International Association of Educators   |  ISSN: 2834-7919   |  e-ISSN: 1554-5210

Original article | International Journal of Progressive Education 2018, Vol. 14(1) 165-176

Multilevel Classification of PISA 2015 Research Participant Countries’ Literacy and These Classes’ Relationship with Information and Communication Technologies

Seher Yalçın

pp. 165 - 176   |  DOI: https://doi.org/10.29329/ijpe.2018.129.12   |  Manu. Number: MANU-1707-31-0001.R1

Published online: February 11, 2018  |   Number of Views: 362  |  Number of Download: 1044


Abstract

In this study, it is aimed to distinguish the reading skills of students participating in PISA 2015 application into multi-level latent classes at the student and country level. Furthermore, it is aimed to examine how the clusters emerged at country-level is predicted by variables as students have the information and communication technology (ICT) resources. The population of this research, which is in a descriptive survey model consists of all students who are aged 15 from 72 countries which participated in the PISA 2015 application. As for sample, it is made up of 519.334 students and 17.908 schools which were chosen randomly for PISA 2015 application from these countries. In analyzing data, a multi-level latent class and three-step analysis were employed. Analyses have shown that having ICT resources at home is the most influential variable on the reading skills of countries. It is determined both in in-country and across countries that there are some differences in ICT resources at home and school. In this context, it may be stated that the equal opportunity in education has not been provided in many countries on international scale.

Keywords: PISA, reading achievement, information and communication technologies, multilevel latent class analysis


How to Cite this Article?

APA 6th edition
Yalcin, S. (2018). Multilevel Classification of PISA 2015 Research Participant Countries’ Literacy and These Classes’ Relationship with Information and Communication Technologies. International Journal of Progressive Education, 14(1), 165-176. doi: 10.29329/ijpe.2018.129.12

Harvard
Yalcin, S. (2018). Multilevel Classification of PISA 2015 Research Participant Countries’ Literacy and These Classes’ Relationship with Information and Communication Technologies. International Journal of Progressive Education, 14(1), pp. 165-176.

Chicago 16th edition
Yalcin, Seher (2018). "Multilevel Classification of PISA 2015 Research Participant Countries’ Literacy and These Classes’ Relationship with Information and Communication Technologies". International Journal of Progressive Education 14 (1):165-176. doi:10.29329/ijpe.2018.129.12.

References
  1. Allen, J., & van der Valden, R. (2012). Skills for the 21st century: Implications for education. Research Centre for Education and the Labour Market, Maastricht.  Retrieved from https://cris.maastrichtuniversity.nl/portal/files/1041352/guid-99b3046c-722d-4c29-878e-52b0ebee50f4-ASSET1.0 [Google Scholar]
  2. Anikó, V. (2016). The relationship between educational inequalities and ict access and use at home. Belvedere Meridionale, 28(1), 5–26. [Google Scholar]
  3. Asparouhov, T., & Muthen, B. (2008). Multilevel mixture models. In G. R. Hancock & K. M. Samuelsen (Ed.), Advances in latent variable mixture models (pp. 27-51). Charlotte, NC: Information Age Publishing, Inc. [Google Scholar]
  4. Bilican Demir, S., & Yıldırım, Ö. (2016). Okulda ve okul dışında bilgi ve iletişim teknolojilerinin kullanımının öğrencilerin PISA 2012 performansıyla ilişkisinin incelenmesi. Kastamonu Eğitim Dergisi, 24(1), 251-262. [Google Scholar]
  5. Borman, G. D., & Dowling, M. (2010). Schools and inequality: A multilevel analysis of coleman’s equality of educational opportunity data. Teachers College Record, 112(5), 1201–1246. [Google Scholar]
  6. Bussière, P., & Gluszynski, T. (2004). The impact of computer use on reading achievement of 15-year-olds. Gatineau, Québec: Learning Policy Directorate, Strategic Policy and Planning, Human Resources and Skills Development Canada. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.494.5476&rep=rep1&type=pdf [Google Scholar]
  7. Eryaman, M. Y. (2006). A hermeneutic approach towards integrating technology into schools: Policy and Practice. In S. Tettegah & R. Hunter (Eds.). Technology: Issues in administration, policy, and applications in K-12 schools. Elsevier Science Publications. [Google Scholar]
  8. Eryaman, M. Y. (2007). Examining the characteristics of literacy practices in a technology-rich sixth grade classroom. The Turkish Online Journal of Educational Technology (TOJET) 6(2), 26-41. [Google Scholar]
  9. Finegold, D., & Notabartolo, A. (2010). 21st-century competencies and their impact: An interdisciplinary literature review. Research on 21st Century Competencies, National Research Council, 1–50. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/cbdv.200490137/epdf [Google Scholar]
  10. Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Gebhardt, E. (2014). International computer and information literacy study preparing for life in a digital age, the IEA international computer and information literacy study international report. Cham: Springer. Retrieved from https://link.springer.com/content/pdf/10.1007%2F978-3-319-14222-7.pdf  [Google Scholar]
  11. Freddano, M., & Diana, P. (2012). The role of ICT to raise students’ achievement in Italian technical and professional schools. Problems of education in the 21stcentury, 49, 15-26. [Google Scholar]
  12. Fuchs, T., & Wößmann, L. (2005). Computers and student learning: Bivariate and multivariate evidence on the availability and use of computers at home and at school. Ifo Working Paper Series, No: 8. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.618.3222&rep=rep1&type=pdf  [Google Scholar]
  13. Gamoran, A., & Long, D. A. (2006). Equality of educational opportunity: A 40-year retrospective (WCER Working Paper No. 2006-9). Madison: University of Wisconsin–Madison, Wisconsin Center for Education Research. Retrieved from http://www.wcer.wisc.edu/publications/workingPapers/papers.php [Google Scholar]
  14. Gürsakal, S. (2012). PISA 2009 öğrenci başarı düzeylerini etkileyen faktörlerin değerlendirilmesi. Suleyman Demirel University The Journal of Faculty of Economics and Administrative Sciences, 17(1), 441-452. [Google Scholar]
  15. Holmlund, H. (2016). Education and equality of opportunity: What have we learned from educational reforms? The Institute for Evaluation of Labour Market and Education Policy, Working Series, 5. Retrieved from http://www.ifau.se/globalassets/pdf/se/2016/wp2016-05-education-and-equality-of-opportunity.pdf  [Google Scholar]
  16. Jackson, L. A., von Eye, A., Witt, E. A., Zhao, Y., & Fitzgerald, H. E. (2011). A longitudinal study of the effects of internet use and videogame playing on academic performance and the roles of gender, race and income in these relationships. Computers in Human Behavior, 27, 228–239. [Google Scholar]
  17. Lukočienė, O., Varriale, R., & Vermunt, J. K. (2010). The simultaneous decision(s) about the number of lower and higher-level classes in multilevel latent class analysis. Sociological Methodology, 40(1), 247-283. doi: 10.1111/j.1467-9531.2010.01231.x [Google Scholar] [Crossref] 
  18. Organisation for Economic Co-operation and Development (OECD). (2011). PISA 2009 results: Students on line: Digital technologies and performance (volume VI). OECD Publishing, Paris. Retrieved from http://dx.doi.org/10.1787/9789264112995-en  [Google Scholar]
  19. Organisation for Economic Co-operation and Development (OECD). (2013). PISA 2015 draft reading literacy framework. OECD Publishing, Paris. Retrieved from https://www.oecd.org/pisa/pisaproducts/Draft%20PISA%202015%20Reading%20Framework%20.pdf  [Google Scholar]
  20. Organisation for Economic Co-operation and Development (OECD). (2014). PISA 2012 results in focus. OECD Publishing, Paris. Retrieved from https://www.oecd.org/pisa/keyfindings/pisa-2012-results-overview.pdf  [Google Scholar]
  21. Organisation for Economic Co-operation and Development (OECD). (2015). Students, computers and learning: Making the connection, PISA. OECD Publishing, Paris. Retrieved from http://dx.doi.org/10.1787/9789264239555-en [Google Scholar]
  22. Organisation for Economic Co-operation and Development (OECD). (2016a). PISA 2015 results in focus. OECD Publishing, Paris. Retrieved from https://www.oecd.org/pisa/pisa-2015-results-in-focus.pdf  [Google Scholar]
  23. Organisation for Economic Co-operation and Development (OECD). (2016b). PISA 2015 technical report. OECD Publishing, Paris. Retrieved from https://www.oecd.org/pisa/sitedocument/PISA-2015-Technical-Report-Chapter-18-Computer-Platform.pdf [Google Scholar]
  24. Schütz, G., Ursprung, H. W., & Woessmann, L. (2005). Education policy and equality of opportunity. IZA Discussion paper No. 1906. Retrieved from http://ftp.iza.org/dp1906.pdf  [Google Scholar]
  25. UNESCO. (2015). Education for all 2000-2015: Achievements and challenges. The United Nations Educational, Scientific and Cultural Organization, Paris. Retrieved from  http://unesdoc.unesco.org/images/0023/002322/232205e.pdf  [Google Scholar]
  26. Vermunt, J. K. (2003). Multilevel latent class models. Sociological Methodology, 33(1), 213-239. doi: 10.1111/j.0081-1750.2003.t01- 1-00131.x  [Google Scholar] [Crossref] 
  27. Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450-469. [Google Scholar]
  28. Vermunt, J. K., & Madigson, J. (2004). Local independence. In A. B. M. S. Lewis Beck (Ed.), Encyclopedia of social sciences research methods (pp. 732-733). Thousand Oaks: Sage Publications.  [Google Scholar]
  29. Vermunt, J. K., & Magidson, J. (2013a). Latent GOLD 5.0 upgrade manual. Belmont, MA: Statistical Innovations Inc.  [Google Scholar]
  30. Vermunt, J. K., & Magidson, J. (2013b). LG-syntax user’s guide: Manual for latent GOLD 5.0 syntax module. Belmont, MA: Statistical Innovations Inc. [Google Scholar]