Literacy skills gaps: A cross-level analysis on international and intergenerational variations


The global agenda for sustainable development has centred lifelong learning on UNESCO’s Education 2030 Framework for Action. The study described in this article aimed to examine international and intergenerational variations in literacy skills gaps within the context of the United Nations Sustainable Development Goals (SDGs). For this purpose, the author examined the trend of literacy gaps in different countries using multilevel and multisource data from the OECD’s Programme for the International Assessment of Adult Competencies (PIAAC) and UNESCO Institute for Lifelong Learning survey data from the third edition of the Global Report on Adult Learning and Education (GRALE III). In this article, particular attention is paid to exploring the specific effects of education systems on literacy skills gaps among different age groups. Key findings of this study indicate substantial intergenerational literacy gaps within countries as well as different patterns of literacy gaps across countries. Young generations generally outscore older adults in literacy skills, but feature bigger gaps when examined by gender and social origin. In addition, this study finds an interesting tendency for young generations to benefit from a system of Recognition, Validation and Accreditation (RVA) in closing literacy gaps by formal schooling at country level. This implies the potential of an RVA system for tackling educational inequality in initial schooling. The article concludes with suggestions for integrating literacy skills as a foundation of lifelong learning into national RVA frameworks and mechanisms at system level.


Écarts d’alphabétisation: analyse multi-niveaux sur les variations internationales et intergénérationnelles – Le programme mondial de développement durable a placé l’apprentissage tout au long de la vie au centre du Cadre d’action Éducation 2030 de l’UNESCO. L’un des buts de l’étude présentée dans cet article consistait à examiner les variations internationales et intergénérationnelles dans les écarts d’alphabétisation par rapport aux Objectifs de développement durable (ODD) énoncés par les Nations Unies. À cette fin, l’auteure a exploré la tendance aux écarts d’alphabétisation dans divers pays, à partir de données multi-niveaux et multi-sources issues du Programme pour l’évaluation internationale des compétences des adultes (PEICA) de l’OCDE ainsi que des données d’enquête de l’Institut de l’UNESCO pour l’apprentissage tout au long de la vie pour la troisième édition du Rapport mondial sur l’apprentissage et l’éducation des adultes (GRALE III). Dans cet article, l’auteure porte une attention particulière aux effets spécifiques des systèmes éducatifs sur les écarts d’alphabétisation entre différents groupes d’âge. Les principaux résultats de cette étude indiquent d’importants écarts entre les générations à l’intérieur des pays ainsi que différents schémas entre les pays pour ces écarts d’alphabétisation. Les jeunes générations possèdent globalement des compétences lettrées supérieures aux adultes plus âgés, mais présentent des écarts plus marqués s’ils sont examinés en fonction du sexe ou de l’origine sociale. Cette étude établit en outre la tendance favorable pour les jeunes générations à tirer profit d’un système de reconnaissance, validation et accréditation (RVA), qui comble au niveau national les écarts d’alphabétisation survenus lors de la scolarité formelle. Ce qui implique qu’un système RVA ait le potentiel pour combattre les inégalités éducatives apparues au cours de la scolarité de base. L’article conclut sur des suggestions pour incorporer l’alphabétisation en tant que fondement de l’apprentissage tout au long de la vie dans les cadres nationaux de RVA et dans les mécanismes au niveau systémique.

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  1. 1.

    Foundation skills refer to “the basic academic knowledge and skills that learners acquire often as result of their participation in formal school education (primary and secondary schools) or sometimes through non-formal and informal learning opportunities. These skills, which include basic literacy and numeracy skills, provide the foundation upon which learners receive further education to deepen their capacity for fulfilling, meaningful lives and decent jobs” (UNESCO 2014, p. 2).

  2. 2.

    Recognition, Validation and Accreditation (RVA) of non-formal and informal learning is a key element of adult learning and education policy, providing an incentive for individuals to continue to learn and to enable them to become more active in the labour market and society (UIL 2015).

  3. 3.

    Quintiles refer to five equal groups, each representing 20 per cent of a given population.

  4. 4.

    While formal education refers to the traditional school, college and university setting; non-formal education refers to any organised educational activity outside the established formal system, and informal education refers to the truly lifelong process whereby every individual acquires attitudes, values and skills and knowledge from daily experience and the educative influences and resources in his or her environment.

  5. 5.

    Plausible values are a means to analyse the latent trait being measured; they are imputed values that resemble individual test scores and have approximately the same distribution. Item Response Theory (IRT) is a theory of testing based on the relationship between individuals' performances on a test item and the test taker's levels of performance on an overall measure of the ability that item was designed to measure. Latent regression refers to the analytical technique to measure a linear relationship between latent variables.

  6. 6.

    Replicate weights allow a single sample to simulate multiple samples and generate more informed standard error estimates that mimic the theoretical basis of standard errors while retaining all information on the complex sample design.

  7. 7.

    The Belém Framework for Action is the outcome document of the Sixth International Conference on Adult Education (CONFINTEA VI), held 1–4 December 2009 in Belém, Brazil. In the preamble, UNESCO Member States “deem it vital that we redouble our efforts to ensure that existing adult literacy goals and priorities, as enshrined in Education for All (EFA), the United Nations Literacy Decade (UNLD) and the Literacy Initiative for Empowerment (LIFE), are achieved by all means possible” (UIL 2010, p. 5).

  8. 8.

    R is a free and open source software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.

  9. 9.

    Aggregation bias and ecological fallacy refer to a logical fallacy in the interpretation of statistical data where inferences about the nature of individuals are deduced from inference for the group to which those individuals belong. .

  10. 10.

    The random intercept model is a model in which intercepts are allowed to vary, and therefore, the scores on the dependent variable for each individual observation are predicted by the intercept that varies across groups.

  11. 11.

    Random coefficient regression refers to a model in which slopes are allowed to vary, and therefore, the slopes are different across groups.

  12. 12.

    Confidence intervals refer to a type of interval estimate (of a population parameter) that is computed from the observed data; the standard error of a parameter is the standard deviation of its sampling distribution or an estimate of the standard deviation.

  13. 13.

    For a clear interpretation of the coefficient slopes, this study relies on dummy coding in the multivariate regression models to use a category variable (gender and RVA).

  14. 14.

    In statistical analysis, coefficient and regression slopes refer to a slope of the linear relationship between a dependent variable and the part of a predictor variable that is independent of all other predictor variables.

  15. 15.

    Best Linear Unbiased Prediction (BLUP) estimates coefficients of unobserved random slopes that vary in a multilevel model. These coefficients allow the intercept and slope for conditional fitted equations to be determined, which predict the fitted values for the specific groups (Bates 2010; Robinson 1991).

  16. 16.

    The random-effect analysis was conducted using the lmer package in R.

  17. 17.

    A null model refers to the HLM model without predictors. A contextual model includes national-level predictors, while an interaction model shows an interaction effect between predictors at individual level and national level.


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Kim, S. Literacy skills gaps: A cross-level analysis on international and intergenerational variations. Int Rev Educ 64, 85–110 (2018).

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  • literacy skills gap
  • Sustainable Development Goals (SDGs)
  • Programme for the International Assessment of Adult Competencies (PIAAC)
  • Global Report on Adult Learning and Education (GRALE)
  • cross-level analysis