Survive to stay connected: patterns of user experiences in a Life Long Learning digital platform

In an ever-changing world, having the right competences for the job market represents a key challenge for sustained employability. To address this need a growing number of digital platform for life long learning (LLL) has been developed. Anyway, it is less known how users navigate and use these platforms. The present study represents a one of the first attempts to fill this gap, offering a deep analysis for the identification of latent subgroups of learners with similar behaviours on a digital LLL platform. Then, the identified subgroups are described in terms of personal features and survival profiles. Findings reveal three distictive latent classes, with very different survival profiles. The analysis provides interesting insights about how the administators of a digital LLL platform can better personalize their contents according to the type of learner, to support and let them stay on the platform, acquiring the needed skills for the job market.