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Determination of the Relationship between the Students’ “Mathematical Literacy” and “Home and School Educational Resources” in Program for International Student Assessment - (PISA 2012)

Yıl 2017, Cilt: 13 Sayı: 1, 94 - 109, 16.04.2017
https://doi.org/10.17860/mersinefd.305762

Öz

The purpose of the study is to
examine how home
(desk, private
study room, a quiet place to study, computer, internet connectivity, textbook,
and DVD player) and school educational resources (public or private, school
location, class size, shortage of mathematics teachers, instructional
materials, Internet connection, library materials, buildings and grounds,
heating, cooling and lighting
) are related to students’ mathematical
literacy in PISA 2012. The students in Turkey who attended PISA
2012
form the sample of this study. The sample of the study involves 4308 students
and 157 schools. (Turkish sample of PISA 2012 consists of 4848 students from
170 schools, but in this study, missing values in 13 schools were removed from
the analysis before hierarchical linear modeling was done). Hierarchical linear
model (HLM) was used for data analysis. The variables at student level (Level
1) which are related to mathematical literacy are having a study desk,
computer, textbook, and DVD
player.
According to the results when the students have a study desk, computer,
textbook, and DVD
player, their
mathematical literacy increases. The variable
at school level (Level 2), which is related to mathematical
literacy is having Internet connection at school.

Kaynakça

  • Abbott, M.L., Joireman, J., & Stroh, H.R. (2002). The influence of district size, school size and socioeconomic status on student achievement in Washington: A replication study using hierarchical linear modeling. A Technical Report for the Washington School Research Center.
  • Acar, M. (2013). Öğrenci başarılarının belirlenmesi sınavında Türkçe dersi başarısının öğrenci ve okul özellikleri ile ilişkisinin hiyerarşik lineer model ile analizi. Yayınlanmış doktora tezi, Ankara. Ankara Üniversitesi.
  • Acar, T., & Öğretmen, T. (2012). Çok düzeyli istatistiksel yöntemler ile 2006 PISA fen bilimleri performansının incelenmesi. Eğitim ve Bilim Dergisi, 37(163), 178-189.
  • Acar Güvendir, M. (2014). Öğrenci başarılarının belirlenmesi sınavında öğrenci ve okul özelliklerinin Türkçe başarısı ile ilişkisi. Eğitim ve Bilim, 39(172), 163-180.
  • Adaman, F., & Keyder, Ç. (2006). Türkiye’de büyükşehirlerin varoşlarında yoksulluk ve sosyal dışlanma. Poverty and social exclusion in the suburbs of big cities in Turkey. European Commission, the Local Community Action Program in Combating Social Exclusion 2002-2006.
  • Akyüz, G. (2006). Teacher and classroom characteristics: their relationship with mathematics achievement in Turkey, European Union countries and candidate countries. A Thesis Submitted to the Graduate School of Natural and Applied Sciences. Ankara: Middle East Technical University.
  • Aslanoğlu, E.A. (2007). PIRLS 2001 Türkiye verilerine göre 4. sınıf öğrencilerinin okuduğunu anlama becerileriyle ilişkili faktörler. Yayınlanmamış doktora tezi, Ankara. Ankara Üniversitesi, Eğitim Bilimleri Enstitüsü.
  • Atar, H.Y., & Atar, B. (2012). Türk eğitim reformunun öğrencilerin TIMSS 2007 fen başarılarına etkisinin incelenmesi. Kuram ve Uygulamada Eğitim Bilimleri, 12(4), 2621-2636.
  • Attewell, P., & Battle, J. (1999). Home computers and school performance. The Information Society, 15, 1-10.
  • Attewell, P., Suazo-Garcia, B., & Battle, J. (2003). Computers and young children: Social benefit or social problem? Social Forces, 82(1), 277-296.
  • Baykul, Y. (2011). Türklerde eğitimde ölçme ve değerlendirme, Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi (Özel Sayı), 1-32.
  • Berliner, D.C. (2009). Poverty and potential: out-of-school factors and school success. Boulder, CO and Tempe, AZ: Education and the Public Interest Center, University of Colorado/Education Policy Research Unit, Arizona State University. Retrieved January 05, 2015 from http://epicpolicy.org/publication/poverty-and-potential.
  • Berk, R.A. (2005). Survey of 12 strategies to measure teaching effectiveness. International journal of teaching and learning in higher education, 17(1), 48-62.
  • Borzekowski, D.L.G., & Robinson, N.T. (2005). The remote, the mouse, and the No. 2 pencil: The household media environment and academic achievement among third grade students. Archives of Pediatrics and Adolescent Medicine, 159(7), 607–13.
  • Briggs, J. (1993). What do inventories of students' learning processes really measure? A theoretical review and clarification. British Journal of Educational Psychology, 1, 3-19.
  • Chudowsky, N., & Pellegrino, J.W. (2003). Large-scale assessments that support learning: What will it take? Theory into Practice, 42(1), 75-83.
  • Çakan, M. (2003). Geniş ölçekli başarı testlerinin eğitimdeki yeri ve önemi. Eğitim ve Bilim, 28(128), 19-26.
  • Çalışkan, M. (2008). The impact of school and student related factors on scientific literacy skills in the programme for international student assessment- PISA 2006. A Thesis Submitted to the Graduate School of Natural and Applied Sciences. Ankara: Middle East Technical University.
  • 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.
  • Dudaite, J. (2013). Influence of economic home factors on student achievement. Outlines of Social Innovations in Lithuania in (266-279), Kocani: European Scientific Institute and licensors.
  • Duncan, G. J., & Brooks–Gunn, J. (1997). Income effects across the life span: Integration and interpretation. In G. J.
  • Duncan & J. Brooks–Gunn (Eds.) Consequences of growing up poor (596–610). NY: Russell Sage Foundation Press.
  • Fiorini, M. (2010). The effect of home computer use on children's cognitive and non‐cognitive skills. Economics of Education Review, 29(1), 55–72.
  • Fisher, R. (2005). Teaching children to think. Cheltenham: Nelson Thornes.
  • Fuchs, T., & Woessmann, L. (2004). Computers & student learning: Bivariate and multivariate evidence on the availability and use of computers at home and at school. CESifo Working Paper 1321. Munich: CESifo. Available: http://ideas. repec.org/p/ces/ceswps/ _1321.html.
  • Fullarton, S. (2004). Closing the gaps between schools: Accounting for variation in mathematics achievement in Australian schools using TIMSS 95 and TIMSS 99. In Proceedings of the IRC-2004 TIMSS, 1, 16-31.
  • Garner, R. (1992). Learning from school texts. Educational Psychologist, 27, 53–63.
  • Gedikoğlu, T. (2005). Avrupa Birliği sürecinde Türk eğitim sistemi: sorunlar ve çözüm önerileri. Mersin University Journal of the Faculty of Education, 1(1), 66-80.
  • Gelbal, S. (2008). Sekizinci sınıf öğrencilerinin sosyoekonomik özelliklerinin Türkçe başarısı üzerinde etkisi. Education and Science, 150, 1-13.
  • Grilli, L., Pennoni, F., Rampichini, C., & Romeo, I. (2016). Exploiting TIMSS and PIRLS Combined Data: Multivariate Multilevel Modelling of Student Achievement. The Annals of Applied Statistics 10(4), 2405–2426 DOI: 10.1214/16-AOAS988.
  • Goddard, R.D., Sweetland, S.R., & Hoy, W.K. (2000). Academic emphasis of urban elementary schools and student achievement in reading and mathematics: A multilevel analysis. Educational Administration Quarterly, 36(5), 683-702.
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Uluslararası Öğrenci Değerlendirme Programında Öğrencilerin Matematik Okuryazarlıkları ile Ev ve Okul Eğitim Olanakları Arasındaki İlişkinin Belirlenmesi - (PISA-2012)

Yıl 2017, Cilt: 13 Sayı: 1, 94 - 109, 16.04.2017
https://doi.org/10.17860/mersinefd.305762

Öz

Bu araştırmanın amacı, Uluslarası Öğrenci
Değerlendirme Programı (PISA) 2012’de öğrencilerin matematik okuryazarlıkları
ile ev (çalışma masası, kendine ait oda, sessiz bir çalışma yeri, bilgisayar,
internet bağlantısı, çalışma kitabı, DVD oynatıcısı) ve okul (okul türü,
bölgesi, sınıf büyüklüğü, matematik öğretmeni eksikliği, öğretimsel
materyaller, internet bağlantısı, kütüphane materyalleri, binalar ve alanlar,
ısınma, soğutma ve aydınlatma) eğitim olanakları arasındaki ilişkiyi
incelemektir. PISA 2012’ye katılmış olan Türkiye’deki 157 okuldan, 4308 15 yaş
grubu öğrenciler, bu araştırmanın örneklemini oluşturmaktadır
(PISA
Türkiye örneklemi 170 okuldan 4848 öğrencidir; ancak HLM’ye başlamadan önce 13 okula
ait kayıp veriler veri setinden çıkarılmıştır). Verilerin analizinde,
veriler içe içe yapı gösterdiği için
hiyeraşik lineer model kullanılmıştır. Öğrenci düzeyinde matematik
okuryazarlığı ile ilişkili olan değişkenler; çalışma masası, bilgisayar,
çalışma kitabı ve DVD oynatıcısıdır. Buna göre, çalışma masası, bilgisayar,
çalışma kitabı ve DVD oynatıcısına sahip olan öğrencilerin matematik
okuryazarlığı daha yüksektir. Okul düzeyinde matematik okuryazarlığı ile
ilişkili olan değişken ise okulda internet bağlantısının olmasıdır. 

Kaynakça

  • Abbott, M.L., Joireman, J., & Stroh, H.R. (2002). The influence of district size, school size and socioeconomic status on student achievement in Washington: A replication study using hierarchical linear modeling. A Technical Report for the Washington School Research Center.
  • Acar, M. (2013). Öğrenci başarılarının belirlenmesi sınavında Türkçe dersi başarısının öğrenci ve okul özellikleri ile ilişkisinin hiyerarşik lineer model ile analizi. Yayınlanmış doktora tezi, Ankara. Ankara Üniversitesi.
  • Acar, T., & Öğretmen, T. (2012). Çok düzeyli istatistiksel yöntemler ile 2006 PISA fen bilimleri performansının incelenmesi. Eğitim ve Bilim Dergisi, 37(163), 178-189.
  • Acar Güvendir, M. (2014). Öğrenci başarılarının belirlenmesi sınavında öğrenci ve okul özelliklerinin Türkçe başarısı ile ilişkisi. Eğitim ve Bilim, 39(172), 163-180.
  • Adaman, F., & Keyder, Ç. (2006). Türkiye’de büyükşehirlerin varoşlarında yoksulluk ve sosyal dışlanma. Poverty and social exclusion in the suburbs of big cities in Turkey. European Commission, the Local Community Action Program in Combating Social Exclusion 2002-2006.
  • Akyüz, G. (2006). Teacher and classroom characteristics: their relationship with mathematics achievement in Turkey, European Union countries and candidate countries. A Thesis Submitted to the Graduate School of Natural and Applied Sciences. Ankara: Middle East Technical University.
  • Aslanoğlu, E.A. (2007). PIRLS 2001 Türkiye verilerine göre 4. sınıf öğrencilerinin okuduğunu anlama becerileriyle ilişkili faktörler. Yayınlanmamış doktora tezi, Ankara. Ankara Üniversitesi, Eğitim Bilimleri Enstitüsü.
  • Atar, H.Y., & Atar, B. (2012). Türk eğitim reformunun öğrencilerin TIMSS 2007 fen başarılarına etkisinin incelenmesi. Kuram ve Uygulamada Eğitim Bilimleri, 12(4), 2621-2636.
  • Attewell, P., & Battle, J. (1999). Home computers and school performance. The Information Society, 15, 1-10.
  • Attewell, P., Suazo-Garcia, B., & Battle, J. (2003). Computers and young children: Social benefit or social problem? Social Forces, 82(1), 277-296.
  • Baykul, Y. (2011). Türklerde eğitimde ölçme ve değerlendirme, Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi (Özel Sayı), 1-32.
  • Berliner, D.C. (2009). Poverty and potential: out-of-school factors and school success. Boulder, CO and Tempe, AZ: Education and the Public Interest Center, University of Colorado/Education Policy Research Unit, Arizona State University. Retrieved January 05, 2015 from http://epicpolicy.org/publication/poverty-and-potential.
  • Berk, R.A. (2005). Survey of 12 strategies to measure teaching effectiveness. International journal of teaching and learning in higher education, 17(1), 48-62.
  • Borzekowski, D.L.G., & Robinson, N.T. (2005). The remote, the mouse, and the No. 2 pencil: The household media environment and academic achievement among third grade students. Archives of Pediatrics and Adolescent Medicine, 159(7), 607–13.
  • Briggs, J. (1993). What do inventories of students' learning processes really measure? A theoretical review and clarification. British Journal of Educational Psychology, 1, 3-19.
  • Chudowsky, N., & Pellegrino, J.W. (2003). Large-scale assessments that support learning: What will it take? Theory into Practice, 42(1), 75-83.
  • Çakan, M. (2003). Geniş ölçekli başarı testlerinin eğitimdeki yeri ve önemi. Eğitim ve Bilim, 28(128), 19-26.
  • Çalışkan, M. (2008). The impact of school and student related factors on scientific literacy skills in the programme for international student assessment- PISA 2006. A Thesis Submitted to the Graduate School of Natural and Applied Sciences. Ankara: Middle East Technical University.
  • 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.
  • Dudaite, J. (2013). Influence of economic home factors on student achievement. Outlines of Social Innovations in Lithuania in (266-279), Kocani: European Scientific Institute and licensors.
  • Duncan, G. J., & Brooks–Gunn, J. (1997). Income effects across the life span: Integration and interpretation. In G. J.
  • Duncan & J. Brooks–Gunn (Eds.) Consequences of growing up poor (596–610). NY: Russell Sage Foundation Press.
  • Fiorini, M. (2010). The effect of home computer use on children's cognitive and non‐cognitive skills. Economics of Education Review, 29(1), 55–72.
  • Fisher, R. (2005). Teaching children to think. Cheltenham: Nelson Thornes.
  • Fuchs, T., & Woessmann, L. (2004). Computers & student learning: Bivariate and multivariate evidence on the availability and use of computers at home and at school. CESifo Working Paper 1321. Munich: CESifo. Available: http://ideas. repec.org/p/ces/ceswps/ _1321.html.
  • Fullarton, S. (2004). Closing the gaps between schools: Accounting for variation in mathematics achievement in Australian schools using TIMSS 95 and TIMSS 99. In Proceedings of the IRC-2004 TIMSS, 1, 16-31.
  • Garner, R. (1992). Learning from school texts. Educational Psychologist, 27, 53–63.
  • Gedikoğlu, T. (2005). Avrupa Birliği sürecinde Türk eğitim sistemi: sorunlar ve çözüm önerileri. Mersin University Journal of the Faculty of Education, 1(1), 66-80.
  • Gelbal, S. (2008). Sekizinci sınıf öğrencilerinin sosyoekonomik özelliklerinin Türkçe başarısı üzerinde etkisi. Education and Science, 150, 1-13.
  • Grilli, L., Pennoni, F., Rampichini, C., & Romeo, I. (2016). Exploiting TIMSS and PIRLS Combined Data: Multivariate Multilevel Modelling of Student Achievement. The Annals of Applied Statistics 10(4), 2405–2426 DOI: 10.1214/16-AOAS988.
  • Goddard, R.D., Sweetland, S.R., & Hoy, W.K. (2000). Academic emphasis of urban elementary schools and student achievement in reading and mathematics: A multilevel analysis. Educational Administration Quarterly, 36(5), 683-702.
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  • Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses related to achievement. London, UK: Routledge. International Association for the Evaluation of Educational Achievement (IEA). Retrieved April 4, 2012, from http://timssandpirls.bc.edu.
  • Ismail, N.A., & Awang, H. (2008). Differentials in mathematics achievement among eighth-grade students in Malaysia. International Journal of Science and Mathematics Education, 6(3), 559-571.
  • İş Güzel, Ç. (2006). A cross-cultural comparison of the impact of human and physical resource allocations on students’ mathematical literacy skills in the programme for international student assessment (PISA) 2003. A Thesis Submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University: Ankara.
  • Jackson, L.A., Von Eye, A., Biocca, F.A., Barbatsis, G., Zhao, Y., & Fitzgerald, H.E. (2006). Does home internet use influence the academic performance of low-income children? Developmental Psychology, 42(3), 429-435.
  • Jamison, D.T., Searle, B., Galda, K., & Heyneman, S.P. (1981). Improving elementary mathematics education in Nicaragua: An experimental study of the impact of textbooks and radio on achievement. Journal of Educational psychology, 73(4), 556-567.
  • Juan, A., & Visser, M. (2017). Home and school environmental determinants of science achievement of South African students. South African Journal of Education, 37(1), 1-10.
  • Judge, S. (2005). Impact of computer technology on academic achievement on young African American children. Journal of Research in Childhood Education, 20(2), 97–107.
  • Kassebaum, D. G. (1990). The measurement of outcomes in the assessment of educational program effectiveness. Academic Medicine, 65(5), 293-296.
  • Lay, Y.F., & Chandrasegaran, A.L. (2016). Availability of School Resources and TIMSS Grade 8 Students' Science Achievement: A Comparative Study between Malaysia and Singapore. International Journal of Environmental and Science Education, 11(9), 3065-3080.
  • Lee, V.E., Zuze, T.L., & Ross, K.N. (2005). School effectiveness in 14 Sub- Saharan African countries: Links with 6th graders' reading achievement. Studies in Educational Evaluation. 31(2-3), 207-246.
  • Lynn, R., & Mikk, J. (2007). National differences in intelligence and educational attainment. Intelligence, 35(2), 115-121.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2002). Öğrenci başarılarının belirlenmesi sınavı durum belirleme raporu: Türkçe, Matematik, Fen Bilgisi, Sosyal Bilgiler. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2003a). PIRLS 2001 uluslararası okuma becerilerinde gelişim projesi, ulusal rapor. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2003b). TIMSS 1999 üçüncü uluslararası matematik ve fen bilgisi çalışması, ulusal rapor. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2005). PISA 2003 uluslararası öğrenci değerlendirme projesi, ulusal nihai rapor. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2007a). PISA 2006 uluslararası öğrenci değerlendirme projesi, ulusal ön rapor. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2007b). Öğrenci başarılarının belirlenmesi sınavı durum belirleme raporu: Türkçe, Matematik, Fen Bilgisi, Sosyal Bilgiler, İngilizce. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Milli Eğitim Bakanlığı, Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı (2009). Öğrenci başarılarının belirlenmesi sınavı durum belirleme raporu: Türkçe, Matematik, Fen Bilgisi, Sosyal Bilgiler, İngilizce. Eğitimi Araştırma ve Geliştirme Dairesi Yayınları. Milli Eğitim Bakanlığı.
  • Mullis, I.V.S., Martin, M.O., Foy, P., & Arora, A. (2012). TIMSS 2011 International results in mathematics. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
  • Nes, R.B., Hauge, L.J., Kornstad, T., Kristensen, P., Landolt, M.A., Eskedal, L.T., Irgens, L.M., & Vollrath, M.E. (2011). The impact of child behavior problems on maternal employment: A Longitudinal Cohort Study. Journal of Family and Economic Issues, 35, 351-361.
  • Nye, B., Hedges, L.V., & Konstantopoulos, S. (2000). The effects of small classes on academic achievement: The results of the Tennessee class size experiment. American Educational Research Journal, 37(1), 123–151. DOI: 10.3102/00028312037001123.
  • Organization for Economic Co-operation and Development (OECD) (2016-10 Nisan) retrived from https://www.oecd.org/pisa/pisaproducts/pisa2012database-downloadabledata.htm
  • Özer, Y., & Anıl, D. (2011). Öğrencilerin fen ve matematik başarılarını etkileyen faktörlerin yapısal eşitlik modeli ile incelenmesi. Hacettepe Eğitim Fakültesi Dergisi, 41, 313-324.
  • Özer Özkan, Y., & Acar Güvendir, A. (2014). Socioeconomic factors of students’ relation to mathematic achievement: comparison of PISA and ÖBBS. International Online Journal of Educational Sciences, 6(3), 776-789.
  • Ramírez, M.J. (2006). Understanding the low mathematics achievement of Chilean students: A cross-national analysis using TIMSS data. International Journal of Educational Research, 45(3), 102-116.
  • Raudenbush, S.W., Cheong, Y.F., & Fotiu, R.P. (1996). Social inequality, social segregation, and their relationship to reading literacy in 22 countries. Reading literacy in an International Perspective. Collected Papers from the IEA Reading Literacy Study. U.S. Department of Education Office of Educational Research and Improvement, 3-53.
  • Raudenbush, S.W., & Bryk, A.S. (2002). Hierarchical linear models (2nd ed.). Newbury Park, CA: Sage.
  • Reys, R., Reys, B., Lapan, R., Holliday, G., & Wasman, D. (2003). Assessing the impact of" standards"-based middle grades mathematics curriculum materials on student achievement. Journal for Research in Mathematics Education, 34(1), 74-95.
  • Robitaille, D.F., & Travers, K.J. (1992). International studies of achievement in mathematics. Douglas A. (Ed). (1992). Handbook of research on mathematics teaching and learning: A project of the National Council of Teachers of Mathematics (687-709). New York, NY, England: Macmillan Publishing Co, Inc, xi, 771.
  • Roscigno, V., & Ainsworth-Darnell, J.W. (1999). Race, cultural capital, and educational resources: Persistent inequalities and achievement returns. Sociology of Education, 72, 158-178.
  • Rutkowski, L., Gonzalez, E., Joncas, M., & Von Davier, M. (2010). International large-scale assessment data issues in secondary analysis and reporting. Educational Researcher, 39(2), 142-151.
  • Schmidt, M. E., & Vandewater, E. A. (2008). Media and attention, cognition, and school achievement. The Future of Children, 18(1), 63-85.
  • Schmidt, W.H., McKnight, C.C., & Raizen, S.A. (1997). Splintered vision: An investigation of US mathematics and science education. Norwel, MA: Kluwer Academic Publishers.
  • Schmidt, W.H., McKnight, C. C., Houang, R.T., Wang, H.C., Wiley, D.E., Cogan, L.S., et al. (2001). Why schools matter: A cross-national comparison of curriculum and learning. San Francisco: Jossey-Bass.
  • Shiqi, H. (2006). Teachers' assessment practices and fourth graders' reading literacy achievements: An international study. Educational tests and Measurements; Reading Instruction. DAI/A 67-01. No: 3201337.
  • Snijders, T., & Bosker, R. (1999). Multilevel analysis. Thousand Oaks, CA: Sage Publications, Inc.
  • Southworth, B. (2006). Am I rich enough to do well in math? Math test scores and socio-economic status. Doctoral dissertation, Wichita State University.
  • Şirin, S.R. (2005). Socioeconomic status and achievement: A meta-analytic review of research. Review of Educational Research, 75, 417-453. DOI: 10.3102/00346543075003417.
  • Tekin, H. (2004). Eğitimde ölçme ve değerlendirme, (17. Baskı), Ankara: Yargı Yayınevi.
  • Teachman, J. (1987). Family background, educational resources, and educational attainment. American sociological review, 52, 548-557.
  • Thao, Y.J. (2003). Empowering among students: Home and school factors. The Urban Review, 35(1), 25-42.
  • Toriskie, J.M. (1999). The effects of internet usage on student achievement and student attitudes (fourth-grade, social studies). Unpublished doctoral dissertation, Loyola University of Chicago.
  • Walsh, G., & Gardner, J. (2005). Assessing the quality of early years learning environments. Early childhood research and practice, 7(1), 456-466.
  • Yang, Y. (2003). Dimensions of socio-economic status and their relationship to mathematics and science achievement at individual and collective levels. Scandinavian Journal of Educational Research, 47(1), 21-41.
  • Ziya, E., Doğan, N., & Kelecioğlu, H. (2010). What is the predict level of which computer using skills measured in PISA for achievement in Mathematics. The Turkish Online Journal of Educational Technology, 9(4), 185-191. http://www.uccs.edu/lbecker/index.html Retrieved August 25, 2016
Toplam 79 adet kaynakça vardır.

Ayrıntılar

Konular Eğitim Üzerine Çalışmalar
Bölüm Makaleler
Yazarlar

Meltem Acar Güvendir

Yayımlanma Tarihi 16 Nisan 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 13 Sayı: 1

Kaynak Göster

APA Acar Güvendir, M. (2017). Uluslararası Öğrenci Değerlendirme Programında Öğrencilerin Matematik Okuryazarlıkları ile Ev ve Okul Eğitim Olanakları Arasındaki İlişkinin Belirlenmesi - (PISA-2012). Mersin Üniversitesi Eğitim Fakültesi Dergisi, 13(1), 94-109. https://doi.org/10.17860/mersinefd.305762

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Dergide yayınlanan tüm makaleler, diğerleri tarafından paylaşılmasına olanak veren Creative Commons Alıntı-Gayri Ticari-Türetilemez 4.0 Uluslararası (CC BY-NC-ND 4.0) lisansı altında lisanslanır.