This paper has demonstrated that adults’ engagement in learning is shaped by a complex interplay of motivations, barriers, and contextual factors that extend well beyond traditional socio-demographic categories. By applying a segmentation approach grounded in Latent Class Analysis to data from Bulgaria, Finland, Ireland, and Portugal, the paper has shown that adults cluster into distinct learner profiles that reflect meaningful and policy-relevant patterns of behaviour. These profiles offer a more nuanced and actionable understanding of why adults choose to participate in, or refrain from, learning.
Across all four countries, one central finding stands out: a substantial share of non-participants are “disengaged” not because they are constrained by cost, time, or access, but because they do not perceive learning to be relevant or necessary. This pattern is most pronounced in Bulgaria, but evident in each country. Addressing this motivational deficit requires a sustained emphasis on awareness-raising, confidence-building, and creating visible value in upskilling and reskilling opportunities. Structural reforms alone will not be sufficient to re-engage these groups.
At the same time, the analysis reveals multiple profiles of adults who are motivated to learn but constrained by a diverse set of structural or personal obstacles. These include adults facing financial constraints, family responsibilities, demanding schedules, limited programme suitability, or health and age-related limitations. Their presence across all countries underlines the continued importance of reducing practical barriers through flexible provision, targeted financial support, strengthened guidance and accessible learning pathways. The profiles also highlight that barriers often cluster and compound one another, reinforcing the need for integrated approaches that combine education, employment, health and social support.
Among adults already participating, the results highlight a diverse spectrum of motivations. A recurring profile of “Unmotivated but Obligated” learners underscores that participation alone cannot be equated with meaningful engagement; compulsory or externally driven learning is common but does not necessarily foster sustained or self-directed development. In contrast, intrinsically motivated and multi-motivated learners – although a smaller share in some countries – illustrate the significant potential of learning to support personal growth, career advancement, and broader wellbeing. The coexistence of these profiles underlines the importance of designing provision that is both responsive to labour market needs and aligned with individuals’ interests, aspirations and preferred modes of engagement.
Taken together, the findings suggest that adopting a segmentation approach can markedly strengthen adult learning systems. Learner profiles can support clearer identification of target groups, more effective outreach, better-tailored incentives, and more robust monitoring of policy reach and impact. They also highlight the limitations of one-size-fits-all strategies and the importance of embedding learner-centred design principles across skills ecosystems. At the same time, the use of profiles requires careful implementation to avoid oversimplification or the reinforcement of stereotypes, and to ensure regular updating as needs and contexts evolve.
Looking ahead, further work – such as enriching profiles with additional socio-demographic and labour market characteristics, developing diagnostic tools for practitioners and examining applications using complementary datasets such as PIAAC – would enhance the practical utility of this approach. Nonetheless, the evidence presented in this paper provides a strong foundation: by making visible the diversity of adult learners, segmentation can help countries design more inclusive, targeted, and effective policies that support adults to develop the skills they need throughout life.