace learning tools and methodologies.

By engaging diverse participants from enterprises, the start-up industry, Early-Stage Researchers (ESRs), and other researchers, our approach will iteratively reify the problem space while refining, evaluating and advancing these tools and methodologies.

1. Initial Phase: Theoretical Frames -> Low-Fidelity Prototypes

In the initial phase, we will focus on developing theoretical frames of reference, which in turn will guide the co-creation of low-fidelity representations of tools and methods aimed at enhancing workplace learning, facilitating knowledge transfer across organizational boundaries and forecasting needs and opportunities. ESRs will play an important role, contributing their research insights and collaborating with industry partners employing generative design research to ensure cutting-edge theoretical perspectives meet practical needs, aligning our conceptual understanding with real-life opportunities and ambitions.

2. Concept validation: Iterative “In-the-Wild” problem refinement → High-Fidelity Prototypes

High-fidelity prototypes will be developed and used in iterative “in-the-wild” reification processes where ESRs will further clarify the problem space while maturing proposed tools and methods, and conduct concept validation studies.

3. Pilot Testing: Stakeholder Feedback → Iterative improvements of the prototypes

The developed prototypes will then undergo pilot testing in various cross-organizational settings to gather feedback from stakeholders across different sectors. ESRs will actively participate in these pilot tests, facilitating the integration of research findings into iterative improvements of the prototypes. This collaboration will enhance mutual learning between academia and industry, advancing both theoretical understanding and practical applications of workplace learning and knowledge transfer.

4. Evaluation in authentic settings: Feedback → Iterative Refinement

Following the pilot phase, thorough evaluation and iterative refinement will be conducted based on the feedback received. ESRs will continue to contribute their expertise in evaluating the prototypes in intervention and field studies in authentic settings, ensuring that the final frameworks and proof-of-concept tools effectively scaffold individual learning processes, foster collaborative knowledge creation within organizational contexts and enable and enable forecasting needs and opportunities in education, training to meet future labor market and industry needs.

Intervention and field studies will be evaluated via observation, diaries, surveys and interviews to understand the effects of our tools and practices in their envisioned context of use.