Enabling Self-Directed Digital Learning Among Older Workers – Organizational Conditions and Individual Learning Strategies

The rapid digital transformation and demographic change are reshaping the world of work. Older workers (aged 50+) are particularly affected, facing challenges in acquiring digital competences and engaging in digital learning. As a result, companies must pay special attention to the design and facilitation of adequate learning environments and processes, tailored to older workers and workplace learning in order to maintain employability. A new approach to learning is required and one way for companies to address this issue is through encouraging self-directed digital learning, especially among older workers. Therefore, this thesis investigates the challenges and opportunities in fostering self-directed digital learning among older workers in companies. In particular, which organizational and individual factors support or hinder self-directed digital learning among older workers and how companies can better facilitate these learning processes. Building on theories and perspectives of adult education, geragogy, and human resources development, the study focuses on informal and non-formal learning, recognizing the limitations of traditional, formal training programs. Emphasis is placed on self-directed learning as a means to facilitate individualized, autonomous, and sustainable learning processes that align with the everyday work realities of older workers. Through a literature-based analysis, the thesis explores both organizational (meso level) and individual (micro level) factors that support or hinder self-directed digital learning. The Digital Competence Framework for Citizens (DigComp 2.2) provides the framework for digital competence requirements in a lifelong learning context. The aim is to conceptualize self-directed digital learning among older workers, analyze favourable conditions, and derive recommendations for human resources development strategies in companies.