Effects of pedagogy and educational commitment on the academic performance of middle school students

Authors

DOI:

https://doi.org/10.46661/revmetodoscuanteconempresa.2765

Keywords:

multilevel analysis, school environment, family environment, academic performance, economics of education

Abstract

This article studies from the hierarchical linear models, the hypothesis of positive incidence that the variables of pedagogy and educational commitment generate on the academic performance. For this, the scores obtained by 62769 middle school students in the 2012 PISA tests in 12 countries are analyzed. By specifying that educational processes adopt a hierarchical structure defined in two levels: students and schools; the econometric specification used leads to results ostensibly better compared to those generated from a traditional specification. Among the results, we have that the educational performance in six countries is explained in a greater proportion by variables of the family environment and student’s characteristics, while in six it is explained by the school environment. Similarly, the results confirm the research hypothesis formulated in the document: pedagogy and educational commitment have a positive impact on academic performance, therefore, the formulation of programs that encourage such practices within the schools should be part of the educational policy. Finally, it was found that the sex of the student does not provide any explanation that refers to the existence of educational gaps because the results are dissimilar between countries, while the non-repetition and absence from school, the provision of school elements at home, the level of parent training, among other factors, are associated with outstanding results in academic achievement.

Downloads

Download data is not yet available.

Author Biography

Bilver Adrian Astorquiza Bustos, Facultad de Ciencias Contables, Económicas y Administrativas. Universidad de Manizales (Colombia)

Economista, Magister en Economía Aplicada de la Universidad del Valle y estudiante del Ph. D en Economía de la Universidad EAFIT. Miembro de la Asociación de Estudios Latinoamericanos-LASA- Dirección: 050035 Medellín-Colombia.

References

Barrientos, M.J. (2008). Calidad de la educación pública y logro académico en Medellín 2004-2006. Una aproximación por regresión intercuartil. Lecturas de Economía, 68, 121-144.

Becker, G.S. (1962). Irrational behavior and economic theory. Journal of Political Economy, 70(1), 1-13.

Betts, J.R., & Shkolnik, J.L. (2000). The effects of ability grouping on student achievement and resource allocation in secondary schools. Economics of Education Review, 19(1), 1-15.

Bryk, A.S., & Raudenbush, S.W. (1992). Hierarchical linear models for social and behavioral research: Applications and data analysis methods. Newbury Park, CA: SAGE.

Calero, J., & Escardíbul, J.O. (2007). Evaluación de servicios educativos: el rendimiento en los centros públicos y privados medido en PISA-2003. IEB Working Paper 2007/07.

Cano, F. (2006). Factores de logro cognitivo en la escuela primaria colombiana. Estudio realizado sobre una muestra de planteles grados 3o, 5º (1993-1994). Estudios Sobre Eficacia Escolar En Iberoamérica, 15, 33-60.

Casas, A.F., Gamboa, L.F., & Piñeros, L.J. (2002). El efecto escuela en Colombia, 1999-2000. Bogotá, Colombia: Editorial Universidad del Rosario.

Cervini, R. (2004). Nivel y variación de la equidad en la educación media de Argentina. Revista Iberoamericana de Educación, 34(1), 1-18.

Cohen, D., Raudenbush, S., & Ball, D. (2003). Resources, instruction, and research. Educational Evaluation and Policy Analysis, 25(2), 119-142.

Coleman, J. (1968). The concept of equality of educational opportunity. Harvard Educational Review, 38(1), 7-22.

Cordero, J. M., Manchón, C., & Simancas, R. (2012). Análisis de los condicionantes del rendimiento educativo de los alumnos españoles en PISA 2009 mediante técnicas multinivel. Presupuesto y Gasto Público, 67, 71-96.

Correa, J. J. (2004). Determinantes del rendimiento educativo de los estudiantes de secundaria en Cali: un análisis multinivel. Sociedad y Economía, 6, 81-105.

Denison, E. F. (1962). Sources of economic growth in the United States and the alternatives before us. New York, USA: Committee for Economic Development.

Ermisch, J., & Francesconi, M. (2001). Family matters: Impacts of family background on educational attainments. Economica, 68(270), 137-156.

Galor, O., & Zeira, J. (1993). Income distribution and macroeconomics. The Review of Economic Studies, 60(1), 35-52.

Gaviria, A., & Barrientos, J. H. (2001). Determinantes de la calidad de la educación en Colombia. Archivos de Economía, 1(159), 88.

Gaviria, J. L., & Castro, M. (2005). Modelos jerárquicos lineales. Serie Cuadernos de Estadística, (29).

Ghouali, H. (2007). El acompañamiento escolar y educativo en Francia. Revista Mexicana de Investigación Educativa, 12(32), 207-242.

Goldstein, H. (1995). Multilevel Statistical Models 2nd edition. Bristol, United Kingdom: Hodder Education.

Hanushek, E. (1971). Teacher characteristics and gains in student achievement: Estimation using micro data. The American Economic Review, 61(2), 280–288.

Hanushek, E. A. (2008). The Economic benefits of improved teacher quality. In Governance and performance of education systems (pp. 107–135). Springer.

Hanushek, E., Markman, J., & Rivkin, S.G. (2003). Does peer ability affect student achievement? Journal of Applied Econometrics, 18(5), 527-544.

Hernández, F., Rosário, P., de Tejada, J.D., Martínez, P., & Ruiz, E. (2006). Promoción del aprendizaje estratégico y competencias de aprendizaje en estudiantes de primero de universidad: evaluación de una intervención. Revista de Investigación Educativa, 24(2), 615-632.

Hox, J. (2002). Quantitative methodology series. Multilevel Analysis Techniques and Applications. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.

Hoxby, C.M. (2000). The effects of class size on student achievement: New evidence from population variation. The Quarterly Journal of Economics, 115(4), 1239-1285.

Jencks, C. (1972). Inequality: A reassessment of the effect of family and schooling in America. New York, USA: Basic Books.

Kane, T.J. (2006). Chapter 23 Public Intervention in Post-Secondary Education. Handbook of the Economics of Education, 2, 1369-1401.

Lazear, E.P. (1980). Family Background and Optimal Schooling Decision. National Bureau of Economic Research Cambridge, Mass., USA.

Lee, J.W., & Barro, R.J. (2001). Schooling quality in a cross-section of countries. Economica, 68(272), 465-488.

López, S.F. (2010). El papel de los incentivos y los docentes en la calidad de la educación oficial de Medellín. Trabajo de Grado No Publicado de Maestría (Meritoria), Universidad de Antioquia, Medellín, Colombia.

Martín, E.L., Asencio, E.N., Ordóñez, X.G., & Romero, S.J. (2009). Estudio de variables determinantes de eficiencia a través de los modelos jerárquicos lineales en la evaluación PISA 2006: el caso de España. Education Policy Analysis Archives, 17(1), 1-24.

Mayer, S.E., & Peterson, P.E. (1999). Earning and learning: How schools matter. Brookings Institution Press.

Núñez, J., Steiner, R., Cadena, X., & Pardo, R. (2002). ¿Cuáles colegios ofrecen mejor educación en Colombia? Archivos de Economía, 193, 1-56.

Organisation for Economic Co-operation and Development (2014). PISA 2012 results: What students know and can do (volume I, revised edition, February 2014): Student performance in mathematics, reading and science. OECD Publishing.

Orrego, M. (2009). Incidencia del entorno escolar en el rendimiento académico de los alumnos de secundaria: comparaciones internacionales con base en las pruebas de PISA 2006. Universidad del Valle. Cali: Facultad de Ciencias Sociales y Económicas. Economía.

Piñeros, L. J., & Rodríguez, A. (1998). Los insumos escolares en la educación secundaria y su efecto sobre el rendimiento académico de los estudiantes: un estudio en Colombia.

Washington, DC: The World Bank/Latin America and the Caribbean Region/Department of Human Development.

Ramos, R., Duque, J.C., & Nieto, S. (2012). Decomposing the rural-urban differential in student achievement in Colombia using PISA microdata. Working Paper 23, 1-28.

Raudenbush, S.W., & Bryk, A.S. (2002). Hierarchical linear models: Applications and data analysis methods (Vol. 1). Sage.

Sarmiento, A., Becerra, L., & González, J. I. (2000). La incidencia del plantel en el logro educativo del alumno y su relación con el nivel socioeconómico. Coyuntura Social, Fedesarrollo, 264, 53-63.

Schultz, T.W. (1961). Investment in human capital. The American Economic Review, 51(1), 1-17.

Snijders, T., & Bosker, R. (1999). Multilevel modeling: An introduction to basic and advanced multilevel modeling. London, United Kingdom: SAGE.

Spady, W.G. (1973). The Impact of School Resources on Students. Review of Research in Education, 1(1), 135-177.

Tobón, D., Posada, H. M., & Ríos, P. (2009). Determinants of the performance of the schools in Medellín in the High-School Graduation-Year Test (ICFES). Cuadernos de Administración, 22(38), 311-333.

Vivas, H. (2008). Educación, background familiar y calidad de los entornos locales en Colombia (Tesis Doctoral). Departamento d’Economia Aplicada, Universitat Autónoma de Barcelona (UAB), Barcelona.

Zambrano, J. C. (2013). Análisis multinivel del rendimiento escolar en matemáticas para cuarto grado de Educación Básica Primaria en Colombia. Sociedad y Economía, 25, 205-235.

Published

2019-10-18

How to Cite

Astorquiza Bustos, B. A. (2019). Effects of pedagogy and educational commitment on the academic performance of middle school students. Journal of Quantitative Methods for Economics and Business Administration, 28, 43–67. https://doi.org/10.46661/revmetodoscuanteconempresa.2765

Issue

Section

Articles