Performance indicator in reading in Uruguay; a multi-level approach from TERCE

Authors

DOI:

https://doi.org/10.35362/rie8413988

Keywords:

multilevel models; factors associated with academic achievement; international large-scale sssessments; TERCE

Abstract

The aim of this study is to identify the factors that influence students' achievement at the end of elementary school in Uruguay. Data from UNESCO’s Third Regional Comparative and Explanatory Study (TERCE) were used to identify the factors associated with school performance in Reading. The relationships between contextual indicators and student proficiency were analyzed through hierarchical linear models (MLH) that consider the effects of the characteristics of schools, teachers, students and their families on proficiency in reading. The analysis confirms the importance of student level factors associated to characteristics such as gender, family background, parents' educational expectations and grade retention. Regarding school-level effects, the institutional factors represented a smaller part of the total variance explained. Overall, the ability of Uruguayan schools to influence learning is considerably limited even after taking account of the school composition and it contextual effects.

 

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References

Albernaz, A., Ferreira, F.H.G. y Franco, C. (2002). Qualidade e equidade na educação fundamental brasileira. Rio de Janeiro: PUC-RIO, (Texto para discussão, n. 455).

Andrade, R. J.; Soares, J. F. (2008). O efeito da escola básica brasileira. Estudos em avaliação educacional, 379-406.

ANEP (2009). Uruguay en el segundo estudio regional comparativo y explicativo (SERCE). Informe nacional. Montevideo: ANEP-CODICEN.

ANEP (2015a). Evaluación Nacional de 6° año en Matemática, Ciencias y Lengua 2013. Primer informe, ANEP, Montevideo.

ANEP (2015b). Proyecto de Presupuesto Período 2015-2019. Tomo I, Exposición de Motivos, Montevideo: ANEP- CODICEN.

ANEP (2017). Primer Informe Uruguay en PISA 2015. Montevideo: ANEP-PISA.

Atkinson, A. (2015). Inequality. What can be done? Harvard: Harvard University Press.

Blanco, E. (2008). Factores escolares asociados a los aprendizajes en la educación primaria mexicana: un análisis multinivel. REICE - Revista Electrónica Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 6(1), 1–8.

Blanco, E. (2011). Los límites de la escuela: educación, desigualdad y aprendizajes en México. México, D.F.: El Colegio de México, Centro de Estudios Sociológicos.

Blossfeld, H.-P., Schneider, T. y Doll, J. (2009). Methodological Advantages Of Panel Studies: Designing The New National Educational Panel Study (Neps) In Germany. Journal For Educational Research Online, 1(1), 10–32.

Cardozo, S. (2016). Trayectorias educativas en la educación media PISA-L 2009-2014, INEEd - Grupo de estudios sobre Transiciones Educación-Trabajo (TET), Montevideo.

Castro, R. F. (2009). Fatores associados ao desempenho escolar na 4ª série do ensino fundamental. Em JAC Lordêlo & MV. Dazzani (orgs). Avaliação educacional: desatando e reatando nós [online] (pp.265-295). Salvador: EDUFBA. Disponível em https://bit.ly/2FIDxq4

Carnoy, M. (2015). International test score comparisons and educational policy: A review of the critiques. https://nepc.colorado.edu/publication/international-test-scores.

Cervini, R. (1999). Calidad y equidad en la educación básica de argentina. Factores asociados al logro escolar, 5, 83-citation_lastpage.

Cervini, R. (2002). Desigualdades en el logro académico y reproducción cultural en Argentina. Revista mexicana de investigación educativa, 7(16).

Coleman, J., Campbell, B., Hobson, C., McPartland, J., Mood, A., & Winefield, F. (1966). Equality of Education Opportunity Report: Washington DC: US Government Printing Office.

Cortés, F. y Rubalcava, R. M. (1984). Técnicas estadísticas para el estudio de la desigualdad social. México: El Colegio de México-Flacso.

Cowell, F. A. (1998). Measurement of inequality. Londres: STICERD, London School of Economics.

De Melo, G. (2011). Peer effects identified through social networks. Evidence from Uruguayan schools, Documento de Trabajo, Montevideo: Decon-UdelaR.

Enders, C. K., y Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121–138.

Fernández, T. (2004). Distribución del conocimiento escolar: clases sociales, escuelas y sistema educativo en América Latina. México, D.F: El Colegio de México.

Fernández, T., y Cardozo, S. (2009). Tipos de desigualdad educativa, regímenes de bienestar e Instituciones en América Latina: un abordaje con base en PISA 2009, Páginas de Educación, 4(1), 33-55.

Hanushek, E. A. (2011). The Economic Value Of Higher Teacher Quality. Economics Of Education Review, 30(3), 466-479. https://doi.org/10.1016/J.Econedurev.2010.12.006

Hanushek, E. A. (2013). Economic Growth In Developing Countries: The Role Of Human Capital. Economics Of Education Review, 37, 204–212. https://doi.org/10.1016/J.Econedurev.2013.04.005

Harker, R. y Tymms, R. (2004). The effects of student composition on school outcomes. School Effectiveness and School Improvement, 15(2), 177-199.

Hattie, J. (2002). Classroom composition and peer effects. International Journal of Educational Research, 37 (5), 449-481.

Hox, J.J. (2010). Multilevel Analysis: Techniques and Applications. 2ª ed. New York: Routledge.

INEED (2014). Informe Sobre El Estado De La Educación En Uruguay 2014. Montevideo: Ineed.

INEED (2015). Uruguay En El TERCE: Resultados y Prospecciones. Montevideo: Ineed.

INEED (2017). Informe Sobre El Estado De La Educación En Uruguay 2015-2016. Montevideo: Ineed.

Kirsch, I., y Braun, H. (2020). Changing times, changing needs: enhancing the utility of international large-scale assessments. Large-scale Assessments in Education, 8(1), 1-24.

Torrecilla, F. J. M., y de Becerra, F. C. (2006). Estudios sobre eficacia escolar en Iberoamérica: 15 buenas investigaciones. Convenio Andrés Bello.

OECD (2013). PISA 2012 Results: What Makes Schools Successful? Resources, Policies and Practices (Volume IV). PISA, OECD Publishing. http://dx.doi.org/10.1787/9789264201156-en

OECD (2016). PISA 2015 Results (Volume I): Excellence and Equity in Education. Paris: PISA, OECD Publishing. http://dx.doi.org/10.1787/9789264266490-en

Raudenbush, S. y Bryk, A. S. (1986). A Hierarchical Model For Studying School Effects Source. American Sociological Association, 59(1), 1–17.

Raudenbush, S. y Bryk, A. (2002). Hierachical Linear Models. Second Edition. Ed. Sage. Thousand Oaks. CA.

Raudenbush, S. W., & Willms, J. (1995). The estimation of school effects. Journal of educational and behavioral statistics, 20(4), 307-335.

Ritzen, J. (2013). International Large-Scale Assessments As Change Agents. In Y. K. Von Davier M., Gonzalez E., Kirsch I. (Org.), The Role Of International Large-Scale Assessments: Perspectives From Technology, Economy, and Educational Research. Dordrecht: Springer. https://doi.org/10.1007/978-94-007-4629-9

Roemer, J. E., & Trannoy, A. (2016). Equality of opportunity: Theory and measurement. Journal of Economic Literature, 54(4), 1288-1332.

Soares, J.F. (2003). Quality And Equity In Brazilian Basic Education: Facts And Possibilities. Seminário iasi de estatística aplicada: estatística na educação e educação em estatística, 9, 2003, Rio De Janeiro. Conferência Convidada: Quality And Equity In Brazilian Basic Education: The Hlm Answers. Rio De Janeiro: IASI.

Soares, J. F. (2004). O efeito da escola no desempenho cognitivo de seus alunos. REICE: Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 2(2), 6.

UNESCO (2016a). Informe De Resultados Del Tercer Estudio Regional Comparativo Y Explicativo. Factores Asociados. Santiago De Chile: UNESCO.

UNESCO (2016b). Informe De Resultados Del Tercer Estudio Regional Comparativo Y Explicativo. Logros De Aprendizaje. Santiago De Chile: UNESCO.

UNESCO (2016c). Reporte Técnico Tercer Estudio Regional Comparativo y Explicativo. TERCE. Santiago de Chile: UNESCO.

Von Davier, M., Gonzalez, E., & Mislevy, R. (2009). What are plausible values and why are they useful. IERI monograph series, 2(1), 9-36..

Von Davier, M., Gonzalez, E., Kirsch, I., y Yamamoto, K. (Orgs.). (2013). The Role Of International Large-Scale Assessments: Perspectives From Technology, Economy, And Educational Research. Dordrecht: Springer Netherlands. Https://Doi.Org/10.1007/978-94-007-4629-9

Wagemaker, H. (2014). International large-scale assessments: From research to policy. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis (pp. 11–36). Boca Raton: CRC Press.

Willms, D. (2006). Learning Divides: Ten Policy questions about the performance and equity of schools and schooling systems. Institute for Statistics, Montreal: UNESCO.

Willms, J. D. (2010). School composition and contextual effects on student outcomes. Teachers College Record.

How to Cite

Silveira Aberastury, A. (2020). Performance indicator in reading in Uruguay; a multi-level approach from TERCE. Iberoamerican Journal of Education, 84(1), 155–176. https://doi.org/10.35362/rie8413988

Published

2020-11-11

Issue

Section

Monographic. New data, new challenges: Ibero-America in the latest assessment