Does Socioeconomic Status Influence Achievement? An analysis of the Performance of Kosovar Students on the 2015 and 2018 PISA Assessment
Keywords:
Socioeconomic status, Student achievement PISA, Kosovo
Abstract
Socioeconomic status has long been considered an
influential factor in student achievement. Similar to existing literature, results
of this analysis reveal that socioeconomic status influenced student
achievement in the 2015 and 2018 PISA assessments. However, the
achievement gap between categories widened between 2015 and 2018.
Results reveal that home possessions, school location, parental education
played a role in achievement. Furthermore, students who attended private
schools outperformed students in public schools, a gap that widened
considerably between assessments. Results of the current analysis reveal the
importance of socioeconomic factors in achievement and, the need for
policy builders to mitigate this impact.
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References
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Caponera, E., and Losito, B. (2016). Context factors and student achievement in the IEA studies: evidence from TIMSS. Large-scale Assessments in Education: an IEA-ETS Research Institute Journal, 4(1), 1–22.
Calero, J. (2005). Spain: Country analytical report. Equity in Education Thematic Review. www.oecd.org/spain/38693078.pdf.
Clements, D. and Sarama, J. (2009). Learning and teaching early math: The learning trajectories approach.http://lst-iiep.iiep-unesco.org/cgibin/wwwi32.exe/[in=epidoc1.in]/?t2000=026–594/(100).
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A. Shala, A. Grajcevci & F. Latifić: Does Socioeconomic Status Influence Achievement? An Analysis of the Performance of Kosovar Students on the 2015 and 2018 PISA Assessment 407
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Entorf, H. and Minoiu, N. (2004): What a Difference Immigration Law Makes: PISA results, migration background, socioeconomic status and social mobility in Europe and traditional countries of immigration, Darmstadt Discussion Papers in Economics, No. 128, Technische Universität Darmstadt, Department of Law and Economics, Darmstadt.
Entwisle, D. R. and Astone, N. M. (1994). Some Practical Guidelines for Measuring Youth’s Race/Ethnicity and Socioeconomic Status. Child Development, 65, 1521–1540.
Glewwe, P. W., Hanushek, E. A., Humpage, S. D. and Ravina, R. (2011) School resources and educational outcomes in developing countries: A review of the literature from 1990 to 2011 (Working Paper No. 17554). Retrieved from http:www.nber.org/papers/w17554.
Güven, U. (2017). The Relationship between Testing Frequency and Student Achievement in Eighth- Grade Mathematics: An International Comparative Study Based on TIMSS 2011 (doctoral dissertation). Duquesne University, Pittsburgh, PA.
Güven, U. and Akçay, A. O. (in press). Trends of Homework in Mathematics: Comparative Research Based on TIMSS Study. International Journal of Instruction.
Heckman, J. J., and Rubinstein, Y. (2001). The importance of noncognitive skills: Lessons from the GED testing program. The American Economic Review, 91, 145–149.
Hauser, R. M. (1994). Measuring Socioeconomic Status in Studies of Child Development. Child Development, 65, 1541–1545.
Hanushek, E. A., and Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46(3), 607–668.
Haveman, R. H., and Wolfe, B. (1984). Schooling and Economic Well-Being: The Role of Non-Market Effects. Journal of Human Resources 19(3): 377–407.
Ho, S. C. E. (2013). Multilevel Analysis of the PISA Data: Insights for policy and practice. Hong Kong: Hong Kong Institute of Educational Research
Krawchuk, S. and K. Rust (2002) Sample Design. In Adams, R. and M. Wu (eds.), PISA 2000 Technical Report. OECD, Paris, pp. 39-56.
Ladd, H . F ., a nd F iske, E . B . ( 2009). T he D utch e xperience w ith w eighted s tudent f unding: some lessons for the U.S. Working paper series http://files.eric.ed.gov/fulltext/ED507402. pdf.
Ladd, H. F., Fiske, E. B., and Ruijs, N. (2009). Parental choice in the Netherlands: Growing concern about segregation. Prepared for School Choice and School Improvement: Research in state, district and community contexts. Vanderbilt University.
Letourneau, N. L., Duffett-Leger, L., Levac, L., Watson, B., and Young-Morris, C. (2013). Socioeconomic status and child development: A meta-analysis. Journal of Emotional and Behavioral Disorders, 21(3), 211–224. https://doi.org/10.1177/1063426611421007
Maynard, T. (2002). Boys and literacy: Exploring the issues. London: Routledge / Falmer.
Moisan, C. (2011). Comment en finir avec l'échec scolaire: les mesures efficaces. Projet de rapport national de base de la France. www.oecd.org/fr/education/scolaire/ 49528429.pdf.
Mullis, I. V. S., Martin, M. O., Ruddock, G. J., O’Sullivan, C. Y., and Preuschoff, C. (2009). TIMSS 2011 Assessment Frameworks. Retrieved from http://timssandpirls.bc.edu/timss2011/downloads/TIMSS2011_Frameworks. pdf
Noel, S., and de Broucker, P. (2001). Intergenerational inequities: A comparative analysis of the influence of parents’ educational background on length of schooling and literacy skills. In W.
Hutmacher, D. Cochrane, and N. Bottani (Eds.), In Pursuit of Equity in Education: Using international indicators to compare equity policies (pp. 277–298). Dordrecht, The Netherlands: Kluwer Academic.
OECD (2016). PISA 2015 technical report. Paris: OECD.
OECD (2014). Equity, Excellence and Inclusiveness in Education: Policy lessons from around the world. Paris: OECD.
OECD. (2013). PISA 2012 Results: What makes schools successful? Resources, policies and practices (Vol. IV). PISA: OECD Publishing.
Perry, B. (2010). Exploring academic misconduct: Some insights into student behaviour. Active Learning in Higher Education, 11(2), 97–108. https://doi.org/10.1177/1469787410365657
Roth, B., Becker, N., Romekye, S., Schäfer, S., Domnick, F., and Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118–137.
Sirin, S. R. (2005). Socioeconomic status and student achievement: A meta-analytic review of research. Review of Educational Research, 75, 417–453.
Stanat, P. (2003). Schulleistungen von Jugendlichen mit Migrationshintergrund: Differenzierung deskriptiver Befunde aus PISA und PISA-E. In Deutsches PISAKonsortium (Ed.), PISA 2000.
Ein differenzierter Blick auf die Länder der Bundesrepublik Deutschland. Opladen: Leske und Budrich, pp. 243–260.
Schulz, K. (2005). Learning in complex organizations as practicing and reflecting: A model development and application from a theory of practice perspective. Journal of Workplace Learning,
17(8), 493–507. https://doi.org/10.1108/13665620510625363
Thien, L. M. (2016). Malaysian Students’ Performance in Mathematics Literacy in PISA from Gender and Socioeconomic Status Perspectives. Asia-Pacific Education Researcher, 25, 657–666.
Thomson, S. (2018). Achievement at school and socioeconomic background—an educational perspective. Science of Learning, 3(5), 1–2.
Turkheimer, E., Pettersson, E., and Horn, E. E. (2014). A phenotypic null hypothesis for the genetics of personality. Annual Review of Psychology, 65, 515–540.
Topcu, M. S., Erbilgin, E., and Arikan, 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.
Turmo, A. (2004). Scientific literacy and socio-economic background among 15-year-olds: A Nordic perspective. Scandinavian Journal of Educational Research, 48(3), 287–305.
Willms, J. D. (1999). Quality and inequality in children’s literacy: The effects on families, schools, and communities. In D. P. Keating and C. Hertzman (Eds.), Developmental Health and the Wealth of Nations: Social, biological, and educational dynamics (pp. 72–93). New York: Guilford Press.
Öğrencilerin Fen Bilimleri Başarılarını Etkileyen Faktörler [Factors affecting science achievement of science students in programme for International Students’ Achievement (PISA) in Turkey]. Eğitim ve Bilim, 34(152), 87–100.
Ayorech, Z., Krapohl, E., Plomin, R., and von Stumm, S. (2017). Genetic influence on intergenerational educational attainment. Psychological Science, 28, 1302–1310.
Baumert, J., Trautwein, U. and Artelt, C. (2003), Schulumwelten – institutionelle Bedingungen des Lehrens und Lernens, in: Deutsches PISA-Konsortium (Ed.), PISA 2000. Ein differenzierter Blick auf die Länder der Bundesrepublik Deutschland. Opladen: Leske und Budrich, pp. 261–331.
Benabou, R., Kramarz, F., and Prost, C. (2009). The French zones d'Education Prioritaires: Much ado about nothing? Economics of Education Review, 28, 345–356.
Boocock, S. S. (1972). An Introduction to the Sociology of Learning. Boston: Houghton Mifflin.
Bowles, S., and Nelson, V. I. (1974). The “inheritance of IQ” and the intergenerational reproduction of economic inequality. The Review of Economics and Statistics, 56, 39–51.
Blossfeld, H.-P., and Shavit, Y. (1993). Persisting barriers: Changes in educational opportunities in thirteen countries. In Y. Shavit and H.-P. Blossfeld (Eds.), Persistent Inequality (pp. 1–24).
Boulder, CO: Westview.
Bradley, R. H. and Corwyn, R. F. (2002). Socioeconomic Status and Child Development. Annual Review of Psychology, 53: 371–99.
Brandt, N. (2010). Chile: Climbing on giants’ shoulders: better schools for all Chilean children. OECD
Economics Department working papers, no. 784OECD Publishing. https://doi.org/10.1 787/5kmd41g7x9g0-en.
Caponera, E., and Losito, B. (2016). Context factors and student achievement in the IEA studies: evidence from TIMSS. Large-scale Assessments in Education: an IEA-ETS Research Institute Journal, 4(1), 1–22.
Calero, J. (2005). Spain: Country analytical report. Equity in Education Thematic Review. www.oecd.org/spain/38693078.pdf.
Clements, D. and Sarama, J. (2009). Learning and teaching early math: The learning trajectories approach.http://lst-iiep.iiep-unesco.org/cgibin/wwwi32.exe/[in=epidoc1.in]/?t2000=026–594/(100).
Ceylan, E. (2009). PISA 2006 sonuçlarına göre Türkiye’de fen okuryazarlığında düşük ve yüksek performans gösteren okullar arasındaki farklar [Differences between low-and high-performing schools in scientific literacy based on PISA 2006 results in Turkey]. Yüzüncü Yıl Üniversitesi
Eğitim Fakültesi Dergisi [ Yuzuncu Yıl University Journal of Education Faculty], 4(2), 55–75.
A. Shala, A. Grajcevci & F. Latifić: Does Socioeconomic Status Influence Achievement? An Analysis of the Performance of Kosovar Students on the 2015 and 2018 PISA Assessment 407
Deary, I., Strand, S., Smith, P., and Fernandes, C. (2007). Intelligence and educational achievement. Intelligence 35, 13–21.
Department of Education and Skills, Ireland. (2011). Overcoming school failure: Policies that work. National Report Ireland. www.oecd.org/education/school/49624509.pdf.
Entorf, H. and Minoiu, N. (2004): What a Difference Immigration Law Makes: PISA results, migration background, socioeconomic status and social mobility in Europe and traditional countries of immigration, Darmstadt Discussion Papers in Economics, No. 128, Technische Universität Darmstadt, Department of Law and Economics, Darmstadt.
Entwisle, D. R. and Astone, N. M. (1994). Some Practical Guidelines for Measuring Youth’s Race/Ethnicity and Socioeconomic Status. Child Development, 65, 1521–1540.
Glewwe, P. W., Hanushek, E. A., Humpage, S. D. and Ravina, R. (2011) School resources and educational outcomes in developing countries: A review of the literature from 1990 to 2011 (Working Paper No. 17554). Retrieved from http:www.nber.org/papers/w17554.
Güven, U. (2017). The Relationship between Testing Frequency and Student Achievement in Eighth- Grade Mathematics: An International Comparative Study Based on TIMSS 2011 (doctoral dissertation). Duquesne University, Pittsburgh, PA.
Güven, U. and Akçay, A. O. (in press). Trends of Homework in Mathematics: Comparative Research Based on TIMSS Study. International Journal of Instruction.
Heckman, J. J., and Rubinstein, Y. (2001). The importance of noncognitive skills: Lessons from the GED testing program. The American Economic Review, 91, 145–149.
Hauser, R. M. (1994). Measuring Socioeconomic Status in Studies of Child Development. Child Development, 65, 1541–1545.
Hanushek, E. A., and Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46(3), 607–668.
Haveman, R. H., and Wolfe, B. (1984). Schooling and Economic Well-Being: The Role of Non-Market Effects. Journal of Human Resources 19(3): 377–407.
Ho, S. C. E. (2013). Multilevel Analysis of the PISA Data: Insights for policy and practice. Hong Kong: Hong Kong Institute of Educational Research
Krawchuk, S. and K. Rust (2002) Sample Design. In Adams, R. and M. Wu (eds.), PISA 2000 Technical Report. OECD, Paris, pp. 39-56.
Ladd, H . F ., a nd F iske, E . B . ( 2009). T he D utch e xperience w ith w eighted s tudent f unding: some lessons for the U.S. Working paper series http://files.eric.ed.gov/fulltext/ED507402. pdf.
Ladd, H. F., Fiske, E. B., and Ruijs, N. (2009). Parental choice in the Netherlands: Growing concern about segregation. Prepared for School Choice and School Improvement: Research in state, district and community contexts. Vanderbilt University.
Letourneau, N. L., Duffett-Leger, L., Levac, L., Watson, B., and Young-Morris, C. (2013). Socioeconomic status and child development: A meta-analysis. Journal of Emotional and Behavioral Disorders, 21(3), 211–224. https://doi.org/10.1177/1063426611421007
Maynard, T. (2002). Boys and literacy: Exploring the issues. London: Routledge / Falmer.
Moisan, C. (2011). Comment en finir avec l'échec scolaire: les mesures efficaces. Projet de rapport national de base de la France. www.oecd.org/fr/education/scolaire/ 49528429.pdf.
Mullis, I. V. S., Martin, M. O., Ruddock, G. J., O’Sullivan, C. Y., and Preuschoff, C. (2009). TIMSS 2011 Assessment Frameworks. Retrieved from http://timssandpirls.bc.edu/timss2011/downloads/TIMSS2011_Frameworks. pdf
Noel, S., and de Broucker, P. (2001). Intergenerational inequities: A comparative analysis of the influence of parents’ educational background on length of schooling and literacy skills. In W.
Hutmacher, D. Cochrane, and N. Bottani (Eds.), In Pursuit of Equity in Education: Using international indicators to compare equity policies (pp. 277–298). Dordrecht, The Netherlands: Kluwer Academic.
OECD (2016). PISA 2015 technical report. Paris: OECD.
OECD (2014). Equity, Excellence and Inclusiveness in Education: Policy lessons from around the world. Paris: OECD.
OECD. (2013). PISA 2012 Results: What makes schools successful? Resources, policies and practices (Vol. IV). PISA: OECD Publishing.
Perry, B. (2010). Exploring academic misconduct: Some insights into student behaviour. Active Learning in Higher Education, 11(2), 97–108. https://doi.org/10.1177/1469787410365657
Roth, B., Becker, N., Romekye, S., Schäfer, S., Domnick, F., and Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118–137.
Sirin, S. R. (2005). Socioeconomic status and student achievement: A meta-analytic review of research. Review of Educational Research, 75, 417–453.
Stanat, P. (2003). Schulleistungen von Jugendlichen mit Migrationshintergrund: Differenzierung deskriptiver Befunde aus PISA und PISA-E. In Deutsches PISAKonsortium (Ed.), PISA 2000.
Ein differenzierter Blick auf die Länder der Bundesrepublik Deutschland. Opladen: Leske und Budrich, pp. 243–260.
Schulz, K. (2005). Learning in complex organizations as practicing and reflecting: A model development and application from a theory of practice perspective. Journal of Workplace Learning,
17(8), 493–507. https://doi.org/10.1108/13665620510625363
Thien, L. M. (2016). Malaysian Students’ Performance in Mathematics Literacy in PISA from Gender and Socioeconomic Status Perspectives. Asia-Pacific Education Researcher, 25, 657–666.
Thomson, S. (2018). Achievement at school and socioeconomic background—an educational perspective. Science of Learning, 3(5), 1–2.
Turkheimer, E., Pettersson, E., and Horn, E. E. (2014). A phenotypic null hypothesis for the genetics of personality. Annual Review of Psychology, 65, 515–540.
Topcu, M. S., Erbilgin, E., and Arikan, 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.
Turmo, A. (2004). Scientific literacy and socio-economic background among 15-year-olds: A Nordic perspective. Scandinavian Journal of Educational Research, 48(3), 287–305.
Willms, J. D. (1999). Quality and inequality in children’s literacy: The effects on families, schools, and communities. In D. P. Keating and C. Hertzman (Eds.), Developmental Health and the Wealth of Nations: Social, biological, and educational dynamics (pp. 72–93). New York: Guilford Press.
Published
2021-12-13
How to Cite
Shala A., Grajcevci A., & Latifi F. (2021). Does Socioeconomic Status Influence Achievement? An analysis of the Performance of Kosovar Students on the 2015 and 2018 PISA Assessment. Journal of Elementary Education, 14(4), 393-408. https://doi.org/10.18690/rei.14.4.393-408.2021
Issue
Section
Scientific Articles
Copyright (c) 2021 Arif Shala, Albulene Grajcevci, Fadil Latifi
This work is licensed under a Creative Commons Attribution 4.0 International License.