Predictors of literacy in adulthood: Evidence from 33 countries

Abstract

What makes a literate person? What leads to literacy gains and losses within and between individuals and countries? This paper provides new evidence that helps answer these questions. The present comparative analysis of literacy is based on large representative samples from the Survey of Adult Skills conducted in 33 countries, with 25–65 year old participants. We provide, for the first time, estimates of relative importance for a comprehensive set of experiential factors, motivations, incentives, parental influence, demands of workplace, and other predictors of influence. We sketch a configuration of factors that predicts an “ideal” reader, i.e., the optimal literacy performance. Moreover, we discover a pivotal role of the age effect in predicting variability between countries. Countries with the highest literacy scores are the ones where literacy decreases with age the most strongly. We discuss this finding against current accounts of aging effects, cohort effects and others. Finally, we provide methodological recommendations for experimental studies of aging in cognitive tasks like reading.

Patterns and Predictors of Literacy and Numeracy Development During Adulthood: Insights from Two Longitudinal Assessment Surveys

“…Prior research on competencies-summarized in informative reviews by Desjardins and Warnke (2012), Paccagnella (2016), andNienkemper et al (2021, focusing on low literacy) and expanded by recent studies (e.g., Kyröläinen & Kuperman, 2021)-offers several important insights into the age profiles and into the precursors and correlates of adults' competencies. Much prior research is limited, however, by the research designs that fall mainly into one of two categories: large-scale crosssectional and small-scale longitudinal studies.…”

“…LDV or 'residual change' models control for initial competence levels and thus predict change over the initial competence levels (e.g., Johnson, 2005). In cross-sectional analyses based on PIAAC and its predecessors, educational attainment has long been identified as the key determinant of literacy and numeracy (e.g., Desjardins, 2003;Kyröläinen & Kuperman, 2021;Paccagnella, 2016). Analyses in PIAAC-L replicated these Matthew effects of educational attainment for both literacy and numeracy (Reder et al, 2020).…”

Register identification from the unrestricted open Web using the Corpus of Online Registers of English

“…It is upheld not only by culturally shared properties, but it is also affected and guided through institutional practice over time (Biber & Conrad, 2009;Görlach, 2004;Swales, 1990). For example, practices in educational systems provide a strong and beneficial effect on language comprehension (Kyröläinen & Kuperman, 2021) and the means for upholding conventionalized linguistic patterns, for example, in the structuring of research articles and technical reports. Additionally, editorial conventions can contribute to the degree of conventionalization associated with registers, such as magazine articles and news reports.…”

Effects of Linguistic Distance on Cognitive Skills, Health, and Social Outcomes in Canadian Immigrants

“…Other independent variables were selected on the basis of the cross-national analyses of major predictors of literacy (Kyröläinen and Kuperman, 2021). Some variables are often considered as predictors of other dependent variables than literacy as well.…”

“…PIAAC data come with weights that enable each observed respondent to represent a larger segment of the Canadian population. As described in Kyröläinen and Kuperman (2021), we used ordinary least squares regressions with Jackknife Repeated Replication weights that correct for the complex design of the PIAAC samples (Organisation for Economic Co-operation and Development, 2013). The appropriate regression functions are implemented in the package intsvy that is designed specifically for the PIAAC data (Caro and Biecek, 2017) and is provided in the statistical platform R 3.6.1 (R Core Team, 2021).…”