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Render unto primary the things which are primary's: Inherited and fresh learning divides in Italian lower secondary education

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  • De Simone, Gianfranco

Abstract

We employ a pseudo-panel approach to link the achievements of the same cohort of Italian students over two waves of the Trends in International Mathematics and Science Study. As we investigate the determinants of learning divides in math and science at the end of the lower secondary school (grade 8), we are able to tackle cumulative effects of education by controlling for the estimated prior score (grade 4). We find that the gender gap in math observed at grade 8 should actually be ascribed to primary education, while both school levels contribute to the emergence of the girls’ gap in science. In both subject, lower secondary schools are responsible for the largest part of the learning divide due to family background. On the other hand, foreign-origin students show a remarkable recovery at the lower secondary school, once their entry-level of competence is taken into account.

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  • De Simone, Gianfranco, 2013. "Render unto primary the things which are primary's: Inherited and fresh learning divides in Italian lower secondary education," Economics of Education Review, Elsevier, vol. 35(C), pages 12-23.
    • Handle: RePEc:eee:ecoedu:v:35:y:2013:i:c:p:12-23
    DOI: 10.1016/j.econedurev.2013.03.002
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    Cited by:

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    2. Masci, Chiara & Ieva, Francesca & Agasisti, Tommaso & Paganoni, Anna Maria, 2016. "Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students," Socio-Economic Planning Sciences, Elsevier, vol. 54(C), pages 47-57.
    3. Álvaro Choi & María Gil & Mauro Mediavilla & Javier Valbuena, 2016. "Double toil and trouble: grade retention and academic performance," Working Papers 2016/7, Institut d'Economia de Barcelona (IEB).
    4. Boeri, Filippo, 2023. "High-speed broadband, school closures and educational achievements," LSE Research Online Documents on Economics 118120, London School of Economics and Political Science, LSE Library.
    5. Contini, Dalit & Tommaso, Maria Laura Di & Mendolia, Silvia, 2017. "The gender gap in mathematics achievement: Evidence from Italian data," Economics of Education Review, Elsevier, vol. 58(C), pages 32-42.
    6. Schiltz, Fritz & Sestito, Paolo & Agasisti, Tommaso & De Witte, Kristof, 2018. "The added value of more accurate predictions for school rankings," Economics of Education Review, Elsevier, vol. 67(C), pages 207-215.
    7. Tiziana Laureti, 2014. "Life satisfaction and environmental conditions in Italy: a pseudo-panel approach," Discussion Papers 2014/192, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    8. A. Di Liberto, 2013. "Length of stay in the host country and educational achievement of immigrant students: the Italian case," Working Paper CRENoS 201316, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    9. Gómez Soler, Silvia C., 2016. "Educational achievement at schools: Assessing the effect of the civil conflict using a pseudo-panel of schools," International Journal of Educational Development, Elsevier, vol. 49(C), pages 91-106.
    10. Adriana Di Liberto & Fabiano Schivardi & Giovanni Sulis, 2015. "Managerial practices and student performance," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 30(84), pages 683-728.
    11. Pao‐Li Chang & Fali Huang, 2014. "Trade And Divergence In Education Systems," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(4), pages 1251-1280, November.
    12. Dalit Contini & Elisa Grand, 2017. "On Estimating Achievement Dynamic Models from Repeated Cross Sections," Sociological Methods & Research, , vol. 46(4), pages 988-1017, November.
    13. Gerard Ferrer-Esteban & Mauro Mediavilla, 2017. "The more educated, the more engaged? An analysis of social capital and education," Working Papers 2017/13, Institut d'Economia de Barcelona (IEB).
    14. Contini, Dalit, 2014. "Cross-sectional learning assessments: comparability of regression coefficients and validity of difference-in-difference estimation to evaluate institutional effects," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201431, University of Turin.
    15. Bernardi, Martino & Bratti, Massimiliano & De Simone, Gianfranco, 2014. ""I wish I knew ..." - Misperceived Ability, School Track Counseling Services and Performances in Upper Secondary Education," IZA Discussion Papers 7940, Institute of Labor Economics (IZA).
    16. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2018. "Territorial and individual educational inequality: A Capability Approach analysis for Italy," Economic Modelling, Elsevier, vol. 71(C), pages 247-262.
    17. Álvaro Choi & María Gil & Mauro Mediavilla & Javier Valbuena, 2016. "The evolution of educational inequalities in Spain: dynamic evidence from repeated cross-sections," Working Papers 2016/25, Institut d'Economia de Barcelona (IEB).
    18. Di Tommaso, Maria Laura & Contini, Dalit & De Rosa, Dalila & Piazzalunga, Daniela, 2020. "Tackling the Gender Gap in Math with Active Learning Teaching Practices," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202016, University of Turin.
    19. Contini, Dalit & Cugnata, Federica, 2016. "Learning inequalities between primary and secondary school. Difference-in-difference with international assessments," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201607, University of Turin.

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    More about this item

    Keywords

    Cognitive achievement dynamics; Achievement gap; TIMSS; pseudo-panel;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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