Journals / Kuram ve Uygulamada Eğitim Bilimleri / 2014 / Cilt: 14 - Sayı: 2

A Logistic Regression Analysis of Turkey's 15-year- olds' Scoring above the OECD Average on the PISA'09

Pages
649–668
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Specifically, the results indicated that gender, age when first entering school, mother's level of education, the number of books present at home, students' attitudes toward reading, and the amount of time spent learning the test's language (Turkish) per week were those factors found to predict the probability of students' scoring above the OECD average (493) on the PISA'09 reading assessment.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to investigate which factors are associated with Turkey's 15-year-olds' scoring above the OECD average (493) on the PISA'09 reading assessment.
📊
Key Findings & Data:Collected from a total of 4,996 15-year-old students from Turkey, data were analyzed by logistic regression analysis in order to model the data of students who were split into two: (1) those students who scored above the OECD average of 493 points on the PISA'09 reading assessment, and (2) those who scored below the average.
💡
Conclusion & Impact:Specifically, the results indicated that gender, age when first entering school, mother's level of education, the number of books present at home, students' attitudes toward reading, and the amount of time spent learning the test's language (Turkish) per week were those factors found to predict the probability of students' scoring above the OECD average (493) on the PISA'09 reading assessment.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

This study aims to investigate which factors are associated with Turkey's 15-year-olds' scoring above the OECD average (493) on the PISA'09 reading assessment. Collected from a total of 4,996 15-year-old students from Turkey, data were analyzed by logistic regression analysis in order to model the data of students who were split into two: (1) those students who scored above the OECD average of 493 points on the PISA'09 reading assessment, and (2) those who scored below the average. Specifically, the results indicated that gender, age when first entering school, mother's level of education, the number of books present at home, students' attitudes toward reading, and the amount of time spent learning the test's language (Turkish) per week were those factors found to predict the probability of students' scoring above the OECD average (493) on the PISA'09 reading assessment. The findings of this study contribute to the existing literature within this field by identifying which sources play a role in 15-year-olds' success on the PISA'09 reading assessment in Turkey

🔖

Cite This Article

KASAPOĞLU, K. (2014). A Logistic Regression Analysis of Turkey's 15-year- olds' Scoring above the OECD Average on the PISA'09. Kuram ve Uygulamada Eğitim Bilimleri, Cilt: 14 - Sayı: 2, 649–668. https://ajindex.com/articles/346224

References (5)

  1. Acar, T. (2012). 2009 yılı uluslararası öğrenci başarılarını değerlendirme programında Türk öğrencilerin başarılarını etkileyen faktörler. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 3(2), 309-314.
  2. Alloway, N. (2007). Swimming against the tide: Boys, literacies, and schooling-an Australian story. Canadian Journal of Education, 30(2), 582-605. Árnason, A. E. (2006). Encouraging intrinsic motivation in the middle school reading classroom (B.Ed. thesis, University of Akureyri, Iceland). Retrieved from http:// skemman.is/stream/get/1946/544/1086/1/encouraging.pdf Bracey, G. W. (2005). Research: Cheating update. Phi Delta Kappan, 86(8), 637-638.
  3. Brewster, C., & Fager, J. (2000). Increasing student engagement and motivation: From time-on-task to homework. Portland, OR: Northwest Regional Educational Laboratory. Retrieved from http://educationnorthwest. org/webfm_send/452 Brozo, W. G., Shiel, G., & Topping, K. (2007-2008). Engagement in reading: Lessons learned from three PISA countries. Journal of Adolescent & Adult Literacy, 51(4), 315. doi: 10.1598/JAAL.51.4.2 Bulut, O., Delen, E., & Kaya, F. (2012). An SEM model based on PISA 2009 in Turkey: How does the use of technology and self-regulation activities predict reading scores? Procedia - Social and Behavioral Sciences, 64, 564 Can, R., Türkyılmaz, M., & Karadeniz, A. (2010). Ergenlik dönemi öğrencilerinin okuma alışkanlıkları. Ahi Evran Üniversitesi Eğitim Fakültesi Dergisi, 11(3), 1-21.
  4. Chiu, M. M., & McBride-Chang, C. (2006). Gender, context, and reading: a comparison of students in 43 countries. Scientific Studies of Reading, 10(4), 331-362. doi: 1207/s1532799xssr1004_1 Çobanoğlu, R., & Kasapoğlu, K. (2010). PISA'da Fin başarısının nedenleri ve nasılları. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 39, 121-131.
  5. Elley, W. B. (1992). How in the world do students read? IEA study of reading literacy. Hamburg, Germany: International Association for the Evaluation of Educational Achievement. Available from ERIC database. (Document Reproduction Service No. ED360613) Entorf, H., & Minoiu, N. (2005). What a difference immigration policy makes: A comparison of PISA scores in Europe and traditional countries of immigration. German Economic Review, 6(3), 355-376. doi: 10.1111/j.1468- 2005.00137.x Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education (6th ed.). New York: The McGraw-Hill Companies, Inc. Geske, A., & Ozola, A. (2008). Factors influencing reading literac