Does familiarity with tics influence performance in mathematics and science? The case of Spain
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This paper analyzes, for the case of Spain, the influence of ICT familiarization on the acquisition of mathematicsand science competencies. The analyzed participants correspond to 35943 15-year-old students who took the PISA test in 2018. The data are analyzed through a Multiple Correspondence Analysis and the main results allow us to conclude that, in terms of familiarization (possession and/or use) with ICT, more than 50% of the students declare having and using the analyzed devices, and that this proportion is even higher when it comes to Internet and Cellular with Internet (more than 95%). The devices with the least use are Cellular without internet and ebook reader. Regarding the association between familiarity with ICTs and the acquisition of competencies, the following results are obtained: 1. low levels of competencies are associated with no familiarity with ICTs; 2. medium levels are associated with having/using the Internet, Laptop, Cell phone with Internet and USB disk; and 3. high levels areas sociated with having and using a Computer, Tabletand Printer, in addition to the devicesas sociated with the medium level.
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References
Antonijevi, R. (2007). Usage ofcomputersand caculatorsand student sachievement: Resultsfroma TIMSS 2003. 11.
Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT Impact Report: A review of studies of ICT impact on schools in Europe. European Schoolnet. https://cupdf.com/document/the-ict-impact-report-commonwealth-of-the-ict-impact-report-a-review-of-studies.html
Ben Youssef, A., Dahmani, M., & Omrani, N. (2015). Information technologies, students’ e-skills and diversity of learning process. Education and Information Technologies, 20(1), 141-159. https://doi.org/10.1007/s10639-013-9272-x
Benzecri, J.-P. (1992). Correspondence Analysis Handbook. New York: Marcel Dekker, ISBN: 0-8247-8437-5 Boletín oficial del Estado (BOE), 189, C 019/20-SP 50047 (2020). https://www.boe.es/boe/dias/2020/07/10/pdfs/BOE-A-2020-7682.pdf
Cotik, V., & Monteverde, H. (2016). Evolución de la enseñanza de la informática y las TIC en la Escuela Media en Argentina en los últimos 35 años. Virtualidad, Educación y Ciencia, 7(12), 11-33.
Formichella, M. M., & Alderete, M. V. (2018). TIC en la escuela y rendimiento educativo: El efecto mediador del uso de las TIC en el hogar. Cuadernos de Investigación Educativa, 9(1), 75-93. https://doi.org/10.18861/cied.2018.9.1.2822
Formichella, M. M., & Alderete, M. V. (2020). El efecto de las TIC en el desempeño educativo: El análisis de la comprensión lectora: THE. Semestre Económico, 23(54), 181-199. https://doi.org/10.22395/seec.v23n54a9
García-Martín, S., & Cantón-Mayo, I. (2019). Use of technologies and academic performance in adolescent students. Comunicar, 27(59), 73-81. https://doi.org/10.3916/C59-2019-07
Greenacre, M. (2009). Power transformations in correspondence analysis. Computational Statistics & Data Analysis, 53(8), 3107-3116. https://doi.org/10.1016/j.csda.2008.09.001
Greenacre, M. (2017). Correspondence analysis in practice (Third edition). CRC Press, Taylor & Francis Group.
Greenacre, M., & Blasius, J. (2006). Multiple correspondence analysis and related methods. Chapman & Hall/CRC.
Hamburg, I., & Lütgen, G. (2019). Digital Divide, Digital Inclusion and Inclusive Education. Advances in Social Sciences Research Journal, 6(4), 193-206. https://doi.org/10.14738/assrj.64.6457
Junco, R. (2015). Student class standing, Facebook use, and academic performance. Journal of Applied Developmental Psychology, 36, 18-29. https://doi.org/10.1016/j.appdev.2014.11.001
Kassambara, A., & Mundt, F. (2020). factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R package version 1.0.7. https://CRAN.R-project.org/package=factoextra
Le, S., Josse, J., Husson, F. (2008). FactoMineR: An R Package for Multivariate Analysis. Journal of Statistical Software, 25(1), 1-18. 10.18637/jss.v025.i01
Lepp, A., Barkley, J. E., & Karpinski, A. C. (2015). The Relationship Between Cell Phone Use and Academic Performance in a Sample of U.S. College Students. SAGE Open, 5(1), 2158244015573169. https://doi.org/10.1177/2158244015573169
Noshahr, R. B., Talebi, B., & Mojallal, M. (2014). The Relationship Between Use of Cell-Phone with Academic achievement in female Students. Applied Mathematics in Engineering, Management and Technology, 2, 5.
OECD. (2020). PISA 2018 Results (Volume VI): Are Students Ready to Thrive in an Interconnected World? OECD.
https://doi.org/10.1787/d5f68679-en
Orozco Torres, L. M., López Cortés, E., & Torres Santiago, G. J. (2019). El uso de las tecnologías de la información en estudiantes de nivel bachillerato de comunidades en desarrollo / The Use of Information Technologies in High School Students at Developing Communities. RIDE Revista Iberoamericana para la Investigación y el Desarrollo Educativo, 9(18), 392-411. https://doi.org/10.23913/ride.v9i18.429
Plan Ceibal. (2007). Plan Ceibal—Sobre Nosotros. https://www.ceibal.edu.uy/es/institucional
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Spiezia, V. (2010). Does Computer Use Increase Educational Achievements? Student-level Evidence from PISA. OECD Journal: Economic Studies, 2010(1), 1-22. https://doi.org/10.1787/eco_studies-2010-5km33scwlvkf
Torres-Díaz, J. -C., Duart, J. -M., Gómez-Alvarado, H. -F., Marín-Gutiérrez, I., & Segarra-Faggioni, V. (2016). Internet use and academic success in university students. Comunicar, 24(48), 61-70. https://doi.org/10.3916/c48-2016-06
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
Wickham, H., François, R., Henry, L., Müller, K. (2022). dplyr: A Grammar of Data Manipulation. R package version 1.0.8. https://CRAN.R-project.org/package=dplyr
Wittwer, J., & Senkbeil, M. (2008). Is students’ computer use at home related to their mathematical performance at school? Computers & Education, 50(4), 1558-1571. https://doi.org/10.1016/j.compedu.2007.03.001