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

Abstract

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.

Résumé

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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Notes

  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.

References

  1. Bates, D. M. (2010). lme4: Mixed-effects modeling with R. [R-Forge platform URL http://lme4.r-forge.r-project.org/book/; online resource]. Retrieved 11 March 2016 from http://lme4.r-forge.r-project.org/lMMwR/lrgprt.pdf.

  2. Benavot, A. (2015). Literacy in the 21st century: Towards a dynamic nexus of social relations. International Review of Education, 61(3), 273–294.

    Article  Google Scholar 

  3. Benavot, A., & Braslavsky, C. (2007). School knowledge in comparative and historical perspective: Changing curricula in primary and secondary education. CERC Studies in Comparative Education series, vol. 18. Dordrecht: Springer.

  4. Chabbott, C. (2003). Constructing education for development: International organizations and education for all. New York: Routledge.

    Google Scholar 

  5. Desjardins, R. (2003). Determinants of literacy proficiency: A lifelong-lifewide learning perspective. International Journal of Educational Research, 39(3), 205–245.

    Article  Google Scholar 

  6. Desjardins, R., & Rubenson, K. (2013). Participation patterns in adult education: The role of institutions and public policy frameworks in resolving coordination problems. European Journal of Education, 48(2), 262–280.

    Article  Google Scholar 

  7. Hamilton, M. (2001). Privileged literacies: Policy, institutional process and the life of the IALS. Language and Education, 15(2–3), 178–196.

    Article  Google Scholar 

  8. Hamilton, M. (2012). Literacy and the politics of representation. Abingdon: Routledge.

    Google Scholar 

  9. Hamilton, M., Maddox, B., & Addey, C. (2015). Literacy as numbers: Researching the politics and practices of international literacy assessment regimes. Cambridge: Cambridge University Press.

    Google Scholar 

  10. Hanemann, U. (2015). Lifelong literacy: Some trends and issues in conceptualising and operationalising literacy from a lifelong learning perspective. International Review of Education, 61(3), 295–326.

    Article  Google Scholar 

  11. Hanushek, E. A., & Woessmann, L. (2010). The economics of international differences in educational achievement. Cambridge, MA: National Bureau of Economic Research.

    Google Scholar 

  12. Hanushek, E. A., Schwerdt, G., Wiederhold, S., & Woessmann, L. (2013). Returns to skills around the world: Evidence from PIAAC. NBER Working Paper No. 19762. Cambridge, MA: National Bureau of Economic Research (NBER). Retrieved 7 November 2017 from http://www.nber.org/papers/w19762.pdf.

  13. Heisz, A., & Oikawa, C. (2017, April). The longitudinal and international study of adults: A Canadian PIAAC-Longitudinal. Paper presented on 5 April at the International Conference on PIAAC and PIAAC-Longitudinal in Mannheim, Germany.

  14. Lam, W. S. E., & Warriner, D. S. (2012). Transnationalism and literacy: Investigating the mobility of people, languages, texts, and practices in contexts of migration. Reading Research Quarterly, 47(2), 191–215.

    Article  Google Scholar 

  15. Meyer, H. D., & Benavot, A. (2013). PISA, power, and policy: The emergence of global educational governance. Oxford: Syposium Books.

    Google Scholar 

  16. Meyer, J. W., Kamens, D. H., & Benavot, A. (1992). School knowledge for the masses: World models and national primary curricular categories in the twentieth century. Washington, DC: Falmer.

    Google Scholar 

  17. OECD (Organisation for Economic Co-operation and Development). (2013a). OECD skills outlook 2013: First results from the survey of adult skills. Paris: OECD. Retrieved 7 November 2017 from https://www.oecd.org/skills/piaac/Skills%20volume%201%20(eng)–full%20v12–eBook%20(04%2011%202013).pdf.

  18. OECD. (2013a). The survey of adult skills: Reader’s companion. Paris: OECD.

    Google Scholar 

  19. OECD. (2013b). Technical report of the survey of adult skills (PIAAC). Paris: OECD.

    Google Scholar 

  20. Pellizzari, M., & Fichen, A. (2013). A new measure of skills mismatch: Theory and evidence from the survey of adult skills (PIAAC). Paris: OECD Publishing.

    Google Scholar 

  21. Rammstedt, B., Danner, D., & Lechner, C. (2017). Personality, competencies, and life outcomes: results from the German PIAAC longitudinal study. Large-scale Assessments in Education, 5(1), 2.

  22. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (vol. 1). Thousand Oaks, CA: Sage.

  23. Richmond, M., Robinson, C., & Sachs-Israel, M. (Eds.). (2008). The global literacy challenge: A profile of youth and adult literacy at the mid-point of the united nations literacy decade 2003–2012. Paris: UNESCO.

    Google Scholar 

  24. Robinson, C. (2005). Aspects of literacy assessment: Topics and issues from the UNESCO Expert Meeting [in Paris 10–12 June]. ED-2005NVW23. Paris: UNESCO. Retrieved 7 November 2017 from http://unesdoc.unesco.org/images/0014/001401/140125eo.pdf.

  25. Robinson, G. K. (1991). That BLUP is a good thing: The estimation of random effects. Statistical Science, 6(1), 15–32.

    Article  Google Scholar 

  26. Roma, F., & Bastianelli, M. (2017). Skills, non-cognitive dimensions and job complexity: A new framework for analysis from the “PIAAC Italy Survey”. Paper presented on 5 April at the International Conference on PIAAC and PIAAC-Longitudinal in Mannheim. Germany.

  27. Roosmaa, E.-L., & Saar, E. (2012). Participation in non-formal learning in EU-15 and EU-18 countries: Demand and supply side factors. International Journal of Lifelong Education, 31(4), 477–501.

    Article  Google Scholar 

  28. Singh, M. (2015). Global perspectives on recognizing non-formal and informal learning: Why recognition matters. Technical and Vocational Education and Training: Issues, Concerns and Prospects, 21. Heidelberg/Hamburg: Springer Open/UNESCO Institute for Lifelong Learning.

  29. St. Clair, R. (2012). The limits of levels: Understanding the international adult literacy surveys (IALS). International Review of Education, 58(6), 759–776.

    Article  Google Scholar 

  30. Tuijnman, A., & Boudard, E. (2001). Adult education participation in North America: International perspectives. Adult education and literacy monograph series. Ottawa, ON: Statistics Canada.

    Google Scholar 

  31. UIL (UNESCO Institute for Lifelong Learning). (2010). Confintea VI: Belém Framework for Action: Harnessing the power and potential of adult learning and education for a viable future. Hamburg: UIL. Retrieved 11 December 2017 from http://unesdoc.unesco.org/images/0018/001877/187789m.pdf.

  32. UIL. (2013). 2nd Global Report on Adult Learning and Education: Rethinking literacy. Hamburg: UNESCO Institute for Lifelong Learning (UIL).

    Google Scholar 

  33. UIL. (2015). UNESCO Guidelines for the recognition, validation and accreditation of the outcomes of non-formal and informal learning. Hamburg: UNESCO Institute for Lifelong Learning (UIL). Retrieved 7 November 2017 from http://unesdoc.unesco.org/images/0021/002163/216360e.pdf.

  34. UIL. (2016). 3rd Global Report on Adult Learning and Education: The impact of adult learning and education on health and well-being; employment and the labour market; and social, civic and community life. Hamburg: UNESCO Institute for Lifelong Learning (UIL).

    Google Scholar 

  35. UIS (UNESCO Institute for Statistics) (2016). Sustainable development data digest: Laying the foundation to measure sustainable development goal 4. Montreal: UNESCO Institute for Statistics (UIS). Retrieved 7 November 2017 from http://unesdoc.unesco.org/images/0024/002455/245559e.pdf.

  36. UIS. (2017). Literacy rates continue to rise from one generation to the next. Montreal: UNESCO Institute for Statistics (UIS). Retrieved 31 December 2017 from http://uis.unesco.org/sites/default/files/documents/fs45-literacy-rates-continue-rise-generation-to-next-en-2017_0.pdf.

  37. UNESCO (2006). Literacy for life. Education for All Global Monitoring Report 2006. Paris: UNESCO. Retrieved 7 November 2017 from http://unesdoc.unesco.org/images/0014/001416/141639e.pdf.

  38. UNESCO. (2014). Skills for holistic human development. UNESCO Asia-Pacific Education Policy Brief, vol. 2. Paris/Bangkok: UNESCO/UNESCO Bangkok. Retrieved 2 January 2018 from http://www.unescobkk.org/fileadmin/user_upload/epr/PDF/Policy_Brief_Vol2-28_Nov.pdf.

  39. UNESCO. (2015a). Education 2030: Incheon declaration and Framework for action for the implementation of sustainable development goal 4. Paris: UNESCO. Retrieved 7 November 2017 from http://unesdoc.unesco.org/images/0024/002456/245656e.pdf.

  40. UNESCO. (2015b). Global meeting on literacy and sustainable societies [UNESCO Headquarters, Paris, 8–9 September]. ED/PLS/YLS/2015/ME/1. Paris: UNESCO. Retrieved 8 November 2017 from http://unesdoc.unesco.org/images/0023/002344/234483E.pdf.

  41. UNESCO. (2017 [2016]). Unpacking Sustainable Development Goal 4, Education 2030: Guide. Revised. Paris: UNESCO. Retrieved 15 November 2017 from http://unesdoc.unesco.org/images/0024/002463/246300E.pdf.

  42. Werquin, P. (2010). Recognition of non-formal and informal learning: Country practices. Paris: Organisation for Economic Co-operation and Development (OECD). Retrieved 15 November 2017 from https://www.oecd.org/edu/skills-beyond-school/44600408.pdf.

  43. World Bank (2014). STEP Skills measurement surveys: Innovative tools for assessing skills. Washington, DC: Word Bank Group. Retrieved 1 January 2018 from https://openknowledge.worldbank.org/bitstream/handle/10986/19985/897290NWP0P132085290B00PUBLIC001421.pdf?sequence=1&isAllowed=y.

  44. Yang. J. (2015). Recognition, validation and accreditation of non-formal and informal learning in UNESCO Member States. Hamburg: UNESCO Institute for Lifelong Learning (UIL). Retrieved 15 November 2017 from http://unesdoc.unesco.org/images/0023/002326/232656e.pdf.

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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). https://doi.org/10.1007/s11159-018-9703-4

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Keywords

  • 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