Improving odds for immigrant students best performance: understanding school ethnic composition effect in the Portuguese primary schools using multilevel analysis
Author(s):
Teresa Seabra (submitting) Helena Carvalho (presenting)
Patrícia Ávila (presenting)
Conference:
ECER 2017
Format:
Paper

Session Information

09 SES 04 A, Investigating School Composition Effects

Paper Session

Time:
2017-08-23
09:00-10:30
Room:
W3.11
Chair:
Kajsa Yang Hansen

Contribution

Scientific interest concerning the impact of social and ethnic composition of schools – in other words, the school’s compositional effect – on student performance has intensified throughout the current century, as the subject has been vastly explored by researchers in various national contexts. These effects have usually been studied taking student outcomes as measured by standardized tests on different school subjects and levels of education.

Schnepf (2007) uses PISA results to compare the impact of immigrant concentration in schools on student outcomes in ten countries, finding that both the direction and the effect size differ across national contexts. In some countries (Australia and Canada), immigrant concentration has a positive effect on student outcomes; in other countries (Switzerland, Germany, New Zealand and France) the effect is negative; and in some other countries (Netherlands, Sweden, United Kingdom and United States of America) the effect is not statistically significant. The cross-country variation is evident in research, according to the national context on which the study was developed but also to the ethnic groups involved, as the effect may differ for native students and for those with an immigrant background.

In most research, high immigrant concentration in schools has negative effects on the outcomes of all students, regardless of their status as immigrants or their social class (Agirdag, Van Houtte & Van Avermaet, 2012; Jensen & Rasmussen, 2011; Van der Slik, Driessen & De Bot, 2006). Despite this, the effects are particularly negative for students of immigrant origins, and within these, for those who are black (Lleras, 2008). Another study also concerning the United States of America (Goldsmith, 2003) had previously pointed towards the lack of benefits from concentrating black students in certain schools, while curiously noting that the results of Hispanic and Latino students are higher in schools where they are the majority. Similarly, Fekjaer and Birkelund (2007) disagree that the impact of ethnic composition in schools is consistently negative for student outcomes. They analyse higher education results of students who attended secondary education in schools with different degrees of ethnic diversity, and find that the effect of diversity is small but positive when parents’ educational background is controlled.

In Portugal we conducted a research using an extensive database with the results of fourth grade students in the Mathematics national standardized tests in the Lisbon Metropolitan Area (LMA) for the school year 2009/10. We intent to reveal what are the main factors behind students results in LMA public schools giving special attention to the effect of ethnicity, considered both at the student level (its national origin) and at the school level (the schools ethnic composition).

Research questions:

Does the schools’ ethnic composition has an effect on students’ Mathematics scores? 

Does the schools’ ethnic composition effect on Mathematics scores stand when students’ gender, social and ethnic origins are taken into account? Does this effect stand when the schools’ social composition is taken into account?

How does the schools’ ethnic composition moderate the relation between having/not having an immigrant background and students’ Mathematics scores, when the socio-economic status (SES) of both students and schools is controlled? 

Method

Participants Universe of students on the 4th grade of the first cycle from public schools in the Lisbon Metropolitan Area. The data analyses include 16 269 students and 417 schools. Measures We developed a multilevel research design which involved both individual level variables (level 1) and school level variables (level 2). The dependent variable (measured at level 1) was the Mathematic test score achieved by the students in the National Exams. The independents variables covered the two levels:  Level 1 – Ethnicity (immigrant origin), socioeconomic status (SES) and gender (as a control variable);  Level 2 – Ethnic composition (percentage of foreigners), school SES and school size (as a control variable). Analytical Strategy We used multilevel linear regression to account for the nested data (Goldstein, 1999; Snijders and Bosker 1999). The multilevel analyses were carried out using Linear Mixed Models (SPSS 23.0). To explore our research questions several multilevel models were tested:  Model 1 analyzed the effect of ethnic composition of schools on students’ Mathematics scores in the assessment tests;  Model 2 analyzed the effect of ethnic composition of schools on students’ Mathematics score, taking into account micro-level variables: ethnicity (immigrant origin), socioeconomic status (SES) and gender and school size (control variable);  Model 3 analyzed the effect of ethnic composition of schools on students’ Mathematics score, taking into account micro-level variables: ethnicity (immigrant origin), socioeconomic status (SES) and gender, and macro-level variables: socioeconomic composition of schools and school size (control variable);  Model 4 analyzed the cross-level interaction effect of ethnic composition of schools on the relation between ethnicity (immigrant origin) and students’ Mathematics score, controlling both micro-level variables (socioeconomic status (SES) and gender) and macro-level variables (socioeconomic composition of schools and school size). The 4 models were compared using changes in deviance statistics.

Expected Outcomes

 Ethnic composition of schools has a significant effect on students’ Mathematics score. The higher the % of immigrant students in schools, the worse students grades;  Ethnic composition of schools has a significant effect even when the micro-level variables (immigrant origin, socioeconomic status and gender) are controlled;  When taking into account also school SES, the ethnic composition of schools no longer has a significant effect on students’ Mathematics score, but the micro-level variables (immigrant origin, socioeconomic status and gender) remain with significant effect;  The moderator effect of the ethnic composition of schools on the relation between ethnicity (immigrant origin) and students’ Mathematics score is significant even when the micro-level variables (socioeconomic status and gender) and the macro-level variables (School SES and school size) are controlled. These results suggest that although the effect of school ethnic composition is not significant when all the above mentioned level 1 and level 2 variables are included in the model (model 3), the relation between ethnicity (immigrant origin) and students’ Mathematics score can only be fully understand if we consider the ethnic composition of schools (model 4). We will explore this moderator effect analysing the way school ethnic composition affects the relation between ethnicity (immigrant origin) and students’ Mathematics score.

References

Agirdag, O., M. Van Houtte & P. Van Avermaet (2012). Why does the ethnic and socio-economic composition of schools influence Math achievement? The role of sense of futility and futility culture. European Sociological Review, 28-3, 366-378. Jensen, P., A. Rasmussen (2011). The effect of Immigrant Concentration in Schools on native and Immigrant Children´s Reading and Maths Skils. Economics of Education Review, 30 (6), 1503-1515. Lleras, Ch. (2008). Race, racial Concentration, and the dynamics of educational Inequality Across urban and Suburban Schools. American Educational Research Journal, 45 (4), 886-912. Fekjaer e Birkelund (2007). Does the Ethnic Composition of Upper Secondary Schools Influence Educational Achievement and Attainment? A multilevel Analysis of Norwegian Case. European Sociological Review, 23 (3), 309-323. Goldsmith, Pat António (2003). All segregation is not equal: the impact of latino and black school composition. Sociological Perspectives, 46 (1), 83-105. Goldstein, H. (1999). Multilevel statistical models. London: Institute of Education, Multilevel Models Project, April 1999, Edward Arnold. Schnepf, S. V. (2007). Immigrants´educational Disadvantage: An examination across ten Countries and Three Surveys. Journal of Population Economics, 20, 527-545. Snijders, T.A.B. e R.J. Bosker (1999). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. Sage. Van der Slik, F., G. Driessen e K. De Bot (2006). Ethnic and Socioeconomic Class Composition and language Proficiency: a Longitudinal Multilevel Examination in Duch Elementary Schools. European Sociological Review, 22 (3), 293-308.

Author Information

Teresa Seabra (submitting)
Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal
Helena Carvalho (presenting)
ISCTE-IUL
Department of Social Research Methods
Lisbon
Patrícia Ávila (presenting)
Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal

Update Modus of this Database

The current conference programme can be browsed in the conference management system (conftool) and, closer to the conference, in the conference app.
This database will be updated with the conference data after ECER. 

Search the ECER Programme

  • Search for keywords and phrases in "Text Search"
  • Restrict in which part of the abstracts to search in "Where to search"
  • Search for authors and in the respective field.
  • For planning your conference attendance, please use the conference app, which will be issued some weeks before the conference and the conference agenda provided in conftool.
  • If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.