Research Article
DETERMINATION OF STUDENTS’ PROFILES ACCORDING TO HOME EDUCATIONAL RESOURCES AND MATHEMATICS ACHIEVEMENT VIA LATENT CLASS ANALYSIS
Abstract
The purpose of this study was to examine the correlation between mathematics achievements and
ownership of the home educational resources of students via Latent Class Analysis (LCA) using Programme
for International Student Assessment (PISA) 2015 study. Although 5895 15-year-old Turkish students
were participated in PISA study, the data of 5355 students were included in the analysis because of the
missing data of the selected variables. 12 items which were related to students’ home educational resources
were used in LCA analysis. As a result, 3 classes were determined; 32% of students were in 1st latent class,
29% of students were in 2nd latent class and 39% of students were in 3rd latent class. It was revealed that
students in 1st latent class had only “a desk to study at”, “a quiet place to study”, “books to help with your
school work” and “a dictionary” while students in 3rd latent class had all the home educational resources
(12 items). Furthermore, it was shown that students in 3rd latent class had the highest mathematics score
while students in 1st latent class had the lowest mathematics scores.
References
- ACAR GÜVENDİR, M. (2014). Öğrenci Başarılarının Belirlenmesi Sınavında Öğrenci ve Okul Özelliklerinin Türkçe Başarısı ile İlişkisi, Eğitim ve Bilim, 39(172): 163-180.
- ARICIGİL ÇİLAN, Ç. (2015). Uygulamalı Gizli Sınıf Analizi, İstanbul:Çağlayan Kitabevi.
- ARIKAN, S., Van de Vijver, F.J.R.; Yağmur, K. (2016). Factors Contributing to Mathematics Achievement Differences of Turkish and Australian Students in TIMSS 2007 and 2011, Eurasia Journal of Mathematics, Science & Technology Education, 12(8): 2039-2059.
- ATTEWELL, P., Battle, J. (2006). Home Computers and School Performance, The Information Society, 15: 1-10.
- BEESE, J., Liang, X. (2010). Do Resources Matter? PISA Science Achievement Comparison Between Students in the United States, Canada and Finland, Improving Schools, 13(3): 266-279.
- DAYTON, C.M.; Macready, G.B. (1988). Concomitant-Variable Latent-Class Models, Journal of the American Statistical Association, 83(401): 173-178.
- DEMİR, I., Kılıç, S., Ünal, H. (2010). Effects of Students’ and Schools’ Characteristics on Mathematics Achievement: Findings from PISA 2006, Procedia Social and Behavioral Sciences, 2: 3099-3103.
- 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.
- FIRAT, E., Aydın, A. (2015). İnsani Kalkınma Endeksine göre Türkiye’nin Eğitim Endeks Göstergelerinin OECD Ülkeleri ile Karşılaştırılması, Selçuk Üniversitesi İktisadi ve İdari Bilimler Fakültesi Sosyal Ekonomik Araştırmalar Dergisi, 15(29): 62-87.
- FUCHS, T., Woessmann, L. (2014). Computers and Student Learning: Bivariate and Multivariate Evidence on the Availability and Use of Computers at Home and at School, Munich: CESifo Working Paper No. 1321.
- GOODMAN, L.A. (1974). Exploratory Latent Structure Analysis Using Both Identifiable And Unidentifiable Models, Biometrika, 61(2): 215-231.
- GOODMAN, L.A. (1979). On The Estimation Of Parameters In Latent Structure Analysis, Psychometrika, 44(1): 123-128.
- GÜVENDİR, E. (2015). A Multi-Level Simultaneous Analysis of How Student and School Characteristics Are Related to Students’ English Language Achievement, Education Research And Perspectives, 42: 491-527.
- HAGENAARS, J.A., McCutcheon, A.L. (2002). Applied Latent Class Analysis, Cambridge University Press.
- 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.
- 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.
- KITSANTAS, A., Cheema, J., Ware, H.W. (2011). Mathematics Achievement: The Role of Homework and Self-Efficacy Beliefs, Journal of Advanced Academics, 22(2): 310-339.
- LEWIS, R., Aiken, J. (1970). Attitudes toward Mathematics, Review of Educational Research, 40(4): 551- 596.
- MİLLİ EĞİTİM BAKANLIĞI (MEB), (2005). PISA 2003 Projesi Ulusal Nihai Raporu, Ankara.
- ORGANIZATION FOR ECONOMIC COOPERATION AND DEVELOPMENT (OECD), (2016). PISA 2015 Results (Volume I): Excellence and Equity in Education, OECD Publishing.
- ÖZBERK, E.H., Atalay Kabasakal, K., Boztunç Öztürk, N. (2017). Investigating the Factors Affecting Turkish Students’ PISA 2012 Mathematics Achievement Using Hierarchical Linear Modeling, Hacettepe University Journal of Education, 32(3): 544-559.
- ROSCIGNO, V.J., Ainsworth-Darnell, J.W. (1999). Race, Cultural Capital, and Educational Resources: Persistent Inequalities and Achievement Returns, Sociology of Education, 72: 158-178.
- SMITH, R., Neisworth, J., Greer, J.G. (1978). Evaluating Educational Environments, Bell and Howell, Colombus, OH: Merrill/Macmillan.
- ŞİRİN, S.R. (2005). Socioeconomic Status and Achievement: A Meta-Analytic Review of Research, Review of Educational Research, 75: 417-453.
- TOPÇU, M.S., Erbilgin, E., Arıkan, S. (2016). Factors Predicting Turkish and Korean Students’ Science and Mathematics Achievement in TIMSS 2011, Eurasia Journal of Mathematics, Science & Technology Education, 12(7): 1711-1737.
Year 2017,
Volume: 39 Issue: 2, 505 - 520, 24.12.2017
Abstract
References
- ACAR GÜVENDİR, M. (2014). Öğrenci Başarılarının Belirlenmesi Sınavında Öğrenci ve Okul Özelliklerinin Türkçe Başarısı ile İlişkisi, Eğitim ve Bilim, 39(172): 163-180.
- ARICIGİL ÇİLAN, Ç. (2015). Uygulamalı Gizli Sınıf Analizi, İstanbul:Çağlayan Kitabevi.
- ARIKAN, S., Van de Vijver, F.J.R.; Yağmur, K. (2016). Factors Contributing to Mathematics Achievement Differences of Turkish and Australian Students in TIMSS 2007 and 2011, Eurasia Journal of Mathematics, Science & Technology Education, 12(8): 2039-2059.
- ATTEWELL, P., Battle, J. (2006). Home Computers and School Performance, The Information Society, 15: 1-10.
- BEESE, J., Liang, X. (2010). Do Resources Matter? PISA Science Achievement Comparison Between Students in the United States, Canada and Finland, Improving Schools, 13(3): 266-279.
- DAYTON, C.M.; Macready, G.B. (1988). Concomitant-Variable Latent-Class Models, Journal of the American Statistical Association, 83(401): 173-178.
- DEMİR, I., Kılıç, S., Ünal, H. (2010). Effects of Students’ and Schools’ Characteristics on Mathematics Achievement: Findings from PISA 2006, Procedia Social and Behavioral Sciences, 2: 3099-3103.
- 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.
- FIRAT, E., Aydın, A. (2015). İnsani Kalkınma Endeksine göre Türkiye’nin Eğitim Endeks Göstergelerinin OECD Ülkeleri ile Karşılaştırılması, Selçuk Üniversitesi İktisadi ve İdari Bilimler Fakültesi Sosyal Ekonomik Araştırmalar Dergisi, 15(29): 62-87.
- FUCHS, T., Woessmann, L. (2014). Computers and Student Learning: Bivariate and Multivariate Evidence on the Availability and Use of Computers at Home and at School, Munich: CESifo Working Paper No. 1321.
- GOODMAN, L.A. (1974). Exploratory Latent Structure Analysis Using Both Identifiable And Unidentifiable Models, Biometrika, 61(2): 215-231.
- GOODMAN, L.A. (1979). On The Estimation Of Parameters In Latent Structure Analysis, Psychometrika, 44(1): 123-128.
- GÜVENDİR, E. (2015). A Multi-Level Simultaneous Analysis of How Student and School Characteristics Are Related to Students’ English Language Achievement, Education Research And Perspectives, 42: 491-527.
- HAGENAARS, J.A., McCutcheon, A.L. (2002). Applied Latent Class Analysis, Cambridge University Press.
- 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.
- 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.
- KITSANTAS, A., Cheema, J., Ware, H.W. (2011). Mathematics Achievement: The Role of Homework and Self-Efficacy Beliefs, Journal of Advanced Academics, 22(2): 310-339.
- LEWIS, R., Aiken, J. (1970). Attitudes toward Mathematics, Review of Educational Research, 40(4): 551- 596.
- MİLLİ EĞİTİM BAKANLIĞI (MEB), (2005). PISA 2003 Projesi Ulusal Nihai Raporu, Ankara.
- ORGANIZATION FOR ECONOMIC COOPERATION AND DEVELOPMENT (OECD), (2016). PISA 2015 Results (Volume I): Excellence and Equity in Education, OECD Publishing.
- ÖZBERK, E.H., Atalay Kabasakal, K., Boztunç Öztürk, N. (2017). Investigating the Factors Affecting Turkish Students’ PISA 2012 Mathematics Achievement Using Hierarchical Linear Modeling, Hacettepe University Journal of Education, 32(3): 544-559.
- ROSCIGNO, V.J., Ainsworth-Darnell, J.W. (1999). Race, Cultural Capital, and Educational Resources: Persistent Inequalities and Achievement Returns, Sociology of Education, 72: 158-178.
- SMITH, R., Neisworth, J., Greer, J.G. (1978). Evaluating Educational Environments, Bell and Howell, Colombus, OH: Merrill/Macmillan.
- ŞİRİN, S.R. (2005). Socioeconomic Status and Achievement: A Meta-Analytic Review of Research, Review of Educational Research, 75: 417-453.
- TOPÇU, M.S., Erbilgin, E., Arıkan, S. (2016). Factors Predicting Turkish and Korean Students’ Science and Mathematics Achievement in TIMSS 2011, Eurasia Journal of Mathematics, Science & Technology Education, 12(7): 1711-1737.
There are 25 citations in total.
Details
| Subjects | Economics |
|---|---|
| Journal Section | Makaleler |
| Authors | |
| Publication Date | December 24, 2017 |
| Submission Date | September 1, 2017 |
| Published in Issue | Year 2017 Volume: 39 Issue: 2 |
Cite
Marmara University Journal of Economic and Administrative Sciences is licensed under Attribution-NonCommercial 4.0 International
