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Statistics on adult education and training (AET) are often considered as insufficient because they fail to deliver a comprehensive and consistent picture of this field of education. This study addresses a specific problem in AET statistics that is varying participation rates of adults in AET depending on underlying data sources. We elaborate potential causes for deviations in survey design and the measurement of participation in sample based AET statistics with reference to the Total Survey Error (TSE) approach. Our analysis compares AET participation rates and patterns from four representative German surveys and reveals substantial differences in participation rates and mixed results for patterns of participation in AET. We find similar relationships for the influence of employment and educational attainment. The relationship with region, gender, and age shows to some extent deviations that conclude in contradictory statements on probabilities of participation. The discussion addresses consequences for the interpretation of survey results on AET participations and draws conclusions for the further development of AET statistics.

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Research collaboration promises a useful approach to bridging the gap between research and practice and thus promoting evidence-informed education. This study examines whether information on research collaboration can influence the reception of research knowledge. We assume that the composition of experts from the field and scientists in a research team sends out signals that influence trust in as well as the relevance and applicability of the finding. In a survey experiment with practitioners from the field of adult education the influence of different research team compositions around an identical finding is tested. The results show overall high trust, relevance and applicability ratings with regard to the finding, regardless of the composition of the research team. We discuss the potential importance of additional information about research collaborations for effective knowledge translation and point out the need for more empirical research.

It is challenging to investigate wider benefits of adult learning, especially in later life, due to limited data on educational activities and non-monetary returns in large, longitudinal surveys. Statistical matching provides an approach to exploit the potential of existing data by combining data sources with complementary features based on shared information. The paper describes the matching of two data sources (German Ageing Survey and Study of Educational Attainment and Interests of Older People) in order to examine the effects of educational participation on well-being in later life. We emphasize the matching procedure and how to identify the best-matched dataset. Based on matched data, effects of educational activities on life satisfaction are examined in later life. The