Modeling Determinants of Lifelong Learning According to the Theory of Planned Behavior: A Proxy-Based Approach Using PIAAC Data

In today's world, lifelong learning (LLL) is a key element of individual and societal success. However, despite knowing potential determinants of LLL, we do not yet understand how they interact to facilitate LLL. Therefore, the present study aims to verify the usefulness of the Theory of Planned Behavior (TPB) in predicting LLL. We applied a survey data-based approach by building proxies of TPB components for LLL based on the German PIAAC dataset. Our TPB-based path models explained both participation in non-formal LLL and engagement in informal LLL in a large heterogeneous sample of the German working population, also when controlling for influential socio-demographic determinants of LLL. Thereby, our results provide first evidence that TPB lends itself as core of a LLL process model that can serve as a basis to integrate further well-studied determinants of LLL participation and then can be tested in longitudinal multi-level studies.