This paper attempts to study how school and classroom characteristics shape educational inequalities in Luxembourg. Mainly focusing on unequal distributions of educational resources and opportunities, educational inequality has been in the spotlight of educational sociology. The concept of educational inequality is framed around “systematic variations in several aspects of educational attainment structured by ascribed attributes of students derived from their social group memberships, such as gender, ethnicity, immigrant background and class (axes of inequality)” (Gross et al., 2016, p. 12). Explicitly, a study of variation in educational attainment, according to Jacobs (1996), might embody a disparity in educational trajectories, educational experiences and outcomes (including gained competencies, earned grades and certificates) among students from diverse backgrounds. Unfortunately, educational inequality related to certain axes such as social origin, race, or ethnicity appears to be rather persistent. Thus, it is still a relevant concern in many modern societies.

A prominent study conducted by James S. Coleman and his colleagues (1966) on the examination of schools and student achievement might be considered as a turning-point in the field of educational inequality. The conclusions of the renowned researchers stressed that the primary drivers of student performance are student demographics such as familial resources and race, and also the influence of peer composition in classrooms, rather than the school inputs including school quality and teacher qualifications. These conclusions on the highly underlined influence of a student’s parental resources had a profound impact in the field and shaped the discourse towards general inequality theories on social and cultural factors and on how educational systems reproduce socioeconomic inequalities from the perspectives of Boudon (1974), Bourdieu (1986), and Bourdieu and Passeron (1977). Meanwhile, the conclusions on mostly negligible school effects resulted in a rise of studies in the field of school effectiveness research to unveil effective characteristics of schools on educational achievement with the essential aim of diminishing the achievement gaps of disadvantaged students (Angus, 1993; Burušić et al., 2016; Scheerens, 2016). Consequently, many researchers have hitherto contributed to our modern understanding of how educational inequality perpetuated either by the contributions of individual social, economic, and cultural factors, or by higher level influences such as social compositions in schools and other school inputs regarding many aspects.

Regarding the endurance of educational inequality throughout time and geography, Luxembourg, as one of the most diverse countries in Europe, has its own assets and complications. On the positive sides, its commitment to promoting educational equality, its attempts to provide high-quality school environments, and its society accommodating more than 170 nationalities while operating with three official languages (Luxembourg Ministry of Education, Children and Youth, 2021) are some examples of its unique assets. Yet, as also highlighted in some international and national educational reports (OECD, 2019, 2021; SCRIPT & LUCET, 2018), in this diverse and wealthy country, students from distinct backgrounds still face some common struggles to keep up with their peers from advantageous backgrounds when their gender, language proficiencies, and socioeconomic backgrounds are taken into consideration (Hadjar et al., 2015, 2018). Within the framework of a ministerial project aiming to ensure the continuance of providing equal educational opportunities to students in primary schools of Luxembourg, this study taps on longitudinal patterns of classroom and school impacts on educational inequality. Relying on the results of this study, not only will educational policy makers of the country have grounded scientific evidence to continue to work towards developing policies that can potentially reduce these educational disparities in early stages of Luxembourgish primary schooling, but also the researchers might unveil modern mechanisms to contribute to the field of school effectiveness research and sociology of education.

This study utilizes a multilevel trend modelling approach with an aim to examine the trend of moderation effects of various classroom compositions, teacher-student ratio and social index on the relationship between different axes of inequality (gender, socioeconomic background, and language) and grade-3 (G3) students’ academic achievement in Luxembourg over 6 consecutive years, while accounting for the nested structure of the dataset. To accomplish this aim, the data used in this study has been merged from different census data sources provided by the Ministry of Education, Children and Youth, Luxembourg Center for Educational Testing, and Luxembourg Institute of Socio-Economic Research, along with standardized test data from the national education monitoring, called ÉpStan, within the framework of a ministerial project. With its nested structure, the final census dataset consists of 4052-4794 students in G3 within 334-392 classrooms operating under 145-157 schools from 94-99 communes in Luxembourg between 2014 and 2019. Accordingly, Classroom-ID, School-ID and Commune-ID become the clustering variables. Year-ID is utilized to separately conduct multilevel models per year. The outcome variables of interest are the standardized math and German reading comprehension scores in grade 3. While the individual level predictors are the demographics of students such as gender, socioeconomic status (SES), and language spoken at home, the classroom compositions are represented by female percentage, average SES, and percentage of non-Luxembourgish-or-German speakers (nLGs) at home, created by aggregating the individual level demographics onto the classroom level. The school level predictors are school student population and teacher-student (TS) ratio at a given year provided by the ministry. Lastly, social index (Fazekas, 2012) is utilized as a commune-level proxy for the additional monetary compensations provided to communes to tackle educational inequality in Luxembourg. Using Stata 17, six models per subject-specific score are run with maximum likelihood and available case analysis. The fitness of each model is assessed using associated residual plots and Akaike Information Criterion. Additionally, for each model in the analyses, the intraclass correlations (ICC) are calculated to represent the proportion of variance in the corresponding outcome variable that is explained by the group-level variations. For math scores, they ranged between <1% to 2%, 2.8% to 4.6%, and between 5% to 9%, respectively on the commune, school and classroom levels. For German scores, ICCs ranged between 1% to 3.1%, 3.1% to 6.1%, and between 4.8% to 9.7%, at the commune, school and classroom levels, respectively.

The main individual effects pointed significant advantages on three axes of inequality consistently throughout the years: gender (males in math and females in German), SES (more affluent students), and language (Luxembourgish or German speaking students). The results from cross-level interactions between individual-level axes of inequalities and classroom, school and commune level variables are intriguing. On math scores, the significant disadvantage of female students is moderated positively by high TS-ratio schools (2016 and 2017) and by more commune-level monetary compensations (2017). The significant advantage of coming from more affluent families is amplified by high-average-SES classrooms (2015, 2016, 2017, and 2019), but negatively moderated by high TS-ratio schools (2017) and by more commune-level monetary compensations (2018 and 2019). The significant disadvantage of students who are nLGs is reduced by high-percentage-nLGs classrooms (2015) and by more commune-level monetary compensations (2016). Regarding German reading comprehension scores, the significant disadvantage of male students is moderated positively by more commune-level monetary compensations (2018). The significant advantage of high SES students is amplified also for German scores by high-average-SES classrooms (2015, 2016, 2018, and 2019), but negatively moderated by high TS-ratio schools (2017) and by more commune-level monetary compensations (2019). The significant disadvantage of nLGs students is reduced by high-percentage-nLGs classrooms (2015) and by more commune-level monetary compensations (2014, 2016, and 2019). Consequently, the multilevel trend analyses unveiled two important aspects: achievement-gap reducing and amplifying mechanisms. More commune-level monetary compensations are predicted to narrow disparities in achievement scores based on all axes of inequality. While high TS-ratio schools reduce gender and SES achievement gaps for math, they diminish only SES achievement gaps for German scores. Moreover, homogenous classroom composition based on language appears to lessen the language achievement gap for both scores. Contrarily, homogenous SES classroom composition appears to amplify student SES achievement gaps for both scores.

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