Adults engage in learning for a wide range of reasons, shaped by their individual circumstances, needs, and aspirations (OECD, 2019[1]; OECD, 2021[2]). While many adults participate in learning for professional purposes – such as meeting employer requirements, pursuing career advancement, or preparing for occupational change – others are driven by personal interest or the desire for self-development. These motivations are often closely linked to individual characteristics, including age, educational attainment, employment status and previous learning experiences.
By contrast, many adults do not engage in learning, often due to a combination of structural and attitudinal barriers. Common structural challenges include time constraints related to work or family responsibilities, financial limitations and restricted access to appropriate learning opportunities. Attitudinal barriers may also play a role, with reluctance to engage in learning frequently rooted in low self-confidence, limited perceived relevance, or negative prior experiences with education and training. A main challenge is that adults who stand to benefit most from learning opportunities are often among the least likely to participate and facing most significant barriers. Existing policies and support measures frequently struggle to reach and engage these groups.
To better understand this complex set of behaviours and influences, this paper introduces a methodology for identifying distinct adult learner profiles based on the interaction of factors that influence learning participation. Using Latent Class Analysis (LCA), a quantitative clustering technique, the analysis groups individuals according to shared patterns of motivation and barriers. This approach provides a structured and evidence-based representation of the diversity within the adult learning population, offering valuable insights for policymakers and enabling more targeted and effective design, delivery and allocation of resources.
This policy paper outlines the rationale for adopting a segmentation approach (Chapter 1), presents learner profiles in four countries – Bulgaria, Finland, Ireland and Portugal – along with their policy implications (Chapter 2), and describes considerations for the implementation of learner profiles (Chapter 3). Together, the results provide a solid evidence base to support the development of more inclusive, tailored and effective adult learning systems. Key findings are listed below.