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See detailSchool tracking in Luxembourg: the longitudinal impact of student characteristics and school composition
Pit-Ten Cate, Ineke UL; Ottenbacher, Martha UL; Alieva, Aigul et al

Scientific Conference (2022, December 05)

Research question: The current study aimed to investigate the influence of student and school level factors on school tracking in secondary education. We were especially interested in the association ... [more ▼]

Research question: The current study aimed to investigate the influence of student and school level factors on school tracking in secondary education. We were especially interested in the association between student characteristics and school composition in Grade 3 and school track in Grade 9. Data source: Data were collected as part of the Luxembourg school monitoring programme “Épreuves Standardisées” (ÉpStan; Fischbach et al., 2014). The study cohort include all students enrolled in the Luxembourg public education system in Grade 3 in November 2013 combined with data from the same students in Grade 9 in November 2017-2019 for students following advanced or regular educational pathways, completed with data from November 2020 and 2021 for students that repeated once or twice (N≈3600). Theoretical approach: The study draws upon theoretical frameworks and empirical findings (e.g., Boudon, 1974; Bourdieu, 1984), that have demonstrated students´ socio-demographic characteristics are associated with (dis)advantages for specific groups of students in education systems as well as more recent work focusing on school composition (e.g., Baumert et al., 2006), especially as tracked school systems are known to be prone to social segregation (e.g., Hadjar & Gross, 2016). To date, most research on school segregation in tracked education systems such as Luxembourg has focused on individual student´s characteristics. However, with increasing heterogeneity of student cohorts and known differences in educational opportunities related to the social and ethnic composition of the school’s student body (e.g., Thrupp et al., 2002), the current research extents the existing literature by considering both individual (including prior academic achievement and socio-demographic characteristics) and school level factors (mean academic level and percentage of students from lower socio-economic and migration background) in predicting school track placement. Main findings: Results of a multilevel random effect logistic regression analysis in which we estimated marginal effects on the probability to be placed in the highest, middle or lowest track in Luxembourg show that even after controlling for student´s academic achievement, track placement is affected by the gender and socio-economic background of the student, whereby boys and students from low SES families have less chance to be placed in the highest track. The association with socio-economic background is not only visible on the student level but also on school level, whereby students attending primary schools with a higher percentage of low SES families have less chance to be orientated to the higher track compared to the middle track, regardless of the student´ individual academic performance. [less ▲]

Detailed reference viewed: 105 (13 UL)
Peer Reviewed
See detailSchool Segregation in Primary and Secondary Education in Luxembourg: Track Placement and Academic Achievement
Pit-Ten Cate, Ineke UL; Hadjar, Andreas UL; Alieva, Aigul et al

Scientific Conference (2022, November 09)

Known as a highly stratified education system with early tracking (similar to Dutch, German, Austrian, and German-speaking Swiss systems), Luxembourg features additional properties that add to its ... [more ▼]

Known as a highly stratified education system with early tracking (similar to Dutch, German, Austrian, and German-speaking Swiss systems), Luxembourg features additional properties that add to its complexity in the educational realm (Backes & Hadjar, 2017). It is a simultaneously multilingual system that also has the largest share of students born outside of Luxembourg or parents born abroad. While most migrants come from within Europe, they frequently come from either a particularly high or low socio-economic background. It has been scientifically established that the educational inequalities in Luxembourg are driven mostly by social origin and immigration/language background. Gender is another critical dimension of disadvantage; for example, boys are less motivated to obtain higher education than girls (Hadjar, Scharf, & Hascher, 2021). In addition, gender often intersects with other factors such as immigrant background in shaping disadvantages. However, evidence shows that – beyond individual background characteristics – schools’ social composition also perpetuates inequalities in student achievement (Martins & Veiga, 2010). Therefore, we focus on the role of school-level segregation on student’s academic outcomes over time using data of a longitudinal cohort from the School Monitoring Programme (Éprueve Standardisée (ÉpStan)) with 5097 students in Grade 3 observed in 2013 and later in Grade 9 observed in 2019 (regular pathways) and 2020 and 2021 (irregular pathways, i.e., class repetitions). School segregation is an aggregate measure of the proportion of students who belong to low socio-economic background and the proportion of students born abroad and/or do not speak instruction language at home. Our contribution aims to provide insights into the following questions: 1. Does school-level segregation in primary education (G3) predict student’s track placement in secondary education? 2. Does school-level segregation in primary education (G3) predict student’s math and German achievement in secondary education (G9)? 3. How strongly are achievement outcomes in G9 correlated with within- and between-track segregation in G9? The findings will serve as a complementary base for tailored policy making with respect to the long-term impact of school composition for teaching and learning, especially within a tracked school system. References Becker, S., & Hadjar, A. (2017). Educational trajectories through secondary education in Luxembourg: How does permeability affect educational inequalities? Schweizerische Zeitschrift Für Bildungswissenschaften, 39(3), 437–460. https://doi.org/10.25656/01:16659 Hadjar, A., Scharf, J., & Hascher, T. (2021). Who aspires to higher education? Axes of inequality, values of education and higher education aspirations in secondary schools in Luxembourg and the Swiss Canton of Bern. European Journal of Education, 56(1), 9–26. https://doi.org/10.1111/ejed.12435 Martins, L., & Veiga, P. (2010). Do inequalities in parents’ education play an important role in PISA students’ mathematics achievement test score disparities? Economics of Education Review, 29(6), 1016–1033. https://doi.org/10.1016/j.econedurev.2010.05.001 [less ▲]

Detailed reference viewed: 44 (7 UL)