Extract
[...] The school composition variables covered academic, socio-cultural, linguistic, and gender composition. Level 1 specific variables include French results, cultural capital, linguistic characteristics, self-image, and motivation. Level 2 variables concern the academic, cultural, linguistic, and gender composition of schools. The end-of-year score is the explained variable by the modeling and the beginning-of-year variable is part of the control variables of the statistical modeling. This modeling is of a multi-level type: it integrates both variables at the level of the student and at the level of his school, in order to distinguish individual effects and composition effects. [...]
[...] In terms of social and academic aggregation policies, a strong social aggregation is associated with greater dispersion of performance and a more marked difference between advantaged and disadvantaged students, although correlations are not always significant. Academic aggregation also presents a higher dispersion of performance. In fact, the correlations between these two dimensions show that in countries where social and academic aggregation is high, the performance gaps between students of different socio-economic statuses are more pronounced. Furthermore, these countries also have a lower average score on the PISA test. [...]
[...] Decision-makers should therefore strive to reduce this degree of aggregation, in other words, to reduce segregation between schools. V. Dupriez and X. Dumay (2011), "The quasi-school markets: to the benefit of whom?",French Review of Pedagogy, 2011/3 (n° 176), p. 83-100. Dupriez and Dumay (2011) examine the concept of 'quasi-school market' and its impact on students in OECD countries. They investigate how school autonomy and competition influence student segregation between schools and educational inequalities. They also evaluate whether this model benefits all students equally or if it benefits certain groups more than others. [...]
[...] This commodification is likely to exacerbate school segregation and inequalities, without guaranteeing equal learning outcomes for all students, regardless of their social situation. Methodology The authors adopted a quantitative research methodology through regression analyses. Two types of methodology were used. First, regression analyses were performed in 31 countries to study the relationships between school choice indicators, social and academic segregation, and inequalities in school results. The age at which a first orientation towards vocational or professional education is possible was included in the analysis to explain segregation, as well as income inequality. [...]
[...] (2010) examine the segregation between schools and its effects on inequalities in results. They address how the composition of schools, particularly the characteristics of the families of students enrolled, influences the performance of these students. The authors also discuss the institutional conditions that promote or hinder the emergence of these composition effects, particularly in education systems characterized by a quasi-market where families have free choice of school and where schools enjoy a high degree of autonomy. Methodology The authors used a quantitative data methodology. [...]
