Análisis del rendimiento escolar en el sistema educativo peruano
DOI:
https://doi.org/10.57063/ricay.v2i3.54Keywords:
Reading comprehension, mathematics, achievement levels, regular basic educationAbstract
This paper evaluates the effect of variables such as student gender, educational institution, the type of educational institution and the management of the educational institution, on the probabilities of achievement in reading comprehension and mathematics in students in the second grade of primary school in the Peruvian educational system, using the methodology of ordered logit models, the data correspond to 541,422 students who took the Censal Evaluation of Students (ECE, 2016), which was carried out in the 24 departments and Metropolitan Lima. The results showed that female students had higher levels of achievement in reading comprehension, while male students had higher levels of achievement in mathematics. On the other hand, students in non-state schools perform better in reading comprehension and students in state schools perform better in mathematics. On the other hand, students in multi-teacher schools have higher levels of achievement in reading comprehension and mathematics. It is also observed that, despite improvements in educational achievement in recent years, gaps persist between urban and rural areas, with urban students showing higher levels of achievement in reading comprehension and mathematics.
References
Asencios, R. (setiembre de 2016). Rendimiento escolar en el Perú: análisis secuencial de los resultados de la Evaluación Censal de los Estudiantes. (Documento de Trabajo 2016-005). Lima: Banco Central de Reserva del Perú‒BCRP. Recuperado de https://www.bcrp.gob.pe/docs/Publicaciones/Documentos-de-Trabajo/2016/documento-de-trabajo-05-2016.pdf
Cameron, A., & Trivedi, P. (2005). Microeconometrics Methods and Applications. (1.ª ed.). Nueva York, Estados Unidos: Universidad de Cambridge. DOI: https://doi.org/10.1017/CBO9780511811241
Canquiz-Rincón, L., Mayorga-Sulbarán, D., & Sandoval-Fontalvo, C. (2021). Planeación didáctica para el desarrollo de la comprensión lectora. Ocnos, 20 (2), 96-106. https://doi.org/10.18239/ocnos_2021.20.2.2404 DOI: https://doi.org/10.18239/ocnos_2021.20.2.2404
Chaparro Caso López, A. A., & Gamazo, A. (2020). Estudio multinivel sobre las variables explicativas de los resultados de México en PISA 2015. Archivos Analíticos de Políticas Educativas, 28(26). https://doi.org/10.14507/epaa.28.4620 DOI: https://doi.org/10.14507/epaa.28.4620
Chávez, V., Reyes, J., Carrillo, M., & Rodriguez, A. (2020). Diferencias de género en unidades educativas rurales de Ecuador. Revista de Ciencias Sociales (RCS). 26(1), Enero-Marzo 2020, pp. 203-218. https://doi.org/10.31876/rcs.v26i1.31320 DOI: https://doi.org/10.31876/rcs.v26i1.31320
Chica, S., Galvis, D., & Ramírez, A. (2009). Determinantes del rendimiento académico en Colombia. Pruebas ICFES Saber 11°, 2009. Revista Universidad EAFIT, 46(160), 48-72. Recuperado de https://publicaciones.eafit.edu.co/index.php/revista-universidad-eafit/ article/view/754
Coleman, J. et al. (1966). Equality of Educational Opportunity. Washington, D.C.: U.S. Government Printing Office. Recuperado de https://files.eric.ed.gov/fulltext/ED012275.pdf
Gong, X.; Zhang, H. y Yao, H. (2015). The determinants of compulsory education performance of migrant children in Beijing: An analysis of two cohorts. International Journal of Educational Development 45 pp. 1–15. http://dx.doi.org/10.1016/j.ijedudev.2015.09.002 DOI: https://doi.org/10.1016/j.ijedudev.2015.09.002
Lei, H., & Cui, Y. (2016). Effects of academic emotions on achievement among mainland chinese students: A meta-analysis. Social Behavior and Personality an International Journal, 44(9), 1541–1553. https://doi.org/10.2224/sbp.2016.44.9.1541. DOI: https://doi.org/10.2224/sbp.2016.44.9.1541
McDonough, I.; Roychowdhury, P. & Dhamija, G. (2021) " Midiendo la dinámica de la brecha de rendimiento entre estudiantes de escuelas públicas y privadas durante la vida temprana en la India", Revista de Investigación Laboral, Springer, vol. 42 (1), páginas 78-122, marzo. DOI: 10.1007 / s12122-020-09307-2
Mitchell, R. (2018) Rural and remote repair: examinig workforce shortages and soltions withn rural school environments. International Online Journal of Primary Education, vol. 7(2) pp. 26-33. Recuperado de https://files.eric.ed.gov/fulltext/EJ1243616.pdf
Ministerio de Educación‒MINEDU (2015). Resultados de la evaluación Censal de Estudiantes 2014. (ECE 2014). Lima, Perú: Ministerio de Educación.
Ministerio de Educación-MINEDU. (2018b). Reporte técnico de la Evaluación Censal de Estudiantes (ECE2016) 2º grado y 4º grado de primaria (EBRyEIB), 2º grado de secundaria. Oficina de Medición de la Calidad de los Aprendizajes del Ministerio de Educación del Perú.
Miranda, L. (2008). Factores asociados al rendimiento escolar ysus implicaciones para la política educativa del Perú. Análisis de programas, procesos y resultados educativos en el Perú: contribuciones empíricas para el debte. Lima: GRADE, 2008. ISBN 978-9972-615-46-7. GREDE. Grupo de Análisis para el Desarrollo.
Organization For Economic Cooperation And Development-OECD. Trends shaping education spotlight 7: gender equality. Paris, 2015a. Available on: http://www.oecd.org/education/ceri/Spotlight7-GenderEquality.pdf, Access in: 15 Agosto 2021
Organization For Economic Cooperation And Development-OECD. What lies behind gender inequality in education? Paris, 2015b. (PISA in Focus, vol. 49). Available on: http://dx.doi. org/10.1787/5js4xffhhc30-en. Access in: 15 agosto 2021.
Rodríguez D.; Ordoñez R. & Hidalgo M. (2021). Determinantes del rendimiento académico de la educación media en el departamento de Nariño, Colombia. Lecturas de Economía, 94 pp. 87-126. http://doi.org/10.17533/udea.le.n94a341834 DOI: https://doi.org/10.17533/udea.le.n94a341834
Timarán, R.; Caicedo, J.; Hidalgo, A. Identification of Factors Associated with Academic Performance in Mathematics in the Saber 11th Tests Applying Educational Data Mining. 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Industry, Innovation, And Infrastructure for Sustainable Cities and Communities”, 24-26 July 2019, Jamaica. http://dx.doi.org/10.18687/LACCEI2019.1.1.297 DOI: https://doi.org/10.18687/LACCEI2019.1.1.297
