Educational Differentiation Policies and the Performance of Disadvantaged Students Across OECD Countries
Author(s):
Alba Castejon-Company (presenting / submitting) Adrian Zancajo (presenting)
Conference:
ECER 2014
Format:
Paper

Session Information

09 SES 07 A, Findings from Large-Scale Assessments: Students' Socio-Cultural Background and Deviant Behavior as Challenges for Assessments and Education

Paper Session

Time:
2014-09-03
17:15-18:45
Room:
B010 Anfiteatro
Chair:
Sarah Howie

Contribution

Based on data from PISA, this paper explores the relationship between the academic performance of students from disadvantaged backgrounds and the students’ differentiation models of the educational systems of OECD countries.

As confirmed by numerous studies, students’ socioeconomic background is a variable that noticeably affects students’ educational outcomes (e.g. Blanden and Gregg, 2004; Caro, McDonald and Willms, 2009; Dupriez and Dumay, 2006; Gorard and Smith, 2004; Field, Kuczera and Pont, 2007; OECD, 2007; 2010; 2011; Sirin, 2005; Tieben and Wolbers, 2010). Moreover, differences in outcomes among students according to their socioeconomic status are considered as an indicator of equality of opportunities in educational systems (Field, Kuckzera and Pont, 2007).

There are aspects of educational policy that can reduce or increase the academic gap between disadvantaged students and their more advantaged peers, such as the strategies for managing the students’ heterogeneity. Some studies suggest that educational inequalities are largely determined by the structure of educational systems in terms of their level of differentiation, even more so than by inequalities in society (Dupriez & Dumay, 2006).

Based on differentiation policies, Mons (2004) proposes a classification of educational systems into four categories, which the author terms as “heterogeneity management models”. The first category refers to the separation model, which is characterised by the existence of a short common core curriculum, grouping students according to ability, and generalised use of grade retention in managing students’ progress. The second model is the uniform integration model characterized by a longer common core curriculum but with a high incidence of grade retention and the possibility of forming ability groups according to students’ abilities, although often not in an official way. The à-la-carte integration model is the third to be defined by Mons. Its main features are a long common core curriculum, reduced grade retention, flexible ability grouping in secondary school, and an extensive use of individualised teaching. Finally, the author delineates the individualised integration model, which has a long common core curriculum, automatic grade promotion of students, heterogeneous classrooms, and a generalised use of individualised teaching.

There are several studies that examine the impact of the types of differentiation policies on educational equality. Duru-Bellat, Mons and Suchaut (2004) conclude that a higher level of differentiation in educational systems reduces social equality. Furthermore, they support that countries with high levels of educational differentiation obtain lower score averages in PISA 2000 than countries with more comprehensive educational systems. 

According to Erickson and Jonsson (1996), this is because families with more resources tend to choose more academic tracks for their children. The later the moment at which a track is selected, the lower the level of what the author defines as self-selection by families with more resources. In this sense, in the case of Romania, Malamud and Pop-Eleches (2011) show how educational reform that postponed the moment of choice between academic and vocational tracks significantly increased the number of students from rural areas – or from families with lower educational levels – that were candidates for progressing to higher education levels.

Thus the main objective of this article is to understand the impact of educational differentiation policies on students’ academic performance. More specifically, we focus on students from disadvantaged backgrounds, paying special attention on students who achieve high levels of academic performance and students from such backgrounds that obtain poor results. Therefore, the research question is the following:

  • To what extent do the models of educational differentiation determine the presence of disadvantaged high achievers and of disadvantaged low achievers?

Method

Data: The data come from PISA. Since our research is mainly based on a comparative view of disadvantaged students OECD countries are selected, to ensure a similar level of development of their educational systems. It should be noted that although Mexico and Turkey are part of the OECD, these two countries have been excluded from the analysis because the rate of schooling of the population aged 15 years, which is the target population in PISA, is lower than 90%. Classification of disadvantaged students according to their academic performance: One of the key methodological issues is the identification and classification of socially disadvantaged students. We use here a methodology based on the so-called national definition used in the report “Against the Odds” (OECD, 2011). First, it is necessary to define the set of socially disadvantaged students. They are taken to be those positioned in the lowest quartile of the distribution index of Economic, Social, and Cultural Status (ESCS) within each country. Similarly we divide the distribution of scores into quartiles for each of the analysed countries. From this division, two groups of students can be identified: - Disadvantaged low achievers. These students are located in the lowest quartile of the distribution of the ESCS index and obtained a score that is in the lowest quartile of the distribution for their country. - Disadvantaged high achievers. These students are also positioned in the lowest quartile of the distribution of the ESCS index, but they achieve scores that are located in the upper quartile of the distribution for their country. Classification of educational systems: A second notable methodological issue is the process of classifying the analysed countries in terms of their different educational differentiation models. In order to group OECD countries into the four categories proposed by Mons (2004), we utilise the methodology employed by Dupriez, Dumay, and Vause (2008). This method consists of classifying the different educational systems according to a set of variables that serves as a proxy for some of the key features of each category, using data from PISA.

Expected Outcomes

First, we analyse the average percentages of disadvantaged high achievers and of disadvantaged low achievers in each of these categories of countries, which is greater for the three integration models than for the separation model. The greatest difference is observed between the separation model and the individualised integration model. The ANOVA test shows that there are some significant differences between groups. Analysing these differences in percentages of disadvantaged high achievers across the four models by using Tukey’s post-hoc test for comparison of means, we see that a significant difference only exists between the separation model and the individualised integration model. Even though they are not significant in the other cases, the greatest differences are observed between the individualised integration model and all of the other models. Subsequently, we have carried out an analysis of disadvantaged low achievers. Here we observe that the separation model presents a higher average percentage of disadvantaged low achievers and the individualised integration model is positioned with a lower percentage of this type of students. Also the ANOVA test shows that, as a minimum, there are significant differences between some of the groups. As in the case of disadvantaged high achievers, in the comparison of means for the percentage of disadvantaged low achievers, the only significant statistical difference is between the separation model and the individualised integration model. Finally, we consider whether there is a relationship between the percentages of these subgroups in each of the analysed countries, and the extent to which this corresponds to the different heterogeneity management models. It is worth highlighting the negative relationship demonstrated between the percentage of disadvantaged low achievers and the percentage of disadvantaged high achievers in all analysed countries. The negative relationship between the percentages of these two types of students is significant but not necessarily determinant.

References

Blanden, J. & Gregg, P. (2004). Family Income and Educational Attainment: A Review of Approaches and Evidence for Britain. CMPO Working Paper Series No. 04/101. Caro, D., McDonald, J.T. & Willms, J.D. (2009). Socio‐economic Status and Academic Achievement Trajectories from Childhood to Adolescence. Canadian Journal of Education, 32(3), 558‐590. Coleman, J., Campbell, E., Hobson, C., McPartland, J., Mood, A., Weinfeld, F., & York, R. (1966) Equality of educational opportunity (Washington DC, U.S. Government Printing Office) Dupriez, V. & Dumay, X. (2006), Inequalities in school systems: effect of school structure or of society structure?, Comparative Education, 42(2), 243 - 260. Duppriez, V., Dumay, X., & Vause, A. (2008). How Do School Systems Manage Pupils’ Heterogeneity?. Comparative Education Review, 52, (2). Duru-Bellat, M., Mons, N. & Suchaut, B. (2004) Caractéristiques des systèmes éducatifs et compétences des jeunes à 15 ans, Les Cahiers de l’Iredu, 66. Erikson, R. & Jonsson, J.O. (1996) Explaining class inequality in education: The Swedish test case, in: R. Erikson & J.O. Jonsson (Eds), Can education be equalized? (Boulder CO, Westview Press). Field, S., Kuczera, M. & Pont, B. (2007) No More Failures: Ten Steps to Equity in Education (París, OECD). Gorard, S. & Smith, E. (2004), An international comparison of equity in education Systems, Comparative education, 40 (1), 15-28. Malamud, O. & Pop-Elches, C. (2011). School tracking and access to higher education among disadvantaged groups. NBER Working Paper Series, 16914. Mons, N. (2004) De l'école unifiée aux écoles plurielles : évaluation internationale des politiques de différenciation et de diversification de l'offre éducative. (Thesis. Université de Bourgogne). OECD (2007) Understanding the Social Outcomes of Learning (Paris, OECD). OECD (2010) PISA 2009 Results: Overcoming Social Background: Equity in Learning opportunities and Outcomes. Vol II. (Paris, OECD). OCDE. (2011). Against the Odds. Disadvantaged students who succeed in school. (Paris, OECD). OCDE (2012) Equity and quality education – Supporting disadvantaged students and schools. Executive summary. (Paris, OECD). Sirin, S. R. (2005). Socioeconomic status and academic achievement: A metaanalytic review of research. Review of Educational Research. 75(3), 417 - 453. Tieben N. and Wolbers, M. (2010). Success and failure in secondary education: socio‐economic background effects on secondary school outcome in the Netherlands, 1927–1998. British Journal of Sociology of Education. 31(3), 277-290.

Author Information

Alba Castejon-Company (presenting / submitting)
Universitat Autònoma de Barcelona
Pedagogia Sistemàtica i Social
Bellaterra (Cerdanyola del Vallès), Barcelona
Adrian Zancajo (presenting)
Universitat Autònoma de Barcelona, Spain

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