Educational poverty has become a key reference to consider education as an essential functioning, just as health, social relations, employment, housing conditions and economic resources (Sen, 1992, 1997). Allmendinger (1999) distinguishes between two types of educational poverty: lack of formal education and lack of competencies. We suggest merging the two, considering educational poverty as 1) the lack of a certificate, 2) low level of basic competencies or 3) the two taken together. Adopting this notion of educational poverty, we discuss outcomes from a multivariate analysis we have carried on comparing poorly educated student and adult populations in EU28 countries, UK and Norway. For this purpose, we considered 1) low scoring in mathematics and reading at the OECD PISA tests as a potential predictor of educational poverty in adulthood; 2) upper secondary school dropout rates, NEETs rates and the percentage of young people aged 20 to 39 without a university degree. 3) Finally, among the adult population, we estimated the share of low secondary education attainers and/or lower achievers in literacy and numeracy. We therefore have cross-nationally compared not only the educational levels of the adult population, but also the diffusion of functional illiteracy. Data sources are respectively from: 1) the European Social Survey and Eurostat indicators useful to get the international framework of education levels and illustrative/control variables such as public spending on education; 2) the PIAAC survey on adult skills and 3) OECD-PISA 2018 assessment results for 15-year-old student’s abilities in mathematics and sciences. After a preliminary descriptive analysis, data have been computed via (PCA) Principal Component Analysis and Cluster analysis to graphically project countries cluster-groups distributions in relation to latent dimensions. Emerging results stress out the high diffusion of educational poverty especially among the Italian and Spanish population and the need to strengthening policies against poverty in a multidimensional perspective, so that economic schemes tackling economic poverty could be linked to long-term policies aiming at improving basic social skills and therefore reducing the risk of both educational and economic poverty.
Educational Poverty in Europe: Mixing Education as Certification and as Competencies among Youth and Adult Population / Salmieri, Luca; Giancola, Orazio; Colarusso, Simona. - (2021), pp. 419-432. (Intervento presentato al convegno REINVENTING EDUCATION tenutosi a online).
Educational Poverty in Europe: Mixing Education as Certification and as Competencies among Youth and Adult Population
Luca Salmieri
;Orazio Giancola;Simona Colarusso
2021
Abstract
Educational poverty has become a key reference to consider education as an essential functioning, just as health, social relations, employment, housing conditions and economic resources (Sen, 1992, 1997). Allmendinger (1999) distinguishes between two types of educational poverty: lack of formal education and lack of competencies. We suggest merging the two, considering educational poverty as 1) the lack of a certificate, 2) low level of basic competencies or 3) the two taken together. Adopting this notion of educational poverty, we discuss outcomes from a multivariate analysis we have carried on comparing poorly educated student and adult populations in EU28 countries, UK and Norway. For this purpose, we considered 1) low scoring in mathematics and reading at the OECD PISA tests as a potential predictor of educational poverty in adulthood; 2) upper secondary school dropout rates, NEETs rates and the percentage of young people aged 20 to 39 without a university degree. 3) Finally, among the adult population, we estimated the share of low secondary education attainers and/or lower achievers in literacy and numeracy. We therefore have cross-nationally compared not only the educational levels of the adult population, but also the diffusion of functional illiteracy. Data sources are respectively from: 1) the European Social Survey and Eurostat indicators useful to get the international framework of education levels and illustrative/control variables such as public spending on education; 2) the PIAAC survey on adult skills and 3) OECD-PISA 2018 assessment results for 15-year-old student’s abilities in mathematics and sciences. After a preliminary descriptive analysis, data have been computed via (PCA) Principal Component Analysis and Cluster analysis to graphically project countries cluster-groups distributions in relation to latent dimensions. Emerging results stress out the high diffusion of educational poverty especially among the Italian and Spanish population and the need to strengthening policies against poverty in a multidimensional perspective, so that economic schemes tackling economic poverty could be linked to long-term policies aiming at improving basic social skills and therefore reducing the risk of both educational and economic poverty.File | Dimensione | Formato | |
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