Incidence of Contextual Variables on School Mathematical Achievement

Ramón García-Perales; Ascensión Palomares-Ruiz

doi:10.29333/iejme/7600

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Ramón García-Perales ¹ ^* , Ascensión Palomares-Ruiz ¹

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¹ University of Castilla-La Mancha (UCLM), SPAIN^* Corresponding Author

Abstract

The study of math achievement is fundamental. Its importance lies in analyzing what variables affect a significant percentage of students is not to reach their basic standards. In this sense, the contextual variables may become decisive. The purpose is to analyze data obtained after administration to a sample of students of an evaluation tool that measures mathematical competence. The data were analyzed from two contextual variables, ownership and environment centres, demonstrating statistically significant differences. The evaluation of the students should develop in all its scope, adequately considering the competences and the contextual elements that may influence their results.

Keywords

competences
math achievement
mathematics education
private and public education
rural and urban education

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

INT ELECT J MATH ED, 2020, Volume 15, Issue 2, Article No: em0578

https://doi.org/10.29333/iejme/7600

Publication date: 25 Jan 2020

Article Views: 1892

Article Downloads: 1119

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References

Arnaiz, P. (2012). Escuelas eficaces e inclusivas: cómo favorecer su desarrollo. Educatio Siglo XXI, 30(1), 25-44.
Beck, F., & Shoffstall, G. (2005). How do rural schools fare under a high stakes testing regime? Journal of Research in Rural Education, 20(14), 1-12.
Blackwell, D., & Mclaughlin, D. (1999). Do Rural Youth Attain Their Educational Goals? Rural Development Perspectives, 13(3), 37-44.
Bustos, A. (2006). Los grupos multigrado de Educación Primaria en Andalucía. Granada: Grupo Editorial Universitario.
Bustos, A. (2008). Docentes de escuela rural. Análisis de su formación y sus actitudes a través de un estudio cuantitativo en Andalucía. Revista de Investigación Educativa, 26(2), 485-520.
Bustos, A. (2011). Investigación y escuela rural: ¿Irreconciliables? Profesorado, Revista de currículum y formación del profesorado, 15(2), 155-170.
Calero, J., Quiroga, A., Escardíbul, J. O., Waisgrais, S., & Mediavilla, M. (2008). Sociedad desigual, ¿educación desigual? Sobre las desigualdades en el sistema educativo español. Madrid: Centro de Investigación y Documentación Educativa (CIDE), Ministerio de Educación, Política Social y Deporte.
Castro, M. (2011). ¿Qué sabemos de la medida de las competencias? Características y problemas psicométricos en la evaluación de competencias. Bordón, 63(1), 109-123.
Choi, A., & Calero, J. (2012). Rendimiento académico y titularidad de centro en España. Profesorado, Revista de currículum y formación del profesorado, 16(3), 31-57.
Choi, A., & Calero, J. (2013). Determinantes del riesgo de fracaso escolar en España en PISA 2009 y propuestas de reforma. Revista de Educación, 362, 562-593. https://doi.org/10.4438/1988-592X-RE-2013-362-242
Cleary, T., & Chen, P. (2009). Self-regulation, motivation and math achievement in middle school: Variations across grade level and math context. Journal of School Psychology, 47(5), 291-314. https://doi.org/10.1016/j.jsp.2009.04.002
Coleman, J., & Hoffer, T. (1987). Public and private high schools. The impact of communities. New York: Basic Books.
Edington, E., & Martellaro, H. (1984). Variables affecting academic achievement in New Mexico schools. Las Cruces: New Mexico Center for Rural Education.
Elosua, P. (2013). Diferencias individuales y autonómicas en el estatus socioeconómico y cultural como predictores en PISA 2009. Revista de Educación, 361, 646-664. https://doi.org/10.4438/1988-592X-RE-2013-361-236
Fernández, M. (2008). Escuela pública y privada en España: La segregación rampante. Profesorado, Revista de currículum y formación del profesorado, 12(2), 1-27.
Fernández-González, N. (2015). PISA como instrumento de legitimación de la reforma de la LOMCE. Bordón, 67(1), 165-178. https://doi.org/10.13042/Bordon.2015.67111
Fertig, M. (2003). Who”s to Blame? The Determinants of German Students. Achievement in the PISA 2000 Study. IZA Discussion Paper Series, 739, 1-18.
Gaviria, A., & Barrientos, J. (2001). Calidad de la educación y rendimiento académico en Bogotá. Coyuntura Social, 24, 111-127.
Guven, B., & Cabakcor, B. O. (2013). Factors influencing mathematical problem-solving achievement of seventh grade Turkish students. Learning and Individual Differences, 23, 131-137. https://doi.org/10.1016/j.lindif.2012.10.003
Hannaway, J., & Talbert, J. (1993). Bringing context into effective school research: Urban-suburban differences. Educational Administration Quarterly, 29, 164-186. https://doi.org/10.1177/0013161X93029002004
Hanushek, E. (1986). The economics of schooling. Journal of Economic Literature, 24, 1141-1177.
Instituto Nacional de Evaluación Educativa. (2008). PISA 2003. Matemáticas. Informe español. Madrid: Ministerio de Educación, Cultura y Deporte.
Instituto Nacional de Evaluación Educativa. (2010a). Evaluación General de Diagnóstico 2009. Educación Primaria. Informe de resultados. Madrid: Ministerio de Educación, Cultura y Deporte.
Instituto Nacional de Evaluación Educativa. (2010b). PISA 2009: Informe Español. Madrid: Ministerio de Educación, Cultura y Deporte.
Instituto Nacional de Evaluación Educativa. (2012). PIRLS-TIMSS 2011: Estudio internacional de progreso en Comprensión Lectora, Matemáticas y Ciencias. Volumen I: Informe Español. Madrid: Ministerio de Educación, Cultura y Deporte.
Instituto Nacional de Evaluación Educativa. (2013). PISA 2012: Informe Español. Volumen I: Resultados y contexto. Madrid: Ministerio de Educación, Cultura y Deporte.
Instituto Nacional de Evaluación Educativa. (2016). TIMSS 2015. Estudio internacional de tendencias en Matemáticas y Ciencias. IEA. Informe español: resultados y contexto. Madrid: Ministerio de Educación, Cultura y Deporte.
Kleinfeld, J., McDiarmid, W., & Hagstrom, D. (1985). Alaska”s small rural high schools: Are they working? Alaska: ISER Report Series No. 57, University of Alaska.
Lassibille, G., & Navarro, M. L. (2004). Manual of economics of education. Theory and practical cases. Madrid: Pirámide.
Llevot, N., & Garreta, J. (2008). Escuela rural y sociedad. Lleida: Servei de Biblioteca i Documentació, Universitat de Lleida.
López, A. (2013). Alineación entre las evaluaciones externas y los estándares académicos: El Caso de la Prueba Saber de Matemáticas en Colombia. Revista Electrónica de Investigación y Evaluación Educativa, 19(2), 1-15. https://doi.org/10.7203/relieve.19.2.3024
López, M. A. (2013). Aprendizaje, competencias y TIC. Aprendizaje basado en competencias. México: Pearson. https://doi.org/10.1174/021037013808200285
Mcewan, P. (2008). Evaluating multigrade school reform in Latin America. Comparative Education, 44(4), 465-483. https://doi.org/10.1080/03050060802481504
Mesa, V., Gómez, P., & Cheah, U. (2013). Influence of international studies of student achievement on mathematics teaching and learning. In A. J. Bishop et al. (Eds.), Third International Handbook of Mathematics Education, 861-900. Dordrecht: Kluwer. https://doi.org/10.1007/978-1-4614-4684-2_27
Meyer, H. D., & Benavot, A. (2013). PISA, power and policy: The emergence of global education governance. Oxford: Symposium Books. https://doi.org/10.15730/books.85
Ministerio de Educación, Cultura y Deporte. (2013). Ley Orgánica 8/2013, de 9 de Diciembre, para la mejora de la calidad educativa (LOMCE)”. Boletín Oficial del Estado, 295, 97858-921. Madrid: Ministerio de Educación, Cultura y Deporte.
Ministerio de Educación, Cultura y Deporte. (2016a). PISA 2015. Informe español. Boletín de Educación, 51, 1-4.
Ministerio de Educación, Cultura y Deporte. (2016b). PISA 2015. Programa para la Evaluación Internacional de los Alumnos. Informe español. Madrid: Secretaría General Técnica, Ministerio de Educación, Cultura y Deporte.
Monk, D., & Haller, E. (1986). Organizational alternatives for small/rural schools: final report to the New York state legislature. New York, NY: Cornell University.
Noell, J. (1982). Public and Catholic schools: A reanalysis of public and private schools. Sociology of Education, 55, 123-132. https://doi.org/10.2307/2112292
Olson, J., Martin, M., & Mullis, I. (2008). TIMSS 2007. Technical report. Chestnut Hill, MA: TIMSS y PIRLS International Study Center, Boston College.
Opdenakker, M. C., & Van Damme, J. V. (2006). Differences between secondary schools: A study about school context, group composition, school practice, and school effects with special attention to public and catholic schools and types of schools. School Effectiveness and School Improvement, 17(1), 87-117. https://doi.org/10.1080/09243450500264457
Organization for Economic Cooperation and Development. (2009). Top of the class. High performers in science in PISA 2006. Paris: PISA, OECD Publishing.
Organization for Economic Cooperation and Development. (2012). Large cities are assets or ballasts for education. PISA IN FOCUS, 17, 1-4.
Organization for Economic Cooperation and Development. (2013). What makes urban schools different? PISA IN FOCUS, 28, 1-4.
Organization for Economic Cooperation and Development. (2015a). How student performance has evolved over time? PISA IN FOCUS, 47, 1-4.
Organization for Economic Cooperation and Development. (2015b). How schools have changed over the last decade? PISA IN FOCUS, 52, 1-4.
Organization for Economic Cooperation and Development. (2016). PISA 2015: Key results. Paris: PISA, OECD Publishing.
Organization for Economic Cooperation and Development. (2019). PISA 2018: Assessment and Analytical Framework. Paris: PISA, OECD Publishing. https://doi.org/10.1787/b25efab8-en
Ramos, R., Duque, J., & Nieto, S. (2012). Un análisis de las diferencias rurales y urbanas en el rendimiento educativo de los estudiantes colombianos a partir de los microdatos de PISA. Bilbao: XXXVIII Reunión de Estudios Regionales de la Asociación Española de Ciencia Regional (AECR).
Roderer, T., & Roebers, C. (2013). Children’s Performance Estimation in Mathematics and Science Tests over a School Year: A Pilot Study. Electronic Journal of Research in Educational Psychology, 11(1), 5-24. https://doi.org/10.25115/ejrep.v11i29.1555
Roscigno, V., & Crowley, M. (2001). Rurality, institutional disadvantage, and achievement/attainment. Rural Sociology, 66(3), 268-293. https://doi.org/10.1111/j.1549-0831.2001.tb00067.x
Sander, W. (1996). Catholic grade schools and academic achievement. The Journal of Human Resources, 31(3), 540-548. https://doi.org/10.1007/978-1-4757-3335-8_2
Santamaría, R. (2014). The rural school in LOMCE: opportunities and threats. Supervisión, 21(33), 1-26.
Santos, M. E. (2007). Quality of education in Argentina: Determinants and distribution using the results of PISA 2000. Bienestar y política social, 3(1), 79-109.
Sicilia, G., & Simancas, R. (2018). Educational equity in Spain: regional comparison from PISA 2015. Madrid: Fundación Ramón Areces and Fundación Europea Sociedad y Educación.
Smith, J., & and Naylor, R. (2005). Schooling effects on subsequent university performance: evidence for the UK university population. Economics of Education Review, 24(5), 549-562. https://doi.org/10.1016/j.econedurev.2004.07.016
Somers, M. A., Mcewan, P., & Willms, D. (2004). How effective are private schools in Latin America? Comparative Education Review, 48(1), 48-69. https://doi.org/10.2307/3542000
Stevans, L., & Sessions, D. (2000). Private/public school choice and student performance revisited. Education Economics, 8(2), 169-184. https://doi.org/10.1080/096452900410730
Torres, J. A., & Castillo, S. (2016). Incidence of educational support policies in the organizational structures of the centers from the perspective of teachers: A study in the province of Jaen. Educación XX1, 19(2), 205-228. https://doi.org/10.5944/educxx1.16462
Vandernberghe, V., & Robin, S. (2004). Evaluating the effectiveness of private education across countries: A comparison of methods. Labour Economics, 11(4), 487-506. https://doi.org/10.1016/s0927-5371(04)00046-6
Wossmann, L. (2010). Families, schools and primary-school learning: evidence for Argentina and Colombia in an international perspective. Applied Economics, 42(21), 2645-2665. https://doi.org/10.1080/00036840801964617
Young, D. J. (1998). Rural and urban differences in student achievement in science and mathematics: A multilevel analysis. School effectiveness and school improvement, 9(4), 386-418. https://doi.org/10.1080/0924345980090403

How to cite this article

APA

García-Perales, R., & Palomares-Ruiz, A. (2020). Incidence of Contextual Variables on School Mathematical Achievement. International Electronic Journal of Mathematics Education, 15(2), em0578. https://doi.org/10.29333/iejme/7600

Vancouver

García-Perales R, Palomares-Ruiz A. Incidence of Contextual Variables on School Mathematical Achievement. INT ELECT J MATH ED. 2020;15(2):em0578. https://doi.org/10.29333/iejme/7600

AMA

García-Perales R, Palomares-Ruiz A. Incidence of Contextual Variables on School Mathematical Achievement. INT ELECT J MATH ED. 2020;15(2), em0578. https://doi.org/10.29333/iejme/7600

Chicago

García-Perales, Ramón, and Ascensión Palomares-Ruiz. "Incidence of Contextual Variables on School Mathematical Achievement". International Electronic Journal of Mathematics Education 2020 15 no. 2 (2020): em0578. https://doi.org/10.29333/iejme/7600

Harvard

García-Perales, R., and Palomares-Ruiz, A. (2020). Incidence of Contextual Variables on School Mathematical Achievement. International Electronic Journal of Mathematics Education, 15(2), em0578. https://doi.org/10.29333/iejme/7600

MLA

García-Perales, Ramón et al. "Incidence of Contextual Variables on School Mathematical Achievement". International Electronic Journal of Mathematics Education, vol. 15, no. 2, 2020, em0578. https://doi.org/10.29333/iejme/7600