Factors Associated with the Performance of Canary Islands Students in Mathematics, Science and Reading in PISA 2018
Keywords:
Learning, Competences, School effectiveness, Teaching, Assessment
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abstract
The main objective of this study is to identify the factors associated with performance in mathematics, science and reading skills of students from the Canary Islands who participated in PISA 2018. For this purpose, the sample consisted of Canarian students from public secondary schools, who took part in this edition of the report. The multivariate decision tree technique was applied using the CHAID (Chi-squared Automatic Interaction Detector) algorithm for each of the three competencies. The outcome in each competence as the dependent variable, and as independent variables 602 factors extracted from the student, well-being, use of ICT familiarity and educational career questionnaires provided in PISA 2018. The variables associated with the socioeconomic level of the students were eliminated. The results showed the relationship of 30 factors, related to performance, which belong mainly to five different areas: reading activity, ICT familiarity, emotional management, social and environmental awareness and related to school setting. It is considered that the educational implications of this research could allow the organisation of measures and strategies that would improve the performance of Canarian students
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References
Adkins, D. y Brendler, B. M. (2015). Libraries and reading motivation: A review of the Programme for International Student Assessment reading results. IFLA Journal, 41(2), 129-139. https://doi.org/10.1177/0340035215578868
Agasisti, T., Antequera, G. y Delprato, M. (2023). Technological resources, ICT use and school’s efficiency in Latin America-insights from OECD PISA 2018. International Journal of Educational Development, 99, art. 102757. https://doi.org/10.1016/j.ijedudev.2023.102757
Agasisti, T., Avvisati, F., Borgonovi, F. y Longobardi, S. (2021). What school factors are associated with the success of socio-economically disadvantaged students? An empirical investigation using PISA data. Social Indicators Research, 157(2), 749-781. https://doi.org/10.1007/s11205-021-02668-w
Ainley, M. y Ainley, J. (2011). Student engagement with science in early adolescence: The contribution of enjoyment to students’ continuing interest in learning about science. Contemporary Educational Psychology, 36(1), 4-12. https://doi.org/10.1016/j.cedpsych.2010.08.001
Asensio, I., Carpintero, E., Expósito, E. y López, E. (2018). ¿Cuánto oro hay entre la arena? Minería de datos con los resultados de España en PISA 2015. Revista Española de Pedagogía, 76(270), 225-245. https://doi.org/10.22550/REP76-2-2018-02
Cordero, J. M., García, M. A., Manchón, C. y Muñiz, M. A. (2011). La educación medioambiental en España: Una aproximación a partir de los datos de PISA. Estudios Económicos Regionales y Sectoriales, 11(3), 135-156.
Cordero, J. M., Pedraja, F. y Simancas, R. (2015). Factores del éxito escolar en condiciones socioeconómicas desfavorables. Revista de Educación, 370, 172-198. https://doi.org/10.4438/1988-592X-RE-2015-370-302
Cuevas-Cerveró, A. y Vives-Gràcia, J. (2005). La competencia lectora en el estudio PISA. Un análisis desde la alfabetización en información. Anales de Documentación, 8, 51-70.
Cuñat-Roldán, M. y Cuñat-Giménez, R. J. (2022). Las leyes de Educación en España vs resultados de evaluación del informe PISA: Un análisis del periodo 2000-2018. Educatio Siglo XXI, 40(1), 9-30. https://doi.org/10.6018/educatio.431691
Denessen, E., Hornstra, L., van den Bergh, L. y Bijlstra, G. (2022). Implicit measures of teachers' attitudes and stereotypes, and their effects on teacher practice and student outcomes: A review. Learning and Instruction, 78, art. 101437. https://doi.org/10.1016/j.learninstruc.2020.101437
García-Pérez, J., Hidalgo-Hidalgo, M. y Robles-Zurita, A. (2014). Does grade retention affect students' achievement? Some evidence from Spain. Applied Economics, 46(12), 1373-1392. https://doi.org/10.1080/00036846.2013.872761
Gil-Flores, J. y García-Gómez, S. (2017). Importancia de la actuación docente frente a la política educativa regional en la explicación del rendimiento en PISA. Revista de Educación, 378, 52-77. http://doi.org/10.4438/1988-592X-RE-2017-378-361
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
Instituto Nacional de Evaluación Educativa-INEE. (2019). PISA 2018. Programa para la evaluación internacional de los estudiantes. Informe español. Ministerio de Educación y Formación Profesional.
Lee, J. y Stankov, L. (2018). Non-cognitive predictors of academic achievement: Evidence from TIMSS and PISA. Learning and Individual Differences, 65, 50-64. https://doi.org/10.1016/j.lindif.2018.05.009
López Martín, E., Expósito Casas, E., Carpintero Molina, M. E. y Asensio, I. (2018). ¿Qué nos dice PISA sobre la enseñanza y el aprendizaje de las ciencias? Una aproximación a través de árboles de decisión. Revista de Educación, 382, 133-161. https://doi.org/10.4438/1988-592X-RE-2018-382-395
Martínez-Abad, F., Gamazo, A. y Rodríguez-Conde, M. J. (2020). Educational data mining: Identification of factors associated with school effectiveness in PISA assessment. Studies in Educational Evaluation, 66, art. 100875. https://doi.org/10.1016/j.stueduc.2020.100875
Navarro-Martínez, O. y Peña-Acuña, B. (2022). Technology usage and academic performance in the PISA 2018 report. Journal of New Approaches in Educational Research, 11(1), 130-145. https://doi.org/10.7821/naer.2022.1.735
Odell, B., Cutumisu, M. y Gierl, M. (2020). A scoping review of the relationship between students’ ICT and performance in mathematics and science in the PISA data. Social Psychology of Education, 23(6), 1449-1481. https://doi.org/10.1007/s11218-020-09591-x
Organisation for Economic Co-operation and Development-OECD. (2019). PISA 2018: What student knows and can do. OECD Publishing. https://doi.org/10.1787/5f07c754-en
Pekrun, R., Murayama, K., Marsh, H. W., Goetz, T. y Frenzel, A. C. (2019). Happy fish in little ponds: Testing a reference group model of achievement and emotion. Journal of Personality and Social Psychology, 117(1), 166-185. https://doi.org/10.1037/pspp0000230
Rodríguez-García, A. y Arias-Gago, A. R. (2021). Uso metodológico docente y rendimiento lector del alumnado: Análisis fundamentado en PISA lectura 2018. Revista Interuniversitaria de Formación del Profesorado, 24(3), 149-165. https://doi.org/10.6018/reifop.469921
Rogiers, A., Van Keer, H. y Merchie, E. (2020). The profile of the skilled reader: An investigation into the role of reading enjoyment and student characteristics. International Journal of Educational Research, 99, art. 101512. https://doi.org/10.1016/j.ijer.2019.101512
Sorby, S. A. y Panther, G. C. (2020). Is the key to better PISA math scores improving spatial skills? Mathematics Education Research Journal, 32(2), 213-233. https://doi.org/10.1007/s13394-020-00328-9
Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417-453. https://doi.org/10.3102/00346543075003417
Wigfield, A., Gladstone, J. R. y Turci, L. (2016). Beyond cognition: Reading motivation and reading comprehension. Child Development Perspectives, 10(3), 190-195. https://doi.org/10.1111/cdep.12184
Wijaya, A., van den Heuvel-Panhuizen, M., Doorman, M. y Robitzsch, A. (2014). Difficulties in solving context-based PISA mathematics tasks: An analysis of students' errors. The Mathematics Enthusiast, 11(3), 555-584.