Research Article
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Year 2021, , 248 - 264, 01.01.2021
https://doi.org/10.17275/per.21.14.8.1

Abstract

References

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  • Cheema, J. R. (2018). Adolescents' enjoyment of reading as a predictor of reading achievement: new evidence from a cross‐country survey. Journal of Research in Reading, 41(S1), S149-S162. doi: 10.1111/1467-9817.12257.
  • Chi, S., Liu, X., Wang, Z., & Won Han, S. (2018). Moderation of the effects of scientific inquiry activities on low SES students’ PISA 2015 science achievement by school teacher support and disciplinary climate in science classroom across gender. International Journal of Science Education, 40(11), 1284-1304. doi: 10.1080/09500693.2018.1476742.
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  • Demir, İ., Kılıç, S., & Ünal, H. (2010). Effects of students’ and schools’ characteristics on mathematics achievement: findings from PISA 2006. Procedia-Social and Behavioral Sciences, 2(2), 3099-3103. doi: 10.1016/j.sbspro.2010.03.472.
  • Demir, İ., Ünal, H., & Kılıç, S. (2010). The effect of quality of educational resources on mathematics achievement: Turkish case from PISA-2006. Procedia-Social and Behavioral Sciences, 2(2), 1855-1859. doi:10.1016/j.sbspro.2010.03.998.
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  • Doğan, U. C. (2018). Ailenin katılım ve desteği ile ilkokul öğrencilerinin ingilizce dersi akademik başarısı arasındaki ilişkiler. Unpublished Master's thesis, Maltepe University, İstanbul.
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  • Güzeller, C. O., & Akın, A. (2014). Relationship between ICT variables and mathematics achievement based on PISA 2006 database: International evıdence. The Turkish Online Journal of Educational Technology, 13(1), 184-192.
  • Ho, E. S. C. (2010). Family influences on science learning among Hong Kong adolescents: What we learned from PISA. International Journal of Science and Mathematics Education, 8(3), 409-428.
  • Hu, X., Gong, Y., Lai, C., & Leung, F. K. (2018). The relationship between ICT and student literacy in mathematics, reading, and science across 44 countries: A multilevel analysis. Computers & Education, 125(2018), 1-13. doi: 10.1016/j.compedu.2018.05.021.
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Examination of Turkey’s PISA 2018 reading literacy scores within student-level and school-level variables

Year 2021, , 248 - 264, 01.01.2021
https://doi.org/10.17275/per.21.14.8.1

Abstract

The purpose of the current study was to investigate both student-level and school-level factors influencing reading literacy of students in Turkey by using PISA 2018 data. The study focused on reading literacy since the main subject of PISA 2018 was selected as reading literacy. The design of the study is a correlational research examining the relationship between student and school variables and reading literacy. The stratified random sample consisted of 6890 15-year students from 186 different schools. Data coming from PISA 2018 dataset were analysed by Hierarchical Linear Modelling (HLM) at student and school levels. Student-level variables of disciplinary climate in test language lessons, enjoyment of reading, information and community technologies (ICT) competence, parental emotional support, perceived discriminating climate, and perceived cooperation significantly predicted reading literacy, while reading literacy was also predicted by school-level variables of proportion of parents involved in the school, shortage of educational material, student behaviour hindering learning, and teacher behaviour hindering learning. Fifty-seven percent of variance between reading literacy scores of the students were caused by differences between schools. Student-level variables which are disciplinary climate in test language lessons, enjoyment of reading, ICT competence, parental emotional support, perceived discriminating climate, and perceived cooperation significantly predicted reading literacy. On the other hand, school-level variables predicting reading literacy significantly were proportion of parents involved in the school, shortage of educational material, student behaviour hindering learning, and teacher behaviour hindering learning. By considering results of the current study, collaboration between school stakeholders is recommended to increase performance of the students.

References

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  • Åström, M., & Karlsson, K. G. (2007). Using hierarchical linear models to test differences in Swedish results from OECD’s PISA 2003: Integrated and subject-specific science education. Nordic Studies in Science Education, 3(2), 121-131.
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  • Cheema, J. R. (2018). Adolescents' enjoyment of reading as a predictor of reading achievement: new evidence from a cross‐country survey. Journal of Research in Reading, 41(S1), S149-S162. doi: 10.1111/1467-9817.12257.
  • Chi, S., Liu, X., Wang, Z., & Won Han, S. (2018). Moderation of the effects of scientific inquiry activities on low SES students’ PISA 2015 science achievement by school teacher support and disciplinary climate in science classroom across gender. International Journal of Science Education, 40(11), 1284-1304. doi: 10.1080/09500693.2018.1476742.
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  • Demir, İ., & Kılıç, S. (2009). Effects of computer use on students’ mathematics achievement in Turkey. Procedia Social and Behavioral Sciences, 1, 1802–1804. doi: 10.1016/j.sbspro.2009.01.319.
  • Demir, İ., Kılıç, S., & Ünal, H. (2010). Effects of students’ and schools’ characteristics on mathematics achievement: findings from PISA 2006. Procedia-Social and Behavioral Sciences, 2(2), 3099-3103. doi: 10.1016/j.sbspro.2010.03.472.
  • Demir, İ., Ünal, H., & Kılıç, S. (2010). The effect of quality of educational resources on mathematics achievement: Turkish case from PISA-2006. Procedia-Social and Behavioral Sciences, 2(2), 1855-1859. doi:10.1016/j.sbspro.2010.03.998.
  • Dinç, F. (2017). Velilerin eğitime katılım düzeyleri ile öğrenci başarısı arasındaki ilişki. Unpublished Master’s thesis, Pamukkale University, Denizli.
  • Doğan, U. C. (2018). Ailenin katılım ve desteği ile ilkokul öğrencilerinin ingilizce dersi akademik başarısı arasındaki ilişkiler. Unpublished Master's thesis, Maltepe University, İstanbul.
  • Erdem-Kara, B., & Tat, O. (2019). Eğitim kaynaklarının kullanım etkinliği üzerine bir uluslararası karşılaştırma. Eğitimde Kuram ve Uygulama, 15(2), 153-170. doi: 10.17244/eku.478617
  • Gall, G., & Gall, J. P. Borg.(2003). Educational Research: An Introduction. New York, NY: Pearson.
  • Garson, G. D. (2013). Hierarchical Linear Modeling: Guide and Applications. Los Angeles, LA: Sage.
  • Gamazo, A., Martinez-Abad, F., Olmos-Miguelanez, S., & Jose Rodriguez-Conde, M. (2018). Assessment of factors related to school effectiveness in PISA 2015. A multilevel analysis. Revista de Educacion, 379(2018), 56-84. doi: 10.4438/1988-592X-RE-2017-379-369.
  • Gonida, E. N., & Cortina, K. S. (2014). Parental involvement in homework: Relations with parent and student achievement‐related motivational beliefs and achievement. British Journal of Educational Psychology, 84(3), 376-396.
  • Gümüş, S., & Atalmış, E. H. (2011). Exploring the relationshıp between purpose of computer usage and reading skills of Turkish students: Evidence from PISA 2006. The Turkish Online Journal of Educational Technology, 10(3), 129-140.
  • Güzeller, C. O., & Akın, A. (2014). Relationship between ICT variables and mathematics achievement based on PISA 2006 database: International evıdence. The Turkish Online Journal of Educational Technology, 13(1), 184-192.
  • Ho, E. S. C. (2010). Family influences on science learning among Hong Kong adolescents: What we learned from PISA. International Journal of Science and Mathematics Education, 8(3), 409-428.
  • Hu, X., Gong, Y., Lai, C., & Leung, F. K. (2018). The relationship between ICT and student literacy in mathematics, reading, and science across 44 countries: A multilevel analysis. Computers & Education, 125(2018), 1-13. doi: 10.1016/j.compedu.2018.05.021.
  • Huang, H., & Sebastian, J. (2015). The role of schools in bridging within-school achievement gaps based on socioeconomic status: a cross-national comparative study. Compare: A Journal of Comparative and International Education, 45(4), 501-525. doi: 10.1080/03057925.2014.905103.
  • Hwang, J., Choi, K. M., Bae, Y., & Shin, D. H. (2018). Do Teachers’ Instructional Practices Moderate Equity in Mathematical and Scientific Literacy?: an Investigation of the PISA 2012 and 2015. International Journal of Science and Mathematics Education, 16(1), 25-45. doi: 10.1007/s10763-018-9909-8.
  • İş Güzel, Ç. (2014). Uluslararası öğrenci değerlendirme programı’nda (PISA 2003) Türk öğencilerin öğrenci ve okula ilişkin etkenlerin ve etkileşimlerinin matematik okuryazarlığına etkisi. Akdeniz Eğitim Araştırmaları Dergisi, 15, 11-30.
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  • Liu, H., Van Damme, J., Gielen, S., & Van Den Noortgate, W. (2015). School processes mediate school compositional effects: model specification and estimation. British Educational Research Journal, 41(3), 423-447. doi: 10.1002/berj.3147.
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  • Oliver, M., McConney, A., & Woods-McConney, A. (2019). The efficacy of Inquiry-Based instruction in science: A comparative analysis of six countries using PISA 2015. Research in Science Education, 1-22. doi: 10.1007/s11165-019-09901-0.
  • Organization for Economic Cooperation and Development. (2017). Education Policy Outlook: Turkey.
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There are 63 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Articles
Authors

Hasan Yücel Ertem 0000-0001-9058-641X

Publication Date January 1, 2021
Acceptance Date September 13, 2020
Published in Issue Year 2021

Cite

APA Ertem, H. Y. (2021). Examination of Turkey’s PISA 2018 reading literacy scores within student-level and school-level variables. Participatory Educational Research, 8(1), 248-264. https://doi.org/10.17275/per.21.14.8.1