Factores asociados al rendimiento académico de los estudiantes latinoamericanosUna revisión sistemática

  1. Tene-Tenempaguay, Tannya 1
  2. Martínez-Abad, Fernando 1
  3. Hernández-Ramos, Juan Pablo 1
  1. 1 Universidad de Salamanca
    info
    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

    Geographic location of the organization Universidad de Salamanca
Journal:
Profesorado: Revista de curriculum y formación del profesorado

ISSN: 1989-6395,  1138-414X

Year of publication: 2024

Volume: 28

Issue: 3

Pages: 215-236

Type: Article

DOI: 10.30827/PROFESORADO.V28I3.29626 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Profesorado: Revista de curriculum y formación del profesorado

Sustainable development goals

info

SDG classification obtained using Aurora SDG artificial intelligence model.

Abstract

Large-scale international assessments provide valuable databases for analyzing factors associated with students´ academic achievement. This systematic review focuses on students from Latin American countries. It aims to establish a framework on the type of research and statistical techniques most commonly applied, delving deeper into the detected factors associated with academic achievement and school success. The PRISMA reference framework was followed. From the 124 studies initially identified, 28 papers published between 2006 and 2023 were selected. The main results highlight that the empirical studies are mainly focused on South American countries and that the areas of greatest interest are Mathematics and Reading. The statistical techniques most employed are multilevel models and descriptive analysis. Contextual issues are observed as the main factors influencing performance, highlighting gender and family socioeconomic level. More research is needed on educational factors associated with academic achievement and school success in Latin America based on large-scale international educational assessments.

Bibliographic References

  • Berlanga-Silvente, V. y Vilá-Baños, R. (2014). Cómo obtener un Modelo de Regresión Logística Binaria con SPSS. REIRE, Revista d´Innovació i Recerca en Educació, 7 (2), 105-118. https://doi.org/10.1344/reire2014.7.2727
  • Botello-Peñaloza, H. (2016). Desempeño académico y tamaño del salón de clase: evidencia de la prueba PISA 2012. Actualidades Pedagógicas, (67), 97-112. https://doi.org/10.19052/ap.3139
  • Brunner, J. y Ganga-Contreras, F. (2017). Vulnerabilidad educacional en América Latina: Una aproximación desde la sociología de la educación con foco en la educación temprana. Opción, 33(84), 12-37. https://www.redalyc.org/journal/310/31054991002/html/
  • Cervini, R. (2015). Child Labor and School Achievement in Latin America -The SERCE data. Revista electrónica de investigación educativa, 17(2), 130-146. http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1607-40412015000200010&lng=es&tlng=es
  • Cervini, R., Dari, N. y Quiroz, S. (2016). Estructura familiar, tamaño de la familia y el rendimiento en matemática y lectura: Análisis comparativo entre países de América Latina. Perfiles Educativos, 38(151), 12-31. https://doi.org/10.22201/iisue.24486167e.2016.151.54884
  • Cervini, R., Dari, N. y Quiroz, S. (2015). Género y rendimiento escolar en América Latina. Los datos del SERCE en Matemática y Lectura. Revista Iberoamericana de Educación, 68, 99-116. https://doi.org/10.35362/rie680206
  • Chaparro Caso López, A. y 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
  • Delprato, M., Akyeampong, K. y Dunne, M. (2017). The impact of bullying on students’ learning in Latin America: A matching approach for 15 countries. International Journal of Educational Development, 52, 37-57. https://doi.org/10.1016/j.ijedudev.2016.10.002
  • Delprato, M. (2019). Parental education expectations and achievement for Indigenous students in Latin America: Evidence from TERCE learning survey. International Journal of Educational Development, 65, 10-25. https://doi.org/10.1016/j.ijedudev.2018.12.004
  • Delprato, M. y Akyeampong, K. (2019). The effect of working on students’ learning in Latin America: Evidence from the learning survey TERCE. International Journal of Educational Development, 70. https://doi.org/10.1016/j.ijedudev.2019.102086
  • De Jorge-Moreno, J. (2016). Factores explicativos del rendimiento escolar en Latinoamérica con datos PISA 2009. Revista de Métodos cuantitativos para la Economía y la Empresa, (22), 216-229. https://doi.org/10.46661/revmetodoscuanteconempresa.2348
  • Dip, J. A. y Gamboa, L. (2019). The heterogeneity of the effects of preschool education on cognitive outcomes in Latin America. Cepal Review, (128), 71-89.
  • https://hdl.handle.net/11362/44980
  • Fernández, S., Woitschach, P., Alvarez-Díaz, M. y Fernandez-Alonso, R. (2018). Analysis of the opportunity to learn in the TERCE study of UNESCO. Rie-Revista De Investigación Educativa, 36(2), 509-528. https://doi.org/10.6018/rie.36.2.307831
  • Fernández-Alonso, R., Woitschach, P., Álvarez-Díaz, M., González-López, A., Cuesta, M. y Muñiz, J. (2019). Homework and Academic Achievement in Latin America: A multilevel Approach. Frontiers in Psychology, 10(95). https://doi.org/10.3389/fpsyg.2019.00095
  • Ferreira, C. y De Morán, M. (2011). La responsabilidad social corporativa (RSC) en la bases de datos SCOPUS y WOS (Estudio bibliométrico). EDICIC Educación e Investigación en Ciencia de la Información de Iberoamérica y el Caribe, 1(4), 141-160. https://dialnet.unirioja.es/servlet/articulo?codigo=3866973
  • Gigena, M., Vera, M., Giuliodori, R. y Gertel, H. (2011). Exploring the gap difference in 2000-2009 PISA test scores between Argentina, Chile and México. Regional and Sectoral Economic Studies, 11(3), 85-96. https://www.usc.es/economet/reviews/eers1135.pdf
  • Giménez, G., Ciobanu, D. y Barrado, B. (2021). A Proposal of Spatial Measurement of Peer Effect through Socioeconomic Indices and Unsatisfied Basic Needs. Economies, 9(2), 72. https://doi.org/10.3390/economies9020072
  • Giménez, G., Martín-Oro, Á. y Sanaú, J. (2018). The effect of districts’ social development on student performance. Studies in Educational Evaluation, 58, 80-96. https://doi.org/10.1016/j.stueduc.2018.05.009
  • Giménez, G. y Barrado, B. (2020). Exposure to crime and academic achievement: A case study for Costa Rica using PISA data. Studies in Educational Evaluation, 65. https://doi.org/10.1016/j.stueduc.2020.100867
  • Hopfenbeck, T. N., Lenkeit, J., El Masri, Y., Cantrell, K., Ryan, J. y Baird, J. A. (2018). Lessons Learned from PISA: A Systematic Review of Peer-Reviewed Articles on the Programme for International Student Assessment. Scandinavian Journal of Educational Research, 62(3), 333-353. https://doi.org/10.1080/00313831.2016.1258726
  • Izaguirre, A. y Di Capua, L. (2020). Exploring peer effects in education in Latin America and the Caribbean. Research in Economics, 74(1), 73-86. https://doi.org/10.1016/j.rie.2020.02.001
  • Krüger, N. (2020). Efectos Compañero en Contextos Escolares Altamente Segregados. REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 18(4), 171-196. https://doi.org/10.15366/reice2020.18.4.007
  • Leones, M., Baruzzi, G., Scorzo, P. y Rivas, N. (2016). Un análisis de los resultados del Segundo y Tercero Estudio Regional Comparativo y Explicativo: El caso Argentino-SERCE 2006 y TERCE 2013. REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 14(4), 135-155. https://doi.org/10.15366/reice2016.14.4.007
  • Liu, J., Peng, P., Zhao, B. y Luo, L. (2022). Socioeconomic Status and Academic Achievement in Primary and Secondary Education: a Meta-analytic Review. Educational Psychology Review, 34, 2867–2896. https://doi.org/10.1007/s10648-022-09689-y
  • Marteleto, L. y Andrade, F. (2014). The educational achievement of Brazilian Adolescents: Cultural Capital and the Interaction between Families and Schools. Sociology of Education, 87(1), 16-35. https://doi.org/10.1177/0038040713494223
  • Miranda, S. y Treviño, E. (2020). Use of TERCE-UNESCO to report the education practice; factors that affect learning in Science In Chile and Paraguay. Revista Iberoamericana De Educación, 84(1), 135-156. https://doi.org/10.35362/rie8414025
  • Murillo, F.J. y Martínez-Garrido, C. (2014). Homework and primary-school students’ academic achievement in Latin America. International Review of Education, 60, 661-681. https://doi.org/10.1007/s11159-014-9440-2
  • Murillo, F.J., Román, M. y Atrio, S. (2016). Math teaching resources in Latin American primary classrooms: Availability and impact on student learning. Education Policy Analysis Archives, 24(67). https://doi.org/10.14507/epaa.24.2354
  • Murillo, F.J. y Román, M. (2011). The School or the Cradle? Evidences of its Contribution to Students’ Performance in Latin America. Multilevel Study about the estimate of School Effects. Profesorado, Revista De Currículum Y Formación Del Profesorado, 15(3), 27-50. https://revistaseug.ugr.es/index.php/profesorado/article/view/20407
  • Organización para la Cooperación y el Desarrollo Económico (OCDE). (2017). Activos con América Latina y el Caribe. OCDE. https://acortar.link/VEyEVd
  • Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tezlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J., Grimshaw, J., Hróbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., McGuinness, L., Stewart, L., Thomas, J., Tricco, A., Welch, V., Whiting, P. y Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Revista Española de Cardiología, 74(9), 790-799. https://doi.org/10.1016/j.recesp.2021.06.016
  • Post, D. (2018). Incidencia del trabajo infantil en el logro académico de alumnos de sexto grado: Hallazgos del TERCE. Archivos Analíticos de Políticas Educativas, 26(75). http://dx.doi.org/10.14507/epaa.26.2988
  • Rubio, M. y Berlanga, V. (2012). Cómo aplicar las pruebas paramétricas bivariadas t de Student y ANOVA en SPSS. Caso práctico. REIRE, Revista d’Innovació i Recerca en Educació, 5(2), 83-100. https://diposit.ub.edu/dspace/bitstream/2445/45286/1/612532.pdf
  • Ruiz, M., Pardo, A. y San Martín, R. (2010). Modelos de ecuaciones estructurales. Papeles del psicólogo, 31(1), 34-45. https://www.papelesdelpsicologo.es/pdf/1794.pdf
  • Treviño, E., Valdés, H., Castro, M., Costilla, R., Pardo. C. y Donoso Rivas, F. (2010). Factores asociados al logro cognitivo de los estudiantes en América Latina y el Caribe. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000186769
  • Vaillant, D., Rodríguez-Zidán, E. y Zorrilla-Salgador, J. P. (2019). Incidence of the age of access to Information and Communications Technology and the use of the Internet in science learning. Educação & Sociedade, 40. https://doi.org/10.1590/es0101-73302019199206
  • Wang, X.S., Perry, L.B., Malpique, A. y Ide, T. (2023). Factors predicting mathematics achievement in PISA: a systematic review. Large-scale Assessments in Education, 11(1). https://doi.org/10.1186/s40536-023-00174-8