Educational Expectation Gaps Between Second-Generation Immigrant and Ethnic Majority Students in a Comparative Perspective: The Moderating Role of Educational Tracking

Abstract

This paper investigates the influence of educational tracking on immigrant educational expectation gaps in Sweden, England, the Netherlands, and Germany. To account for heterogeneity in immigrant children's origin countries, this paper additionally focuses on the educational selectivity of immigrant parents. The article argues that with a greater degree of tracking, students receive stronger track signals about their ability and their future opportunities, which should reduce the influence of immigrant parents’ aspirations and mitigate immigrant students’ lower responsiveness to school ability. As a result, immigrant students in countries with a high degree of tracking should have less inflated expectations that are more similar to ethnic majority students. Additionally, the moderating effect that tracking can have on the influence of parental aspirations on immigrant students’ educational expectations should mitigate the beneficial effect of immigrant parents’ selectivity in highly versus lowly tracked countries. Findings based on two waves of the CILS4EU data reveal that second-generation immigrant students have higher educational expectations than ethnic majority students in all countries except Germany. No significant differences are found relating to parents’ educational selectivity. The results support the assumption that stronger track signals in countries with a higher degree of tracking lead to higher responsiveness to school ability among second-generation immigrant students. No support is found for a reduced influence of parental aspirations on the immigrant expectation gap in countries with a higher tracking degree. This study contributes to research on immigrant expectation gaps by highlighting the specific mechanisms through which tracking influences operate.

Keywords

educational expectations immigrant selectivity ability tracking immigrant children cross-national comparison

Introduction

Studying educational trajectories reveals that immigrant children in many European countries are more likely than comparable ethnic majority children to continue in upper academic tracks (Heath and Brinbaum 2014b). These “ethnic premia” are assumed to relate back to higher ambitions among immigrant children, which potentially function to compensate for their disadvantaged starting positions (Jackson, Jonsson, and Rudolphi 2012; Heath and Brinbaum 2014b). Indeed, the desire for higher education among immigrant versus ethnic majority students appears uniformly high across Europe (Stanat, Segeritz, and Christensen 2010). However, comparisons of students’ expectations of the education degree they will attain in the future show that these differences not only vary across countries (Minelo and Barban 2012; D’hondt et al. 2016; Feliciano and Lanuza 2016; Fernández-Reino 2016), but also that significant heterogeneity between the country of origin groups exists (Teney, Devleeshouwer, and Hanquinet 2013; Friberg 2019; Hadjar and Scharf 2019).

The focus on students’ educational expectations is crucial because these reflect external conditions created by the opportunity structure an individual is confronted with (Kerckhoff 1976; Mickelson 1989; Reynolds and Pemberton 2001; Morgan 2007). Expectations also represent a realistic appraisal of future prospects and are therefore seen as being relevant in guiding behavior (Haller 1968; Kerckhoff 1976; Mickelson 1989), which in this context has repercussions for an individual's educational attainment (Hanson 1994; Beal and Crockett 2010) and achievement (Mickelson 1990; D’hondt et al. 2016).¹ Students’ ambitions become more realistic during adolescence when ideal preferences are increasingly compromised by inaccessible options and restricted by abilities, home resources, or other perceived barriers (Gottfredson and Lapan 1997).

Structural constraints are, thus, an important consideration when seeking to understand the formation of educational expectations (Kerckhoff 1976), especially between different groups. Particularly educational tracking—a term used to describe the division of students into different instructional groups according to their ability level (Hallinan 2000)—is one structural barrier that is repeatedly associated with educational outcomes. Tracking has been linked to channeling effects on students’ expectations: In highly tracked countries, educational expectations are found to develop more realistically and match more closely with eventual university attendance (Buchmann and Dalton 2002; Buchmann and Park 2009). For students with an immigrant background specifically, the tracking degree has been linked to the degree of disadvantage that they face compared to ethnic majority students (Van de Werfhorst and Mijs 2010; Van de Werfhorst, van Elsas, and Heath 2014; Pomianowicz 2021). In highly tracked countries, even immigrant students from positively selected immigrant communities perform worse across various educational outcomes compared to similar immigrant students in lowly tracked countries (Van de Werfhorst and Heath 2019). Thus, the existing evidence points to the fact that tracking is an important structural factor for student outcomes, and likely plays a significant role in the variation in expectation gaps between immigrant and ethnic majority students across countries, and potentially between immigrant students from different origins.

Against this backdrop, this article asks whether the cross-country gap in expectations of obtaining a university degree between second-generation immigrant and ethnic majority students can be related to the degree of educational tracking. It devotes attention to university attainment because of the importance of the university in access to employment, higher earning potential, and lower risk of unemployment (OECD 2018). International empirical evidence suggests that second-generation immigrant students still face barriers to accessing university in systems with a higher degree of tracking (Griga and Hadjar 2014), which prevents them from attaining upward social mobility via higher education.

This article is an important contribution to the findings from the few existing cross-country comparative studies on the role of tracking in affecting the immigrant expectation gap, which has produced mixed results. In a larger cross-country sample, Chykina (2019) finds a negative association between tracking and first-generation (but not second-generation) immigrant students’ expectations. Nevertheless, the study does not empirically clarify the mechanism linking tracking to educational expectations. This is also true for Hadjar and Scharf (2019), who did not find tracking effects on immigrant gaps in the value of education, a similar but not equivalent concept to the one studied here. Even though this aspect is not the focus of their theoretical and empirical approach, their (unweighted) results show that the expectation gap between ethnic majority students and students with different ethnic origins varies to some extent with the degree of tracking in the surveyed countries. Only Nygård (2017) explores possible tracking mechanisms more closely. Firstly, the author shows that second-generation immigrant students have a lower expectation advantage over ethnic majority students in the more-tracked Dutch education system compared to the less-tracked Swedish system. Moreover, the results also show that significant others play an important role in raising expectations, regardless of the tracking context. However, since the study uses data from disadvantaged school settings, such findings may not extend to a wider student population.

The present paper seeks to clarify this picture and makes three contributions to the literature. First, a rigorous test of the theoretically relevant mechanisms is employed by linking research on tracking effects with research on the formation of educational expectations. The paper identifies and tests two commonly raised but rarely proven arguments in a comparative way. It argues that the country-level tracking degree moderates the impact of significant others’ influences and students’ responsiveness to scholastic ability on educational expectations, which could account for immigrant expectation gaps across countries. Second, it explicitly addresses students’ track level in the empirical analyses, something neglected by the aforementioned studies, particularly in countries with less tracking. By directly measuring students’ track level, this study seeks to clarify how the immigrant expectation gap is altered by more flexible tracking practices within schools compared to more rigid between-school tracking procedures. The article thereby adds to the recent, more nuanced evidence on the varying organization of ability tracking between countries and the impact this has on educational outcome disparities (Chmielewski, Dumont, and Trautwein 2013; Chmielewski 2014).

A third contribution of this paper addressing shortcomings of previous studies relates to the varying operationalization of immigrant background. The (partial) lack of accounting for ethnic origin could be a contributing factor to cross-national variations in second-generation immigrant expectations as well. A growing body of sociological literature shows that part of the variations in educational attainment among immigrant children from different origin groups can be explained by immigrants’ educational selectivity (Feliciano 2005). Selectivity describes the process by which immigrants’ educational level is compared with the educational level of origin-country members, who have not migrated. Immigrants with educational qualifications that exceed the qualifications of the majority of the non-migrated population are positively selected. This individual selection by migrant parents’ relative education likely leads to a positive selection of skills and attitudes, which constitute valuable educational resources for their children. As a consequence, immigrant children with such positively selected parents tend to be more prone to developing higher aspirations and expectations (Feliciano 2006; Ichou 2014; Engzell 2019).

However, based on initial evidence on other educational outcomes (Van de Werfhorst and Heath 2019), it is assumed that tracking diminishes the aspirational transmission mechanism between parents and children by providing more explicit information about students’ abilities. This should particularly reduce the expectation advantage of children with positively versus negatively selected immigrant parents in highly tracked contexts. As a first systematic investigation, this study sheds new light on how tracking systems influence immigrant children's educational expectations depending on their parents’ educational selectivity.

Using the cross-national Children of Immigrants Longitudinal Survey in Four European Countries (CILS4EU), I explore the educational expectations of students around the age of 15 in England, Germany, the Netherlands, and Sweden. These four countries represent distinct types of tracking regimes and thus allow for rigorous testing of how tracking characteristics shape students’ views on their future educational prospects.

This article begins with a theoretical review of the relationship between the formation of educational expectations and the country-level tracking degree (Section “The formation of educational expectations in relation to the tracking degree”). I subsequently elaborate on how the developed theoretical mechanisms add to the understanding of variations in immigrant expectation gaps by the country-specific tracking regime and by parents’ educational selectivity (Section “Tracking and immigrant expectation gaps”). The Section “Context of the study” gives an overview of the country contexts, and the Methods section introduces the data and the operationalization of the theoretical concepts, as well as the analytical approach used to test the derived hypotheses. After presenting the results in the Results section, the article closes with a critical discussion of the key findings and their implications for future research in the Discussion section.

Theoretical Background

The Formation of Educational Expectations in Relation to the Tracking Degree

The central role of educational expectations in predicting educational attainment first came to prominence within the Wisconsin model of status attainment (Sewell, Haller, and Portes 1969). The model assumes that aspirations and expectations are formed via two main mechanisms. The first of these is the impact of interpersonal influence. Significant others—that is, people who matter to the student in question (e.g., parents, peers and teachers)—exert an influence either by directly communicating their expectations or by indirectly serving as a role model. The second mechanism concerns how students develop educational expectations depending on their estimated ability. Past academic success serves as a reference for their own “self-reflection” and forms a basis for assessing future goals and the likelihood of achieving them. Moreover, significant others’ expectations may also be partly based on the student's “demonstrated” ability, which indirectly influences their expectations through a process of adjustment to the views of significant others (Sewell, Haller, and Portes 1969; Haller and Portes 1973).

Critics of the Wisconsin model have emphasized the role of institutional settings in limiting or giving access to the specific opportunities students encounter during their educational career (Kerckhoff 1976; Morgan 2007). One institutional determinant that shapes students’ educational expectations is related to educational tracking. A higher degree of tracking is present when tracking is implemented early and when students are sorted into distinct programs with separate curricula (i.e., academic versus vocational programs) offered between or within schools. Lower-tracked countries apply a more flexible sorting of “ability grouping” or “course-by-course-tracking,” in which students are grouped into courses with different ability levels within or between classes (Chmielewski, Dumont, and Trautwein 2013).

In countries with more tracking, students’ formal access options are restricted by the track level students attend, whereas in countries with less tracking, track level attendance is more loosely coupled with access to university. Additionally, track mobility is more restricted in those systems, which reduces the likelihood of change in academic track later on, especially for disadvantaged students (Hillmert and Jacob 2010; Chmielewski 2014). Finally, in highly tracked countries, skill provision is more restricted to the attended track level. Whereas vocational tracks prepare students for apprenticeship programs, academic tracks equip students with the general knowledge and skills necessary for university attendance (Shavit and Müller 2000).

These central tracking characteristics may restrict how students form their educational expectations in two different ways. The key argument states that students in highly tracked countries have more realistic expectations due to the strong signal that school tracks send about future educational and occupational opportunities and about students’ academic potential (Kerckhoff 1977; Buchmann and Dalton 2002; Buchmann and Park 2009). The first result of stronger track signals should be a smaller scope for interpersonal influences to alter educational expectations. The feedback on students’ academic ability indicated by tracks, along with university access options being strongly dependent on the attended track level, may constrain students’ views of future educational trajectories in highly tracked countries. As a result, they may rely less on feedback provided by those in their personal surroundings, such as parents and peers (Yuchtman and Samuel 1975; Buchmann and Dalton 2002). Early and rigid tracking also leads to the grouping of students with similar characteristics and expectations within tracks, due to which it can be expected that previously existing expectations will be perpetuated (Kubitschek and Hallinan 1998; Buchmann and Dalton 2002; Lorenz et al. 2020). This may also be a result of parents’ aspirations heavily influencing students’ school track level position before entering lower secondary education, as a study in highly tracked Germany suggests (Dumont, Klinge, and Maaz 2019). Hence, in systems with more tracking, parental aspirations may be influential before a transition is made and the resulting correspondence of parents’ aspirations with the track level should reduce the influence of parental aspirations after the transition. Since the study by Buchmann and Dalton (2002), there has been little comparative research on the reduced influence of significant others in secondary education in more-tracked countries.

Secondly, stronger track signals in more tracked countries should enable students to realistically assess their future prospects in relation to their academic ability (Kerckhoff 1977; Buchmann and Park 2009). As a result of social labeling, students are assumed to be more aware of their “academic potential,” as signaled by the track level they are sorted into (Karlson 2015, 118). Due to the more open and flexible tracking practice in countries with a lower degree of tracking, the less dramatic consequences of track placement for higher education attendance could result in students relying less on their ability when forming expectations (Kerckhoff 1977). Indeed, some comparative studies find that school achievement predicts educational expectations more in tracked systems (Basl et al. 2007; Buchmann and Park 2009).

Both mechanisms of the reduced influence of significant others and a higher reliance on school ability in reducing educational expectations in more-tracked countries are assumed to be central in explaining country variations in immigrant expectation gaps.

Tracking and Immigrant Expectation Gaps

The role of parental aspirations

With regard to the influence of significant others, previous research has found that immigrant children in particular express higher expectations due to the higher aspirations and expectations of their parents (Feliciano and Lanuza 2016; Fernández-Reino 2016) and other close relatives (Cheng and Starks 2002). High parental aspirations are commonly traced back to the immigrant optimism hypothesis, which suggests that voluntary immigrants use the migration process as a tool to aid upward mobility and put much effort into increasing their social and educational status in their new society. Immigrant parents who fail to achieve those goals for themselves transfer their wishes and hopes regarding scholastic outcomes to their children (Kao and Tienda 1995; Teney, Devleeshouwer, and Hanquinet 2013).

Regarding differences stemming from the tracking degree, the reduced influence of significant others in more-tracked systems may impede immigrant parents from influencing their children's expectations and thereby lower the overall expectation differences between second-generation and ethnic majority children. Parental aspirations are assumed to affect children's expectations to a lesser extent when students constantly receive feedback on their future educational chances from the track level they are sorted into. Moreover, immigrant parents themselves could be less optimistic and form their own aspirations depending on their child's track level. This effect should be stronger within immigrant families because the marginalized position of immigrants in their host societies may lead immigrant children to rely more on the social capital within their families (Cheng and Starks 2002, 309). Hence, I argue that tracking moderates the influence of parental aspirations on immigrant children's expectations so that the usually higher aspirations among immigrant parents transfer to their children to a lesser extent in countries with more tracking. In contrast, in countries with less tracking, the influence of parental aspirations may have a greater impact, resulting in higher educational expectations for second-generation immigrants compared to ethnic majority students.

H1:

The expectation gap between second-generation immigrant and ethnic majority students should be smaller in highly tracked countries because of the lower influence of parental aspirations on children's expectations.

Variations by educational selectivity

Research has shown that across countries, educational expectations vary considerably between immigrant children from different origin groups² (Salikutluk 2016; Fernández-Reino 2016; Friberg 2019), indicating that the development of high ambitions may not apply to all immigrant children alike. Existing studies suggest that variations in educational outcomes according to ethnic origins are fully or partly the result of educational selectivity (Feliciano 2005; Heath and Brinbaum 2014a; Feliciano and Lanuza 2017; Engzell 2019). In this regard, some studies show that immigrant parents’ pre-migration educational qualifications (the education level compared to origin country members) are more predictive in explaining educational outcomes among immigrant students as opposed to parents’ post-migration education level (the education level compared to destination country members) (Feliciano 2005, 2006; Ichou 2014; Engzell 2019; Brunori, Luijkx, and Triventi 2020).

The focus on pre-migration educational qualifications is based on the idea that immigrants’ credentials should be interpreted in the context where they were obtained. Immigrants with education levels that exceed the credentials of the population of origin are equipped with high levels of “relative education” because they received more education than average among the origin country population (Ichou 2014; Feliciano and Lanuza 2017; Engzell 2019). A high relative education among immigrant parents also comes along with a positive selection of “cultural skills, dispositions, beliefs, and aspirations” (Feliciano and Lanuza 2017, 215), characteristics that shape unique forms of cultural capital and which provide useful resources for immigrant children's educational success (Feliciano 2005; Ichou 2014; Feliciano and Lanuza 2016; 2017; Engzell 2019; Brunori, Luijkx, and Triventi 2020).

Variations in immigrant parents’ selectivity are found to lead to variations in their aspirations for the educational success of their children, and this is one possible explanation for why immigrant children from certain ethnic origins have higher educational expectations (Feliciano 2006). Immigrant parents with high relative education often experience a status loss via migration, but their orientations still remain associated with their previous class position. The discrepancy between pre- and post-migration education levels may additionally encourage the desire for upward mobility, and lead to higher educational values and ambitions regarding the education level of their children. Such high educational beliefs may be cultivated within families via narratives of sacrifices and parental upbringing practices, which find their highest expression in parents’ educational aspirations (Feliciano and Lanuza 2016, 765). By internalizing parents’ cultural orientations and “narratives of hardships” (Feliciano and Lanuza 2017, 215), children develop their own habitus and beliefs of succeeding in education, partly in order to fulfill parents’ preferences, but also because they benefit from the valuable resources provided by cultural capital within immigrant families (Feliciano 2005; 2006; Feliciano and Lanuza 2016; 2017; Brunori, Luijkx, and Triventi 2020; Nygård 2021).

The whole process of transmission from parents’ aspirations to children's expectations is a nuanced version of the immigrant optimism hypothesis. It additionally underscores the relevance of cultural values stemming from parents’ relative educational position and thereby accentuates the varying levels of expectations within the heterogenous immigrant student population stemming from diverse ethnic origins (Feliciano and Lanuza 2017).

Nonetheless, as argued in the previous section, this transmission mechanism could depend on the scope that education systems leave for significant others to influence children's expectations. Indeed, studies which have shown a positive effect of selectivity on children's educational expectations and aspirations have only been conducted in less-tracked countries (Feliciano 2006; Feliciano and Lanuza 2017; Engzell 2019; Nygård 2021), leaving open the question of whether this expectation advantage also appears in more-tracked countries. To my knowledge, there is only one study which explores the role of tracking in how educational selectivity affects children's educational outcomes (Van de Werfhorst and Heath 2019). The study shows that early tracking diminishes the advantage of immigrant students from positively selected communities in test scores and track attendance, which the authors trace back to a limited timeframe for developing the learning potential of highly ambitious immigrant children.

These findings would support the view that tracking moderates the relationship between selectivity and children's expectations as well. Based on the earlier arguments on the reduced effects of significant others, there are two main reasons why children with positively selected immigrant parents have a lower expectation advantage in countries with a higher degree of tracking. First, parents’ orientations towards children's educational success are more likely to flourish in countries where education systems leave all options open until the end, and where the missing track signals do not restrict their views on children's opportunities to succeed until university (Buchmann and Dalton 2002, 104; Friberg 2019, 2847). Second, due to stronger track signals in more tracked countries, children's aspirations should be less influenced by parents’ aspirations, which likely reduces the transmission of parents' aspirations and restricts children's access to cultural capital resources (see also Feliciano and Lanuza 2016, 784).

Hence, the beneficial effect of educational selectivity on expectations via the transmission of parental aspirations, and the resulting expectation advantage of students with positively over negatively selected immigrant parents, should only be visible in countries with less tracking.

H2:

The expectation gap between students with positively and negatively selected immigrant parents should be smaller in highly tracked countries because of the lower influence of parental aspirations on children's expectations.

Responsiveness to school ability

Ample research shows that school ability has a lower impact on the formation of educational expectations among immigrant students compared to ethnic majority students (e.g., D’hondt et al. 2016; Feliciano and Lanuza 2016; Fernández-Reino 2016; Pinquart and Ebeling 2020). One prominent explanation for this finding refers to immigrant parents’ lower familiarity with host country educational institutions and possible language barriers (Kao and Tienda 1998; Antony-Newman 2019), which results in less knowledge of how to effectively navigate the school system and a higher difficulty with accurately assessing their children's school performance (Alexander, Entwisle, and Bedinger 1994; Relikowski, Yilmaz, and Blossfeld 2012). Due to such missing parental resources, immigrant children themselves may lack the knowledge usually necessary to realistically relate school performance to future educational opportunities (Alexander, Entwisle, and Bedinger 1994).

Evidence regarding the varying responsiveness to school ability in immigrant families versus ethnic majority families is mixed. Some studies report that immigrant children and their parents respond less to the children's academic achievements (Stevenson, Chen, and Uttal 1990; Alexander, Entwisle, and Bedinger 1994; Gresch 2012; Relikowski, Yilmaz, and Blossfeld 2012; Feliciano and Lanuza 2016). Other studies do not find evidence that immigrant students’ expectations evolve differently in response to school ability or a lack of information on the functioning of education systems (Karlson 2015; Salikutluk 2016; Tjaden and Hunkler 2017; Geven and Forster 2021). However, most of the latter studies are conducted in Germany, a country with a high tracking degree where the link between immigrant expectation and achievement can be assumed to be narrower.

A systematic investigation of whether lower responsiveness to school ability leads to higher educational expectations among immigrant children requires the consideration of the country's degree of tracking. As already pointed out, systems with more tracking provide students with more information on their ability level via the track level they attend. Hence, in countries with a higher degree of tracking, second-generation immigrant students could be prevented from overestimating their existing ability levels when forming expectations. In contrast, the lower feedback stemming from ability tracks in less-tracked systems may lead second-generation immigrant students to be less informed about the consequences of school achievement and develop expectations regardless of given abilities (Jerrim 2014, 199; Pinquart and Ebeling 2020). Empirically, the presence of varying levels of responsiveness to school ability between immigrant and ethnic majority children should be represented by larger group differences in educational expectations at given ability levels, whereas in case of similar responsiveness, no such group differences should be visible.

H3:

The immigrant expectation gap should be smaller in highly tracked systems, because differences in the influence of school ability on expectations between second-generation immigrant and ethnic majority students are small.

Context of the Study

The four countries under study represent distinct types of tracking implementation. Germany can be regarded as the country with the highest degree of tracking, as the age of selection is the lowest (age 10 in most federal states) and sorting into distinct programs takes place mostly between schools rather than within schools. The Dutch education system can be considered as more integrative due to a higher prevalence of within-school tracking, which facilitates track mobility (Büchner and van der Velden 2013). In principle, track mobility and alternative pathways to enter university exist in Germany as well. Nevertheless, in both systems, access to university is formally provided mainly in the academic tracks (Dronkers and Korthals 2016; Henninges, Traini, and Kleinert 2019).

In Sweden and England, tracking in lower secondary education is less rigid, as it is applied between or within classes within each school. In England, tracking within comprehensive schools is more widespread, since students are grouped for almost all subjects (Chmielewski 2014). In Swedish schools, ability grouping is less extensive as it is applied only for some subjects or in a more informal way within classes (Rudolphi and Erikson 2016). Additionally, the initial choice of vocational versus academic subject seems to play a greater role in subsequent educational decisions in England compared to Sweden (McMullin and Kulic 2016).

In Table 1, these tracking characteristics are summarized on the left-hand side. Germany is the most strongly tracked system and Sweden and England are the more weakly tracked ones, with the Netherlands in between (see Pomianowicz (2021) for an empirical validation of the variation of the tracking degree across countries). On the right-hand side, the hypotheses are again displayed to provide guidance on how country-specific results can be interpreted in accordance with the assumptions about the tracking-degree effects. To give an example, for H1, Table 1 shows that the influence of parental aspirations on immigrant expectation gaps is assumed to be weakest in Germany and strongest in Sweden and England. Although the assignment of countries to the tracking degree reflects ideal cases, the typology shall help to interpret the results accordingly and thereby provide a strong test of whether tracking-degree effects are evident (or not).

Table 1.

The Degree of Tracking and Country-Specific Hypotheses.

Country	Time point first selection	Type of tracking in lower secondary education	Main route to university	Overall degree of tracking	H1: Influence of parental aspiration on overall immigrant expectation gap	H2: Influence of parental aspiration on expectation gap by parents’ educational selectivity	H3: Differences in influence of school ability on immigrant vs. ethnic majority students’ expectations
Germany	Age 10	Academic and vocational program division, mostly between schools	Academic track	+ + +	+	+	+
The Netherlands	Age 12	Academic and vocational program division, mostly within schools	Academic track	+ +	+ +	+ +	+ +
England	Age 16	Widespread ability grouping between classes	All tracks	+	+ + +	+ + +	+ + +
Sweden	Age 16	Some ability grouping between/within classes	All tracks	+	+ + +	+ + +	+ + +

Sources on tracking degree indicators: Bol and Van de Werfhorst (2013); Chmielewski, Dumont, and Trautwein (2013); Chmielewski (2014); Pomianowicz (2021).

Methods

Data

This study makes use of the CILS4EU data, which are from a longitudinal and comparative survey on the multidimensional integration of immigrant youth aged 14 to 16 years in England, Germany, the Netherlands, and Sweden (Kalter et al. 2016). The data include longitudinal measurements of students’ educational expectations and parents’ educational aspirations for their children, as well as detailed information on students’ ethnic origin, track level and scholastic ability. An oversampling of schools with students having an immigrant background allows for analyzing a sufficient number of cases of students from different ethnic origins. These unique features hold an advantage over other large-scale datasets that are missing variables which are necessary to adequately address the mechanisms considered here.

The data used for this paper was collected in 2010/11 (wave 1) and 2011/12 (wave 2). Across the four countries, 76.6 percent of students participating in wave 1 also participated in wave 2 (14,939 students in 425 schools). A three-stage sampling design was implemented: First, large schools and schools with a higher immigrant share were selected. Second, two classes in each school were randomly selected. Third, all students in these two classes were selected.

Operationalization and Sample

The dependent variable educational expectations is obtained from the harmonized version of students’ reports on the highest level of education that they think they will actually complete. This variable indicates whether students expected a university degree (1) and any qualification below university forms the reference category (0). Students who did not know what kind of educational level they should expect are excluded from the sample.

Immigrant background is measured as the generational status of students. Ethnic majority students are children born in the survey country and whose parents were also born in the survey country. Second-generation immigrant students are defined as students who were born in the survey country and whose parents were born abroad, or who have one parent and at least one grandparent (on the side of the native-born parent) who were born abroad (2.5th and 2.75th generation). Furthermore, children born abroad who immigrated at preschool age (1.75th generation) are also defined as second-generation immigrant students since they should closely resemble this group, especially with regard to their exposure to the education system (Rumbaut 2004). First- and third-generation immigrant students as well as students with one native- and one foreign-born parent are excluded from the sample.

To measure the individual-based educational selectivity, an index of the relative educational level of immigrant parents is constructed by comparing the educational degree of immigrant parents to that of others from the origin country who have the same gender and age. Following previous approaches, the most recent update of the Barro and Lee (2013) data is used, which provides the educational attainment of the population aged 15–64 years for 146 countries since 1955. The usual procedure matches each individual with the age- and gender-specific distribution of educational attainment in the origin country (Ichou 2014; Feliciano and Lanuza 2017; Schmidt, Kristen, and Mühlau 2021).³ As the CILS4EU data does not include the ethnic origin of parents, which is necessary to match immigrant parents with the home country population,⁴ an approximation is made by using the country of origin measured on the child's level. The child's country of origin is mainly classified by the children's, parents’, and grandparents’ countries of birth (Dollmann, Jacob, and Kalter 2014, 35). Excluding first- and third-generation immigration students should give a high fidelity to reflect the ethnic origin of parents.

To construct the index, first, education is measured at three comparable levels (primary, secondary and university level) in both datasets. Second, the gender- and age-specific educational distributions in the origin countries are calculated for each birth cohort (measured in 10-year intervals), and for males and females separately in the Barro and Lee data. For those cases where the age of parents was available in the CILS4EU data, equivalent birth cohorts could be calculated. In cases of missing values for parents’ age, age-matching is approximated by restricting the range of the Barro and Lee data to years 1955–1975, assuming that parents are aged around 35–55 years at the time of the study. For the latter cases, the percentage of the population holding each degree is mean summarized across years and birth cohorts for each country of origin. Third, immigrant mothers and fathers are separately matched with the (approximated) age-specific educational distribution in the origin country according to the ethnic origin of the children. The resulting selectivity index is then averaged across parents and ranges from 0 to 1, depicting the percentage of people in the origin country with lower education plus half of the percentage of people with the same education level.

Usually, values below 0.5 can be interpreted as negative selectivity compared to the non-immigrant population in the country of origin, whereas values above 0.5 indicate positive selectivity (Ichou 2014; Schmidt, Kristen, and Mühlau 2021). I use this cutoff point to construct second-generation immigrant students with positively versus negatively selected parents. This distribution of immigrant children from positively and negatively selected groups across the origin countries is pictured in Figure 1. The figure shows that the majority of second-generation immigrant students have positively selected parents, but educational selectivity also varies slightly across origin groups. It is noteworthy that immigrant students from the former Soviet Union in Germany represent the only group in which more students are negatively selected. Finally, a drawback of the Barro and Lee data is that it does not contain information about the largest origin groups in the Netherlands, namely those from Suriname and the Netherlands Antilles, which therefore could not be included in the sample.

Figure 1.

Parents’ educational selectivity across second-generation immigrant students’ origin groups.

The track level is measured by the school type students attend in Germany and the Netherlands. In England and Sweden, students are grouped by ability classes in math, English, and the survey country language. For the analyses, grouping in math is used because ability tracking in math is considered more influential in providing access to university (Chmielewski, Dumont, and Trautwein 2013, 934). The number of schools and ability tracks varies between countries, and are thus collapsed into three categories: high track (0, academic tracks in Germany and the Netherlands; high ability tracks in Sweden an England), middle or low track (1, vocational tracks in Germany and the Netherlands; middle and lower ability tracks in England and Sweden), and no tracking (2, in England and Sweden). In Germany, the latter category (2) refers to attending a comprehensive school, where all three track levels are combined (see Table A2 in the Online Appendix). Although in the Netherlands, many schools also offer several tracks (see Section “Context of the study”), the data does not allow for disentangling single-track from multi-track schools.

Parental aspirations are coded 1 if students report that their parents wish for them to receive a university education. If, according to students, parents want them to get a lower qualification, the variable is coded as 0. “Don’t know” answers are excluded from the sample. The scholastic ability of students was obtained from the results of the language and cognitive ability tests that students took during the survey. Variables are a calculated mean of each test score and range from 0 to 1, with higher values indicating higher test scores (see Table 2 for a descriptive overview of variables).

Table 2.

Descriptive variable Distribution (Weighted, N = 6,591).

	Min.	Max.	Mean/Prop.	SE	% Missing values
Students' educational expectations (wave 2)	0.00	1.00	0.45	0.01	0.23
Immigrant background	0.00	1.00	0.15	0.01	0.52
Parents’ educational selectivity	0.00	2.00	0.26	0.01	2.38
Parental aspirations (wave 1)	0.00	1.00	0.45	0.01	0.76
Cognitive ability (wave 1)	0.00	1.00	0.72	0.00	2.35
Language ability (wave 1)	0.00	1.00	0.60	0.00	2.35
Track level (wave 1)
High track			0.35		4.28
Middle/low track			0.47
No tracking			0.18
Parental education	0.00	1.00	0.31	0.01	2.17
Female student	0.00	1.00	0.49	0.01	0.07
Age	13.02	18.03	14.92	0.01	1.20

Source: CILS4EU. Note: Number of observations refers to non-imputed data.

Finally, the analyses control for age, gender (1 = female), and the highest level of parental education (1 = university level, 0 = below university level).⁵ Due to the exclusion of cases, the analytical sample consists of 7,344 students in 464 schools (see Table A3 in the Online Appendix). I use country-wise multiple imputation from chained equations to impute the remaining missing values. The multivariate analyses are based on the 20 imputation datasets which were created.

Analytical Approach

I conduct two-level logistic regressions, accounting for students nested within schools to address the stratified sampling design of the data. Measuring educational expectations in wave two and the independent variables in wave one allows for a more causal interpretation of the results. General results are displayed using average marginal effects (AMEs) for a more intuitive interpretation of the effects. Even though AMEs cannot account for the non-linear effects of probabilities, they have the advantage of being comparable across models and robust against unobserved heterogeneity between groups (Auspurg and Hinz 2011). All analyses account for school and student selectivity, as well as student and school non-response, by implementing the respective weights at the student and school levels.

First, I start by presenting the results of the unconditional and conditional expectation gap between second-generation and ethnic majority students. Second, stepwise inclusion of the independent variables is carried out in order to ascertain the degree to which the gap is influenced by the covariates of interest. Third, to explore the extent to which parental aspirations account for differences between second-generation and ethnic majority students’ expectations (H1), as well as between positively and negatively selected immigrant students (H2), a decomposition method is used following Fairlie (2005) and Jann (2008). This decomposition technique is suitable for explaining group differences—i.e., the expectation gap between ethnic majority and second-generation immigrant students—in non-linear models. The estimates are displayed in percentage points and allow for quantifying the group differences caused by the variables of interest. The analyses are based on models with all covariates (i.e., the full model) and run with 1,000 replications in order to account for potential bias resulting from the drawing of subsamples (Fairlie 2005). Finally, interaction effects between school ability and immigrant background are used to ascertain whether immigrant and ethnic majority children differ in their consideration of academic ability when forming educational expectations (H3).

Results

Descriptive Results

The descriptive distribution of variables in Table 3 shows that in all countries (except for Germany), second-generation immigrants exhibit higher expectations of obtaining a university degree than their ethnic majority classmates (see the first two columns of each country panel). Parental aspirations for their child's education degree are also generally higher among second-generation immigrant students in all four countries, with Germany showing the smallest and the Netherlands showing a notably large gap between the parents of second-generation immigrant and ethnic majority students. Moreover, second-generation immigrant students score lower in the cognitive and language ability test, although with only minimal differences in England. Second-generation immigrant students are less likely than ethnic majority students to attend the higher tracks in all countries except the Netherlands, where second-generation students are more likely to attend academic tracks. This is a divergence from other studies, which find a descriptive disadvantage in Dutch immigrant students’ track-level position (Van de Werfhorst and van Tubergen 2007; Crul, Schneider, and Lelie 2012; Baysu, Alanya, and de Valk 2018). Again, in Germany, immigrant gaps in track attendance are the most pronounced. A first impression from these descriptive results points to a less favorable context in Germany for developing high educational expectations among second-generation immigrant students.

Table 3.

Weighted Mean Statistics by Immigrant Background and by Parents’ Educational Selectivity.

	Sweden				England				Netherlands					Germany
	Non-immig.	2nd-gen. immig,	Neg. selected	Pos. selected	Non-immig.	2nd-gen. immig,	Neg. selected	Pos. selected	Non-immig.	2nd-gen. immig,	Neg. selected	Pos. selected	Non-immig.	2nd-gen. immig,	Neg. selected	Pos. selected
Students' educational expectations (wave 2)	0.73	0.84	0.78	0.85	0.53	0.71	0.69	0.72	0.42	0.63	0.67	0.62	0.26	0.21	0.18	0.23
Parental aspirations (wave 1)	0.76	0.95	0.91	0.95	0.64	0.82	0.74	0.85	0.32	0.81	0.78	0.82	0.19	0.31	0.26	0.33
Cognitive ability (wave 1)	0.69	0.62	0.63	0.62	0.71	0.70	0.68	0.70	0.74	0.67	0.63	0.68	0.75	0.70	0.69	0.70
Language ability (wave 1)	0.68	0.59	0.56	0.59	0.69	0.68	0.62	0.70	0.58	0.48	0.47	0.49	0.55	0.43	0.43	0.44
Track level (wave 1)
High track	0.23	0.18	0.24	0.16	0.80	0.78	0.87	0.76	0.13	0.25	0.16	0.27	0.33	0.22	0.22	0.22
Middle/low track	0.21	0.21	0.19	0.21	0.14	0.17	0.09	0.20	0.87	0.74	0.84	0.73	0.50	0.66	0.73	0.64
No tracking	0.55	0.62	0.57	0.63	0.06	0.04	0.04	0.05	-	-	-	-	0.17	0.11	0.06	0.14
Parental education	0.57	0.51	0.00	0.61	0.35	0.41	0.02	0.53	0.18	0.15	0.00	0.18	0.25	0.12	0.01	0.17
Female student	0.46	0.58	0.55	0.58	0.51	0.56	0.51	0.57	0.50	0.71	0.61	0.73	0.47	0.51	0.44	0.54
Age	14.74	14.68	14.77	14.66	15.18	15.18	15.10	15.20	14.89	15.00	15.09	14.97	14.87	14.97	15.13	14.92
N (students)	869	452	84	368	1010	352	72	280	1225	234	58	176	1459	990	271	719
N (schools)	125				97				98				144

Source: CILS4EU. Note: Number of observations refers to non-imputed data.

Differences by parental educational selectivity in Table 3 (see the last two columns of each country panel) show that students of positively selected immigrant parents have higher educational expectations, except in the Netherlands, where these students exhibit lower educational expectations compared to students with negatively selected parents. In all four countries, aspirations are higher among positively selected parents. Hence, higher student expectations and higher parental aspirations seem to go along with parental educational selectivity, except in the Netherlands. Moreover, students with positively selected parents are slightly overrepresented in the higher tracks in the Netherlands, whereas in England and Sweden it is the other way around. In Germany, academic track attendance does not vary by parental educational selectivity. Since the number of observations is very small for negatively selected immigrant students, the ensuing multivariate results should be interpreted with caution.

Multivariate Results

Educational expectation gaps between second-generation immigrant and ethnic majority students

Figure 2 plots the country-wise multivariate results of expectation gaps between second-generation immigrant and ethnic majority students. The base model without any controls added shows that second-generation immigrant students develop higher expectations compared to ethnic majority students in Sweden, England, and the Netherlands, whereas in Germany, differences between the two groups are almost non-existent. Controlling for individual controls (not shown here), school ability, students’ track level and parental aspirations in the full model substantially reduces this gap in the Netherlands.

Figure 2.

Coefficient plots of educational expectations by immigrant background (Base vs. full model). Source: CILS4EU. Notes: Coefficient plots from two-level logistic models (AMEs). Models are based on separate country analyses. See Table A4 in the Online Appendix.

Turning attention to the general effect of these control variables reveals some remarkable findings (Figure 2, full model). First, the influence of students’ track level varies with the tracking degree in the assumed direction: The higher the tracking degree, the stronger the negative effect of lower and middle track levels (versus higher track levels) becomes. This supports the notion that students in more tracked countries receive stronger track-level signals about their aptitude and future opportunities and adapt their expectations accordingly. Students in Germany attending comprehensive schools (displayed in the category “no tracking”) also develop lower expectations compared to those in high-track schools, although some of these schools offer an academic track (Helbig and Nikolai 2015, 83). In contrast, the influence of high parental aspirations does not vary along with the tracking degree in the assumed direction; parental aspirations matter most in the Netherlands and in England, whereas the lowest influence is found in Germany and Sweden, contradicting the theoretical assumption that parents’ aspirations will have greater influence in countries with less tracking. Regarding the effects of ability, there is some indication that language ability is more important in the less-tracked systems in Sweden and England. However, this observation does not hold for the measures of cognitive ability. Hence, no clear pattern is found with regard to a higher relevance of school ability in more-tracked countries (Basl et al. 2007; Buchmann and Park 2009). At best, these findings would rather speak to the higher importance of ability in less-tracked countries, whereas in countries with more tracking, the effect of achievement could be absorbed by the stronger effects of track level, reflecting the more salient track signals there.

In order to investigate which factors account for the immigrant expectation gap, Figure 3 shows the results from models with single inclusions of the covariates. Each model shows the coefficient for second-generation immigrant students, displayed as AMEs. Model 1 accounts for age, gender and parental education, variables that are controlled for in each subsequent model. The additional (single) inclusion of track level (M2), school ability (M3), and parents’ aspirations (M4) alters the expectation gap quite differently across the four countries. First, including the track level has almost no effect on the expectation gap between immigrant and ethnic majority students (M2). Second, controlling for students’ cognitive and language ability (M3) slightly increases the gap in all countries, with the highest increase in the Netherlands. This partly mirrors findings from other studies, in which second-generation immigrant students exhibit higher educational expectations despite lower academic ability levels (Feliciano and Lanuza 2016; Fernández-Reino 2016). Third, accounting for parental aspirations (M4) narrows the expectation gap in all four countries—particularly in the Netherlands and Germany—where second-generation immigrant students’ expectations no longer differ from those of the ethnic majority group.

Figure 3.

Coefficient plots of second-generation immigrant vs. ethnic majority students’ educational expectations. Source: CILS4EU. Notes: Bars display the two-level logistic regression coefficient (AMEs) of second-generation immigrant students (ref. ethnic majority students). Models are based on separate country analyses. Bars above zero indicate higher expectations among second-generation immigrant students. Ind. level controls: Age, gender, parental education; School ability: Cognitive and language ability; Full model: All covariates. See Table A5 in the Online Appendix.

In order to quantify these single contributions to explaining group differences and to investigate whether the transmission of parental aspirations is more restricted in countries with more tracking (H1), a decomposition technique following Fairlie (2005) is performed. This technique estimates how the variables of interest contribute to the explanation of the educational expectation gap between second-generation and ethnic majority students. Figure 4 graphically visualizes these findings by showing the separate contributions of individual-level controls (M1), school ability (M2), track level (M3), and parental aspirations (M4). These contributions are shown as the percentage share of the observed group differences and thereby allow for a direct comparison of the magnitude of the contributions of each factor across the four countries.

Figure 4.

Fairlie decomposition of educational expectation differences between second-generation and ethnic majority students. Source: CILS4EU. Notes: △ = Expectations gap between ethnic majority and second-generation immigrant students. Results are based on full models including all covariates. Weighted results, based on non-imputed data. See Table A6 in the Online-Appendix.

As shown in Figure 4, there are variables with negative and positive values, and the interpretation of these signs depends on whether the unconditional expectation gap is positive or negative. In Sweden, England, and the Netherlands, this gap is negative (i.e., second-generation immigrant students have higher educational expectations compared to ethnic majority students). For these countries, the negative values of variables contribute to an increasing gap, which means that these variables explain why second-generation immigrant students have lower expectations than ethnic majority students in the first place. In contrast, positive values of variables lead to a decreasing gap, i.e., they explain why immigrant students initially have higher educational expectations. As in Germany the gap is positive (i.e., second-generation immigrant students have lower educational expectations than ethnic majority students), the interpretation of the signs is reversed. For example, school ability leads to an increased expectation gap between second-generation and ethnic majority students in all countries, which was already visible in Figure 3 (Models 3). Figure 4 now shows the extent to which school ability accounts for the initially lower expectations among second-generation immigrant students is highest in Germany, followed by Sweden, which may be due to second-generation immigrants’ lower ability levels. Similarly, in Germany, students’ track level contributes to a widening expectation gap, suggesting that disadvantaged track-level sorting accounts for lower expectations among second-generation immigrant students.

With regard to H1, Figure 4 shows that in all countries, parental aspirations constitute a substantial factor in explaining the initially higher expectations among second-generation versus ethnic majority students. However, the importance of parents’ aspirations is highest in the Netherlands, followed in declining order by Germany, England and Sweden. This means that the hypothesized moderating effect of tracking is not supported, because a higher importance of parental aspirations on immigrant expectations gaps would be expected in lowly tracked countries like Sweden and England compared to the more tracked countries, Germany and the Netherlands.

Variations by educational selectivity

Figure 5 visualizes the educational expectation gaps between students with positively versus negatively selected parents by displaying the coefficients for the positively selected groups. The base model, where no controls are added, shows that immigrant students with positively selected immigrant parents hold higher educational expectations compared to students with negatively selected parents in all countries except for the Netherlands. However, these differences are non-significant. In the full model, in which all covariates are added, the gap between students is reduced in all countries, except for the Netherlands, where almost no change in the coefficient is evident.

Figure 5.

Coefficient plots of educational expectations by parents’ educational selectivity (Base vs. full model). Source: CILS4EU. Notes: Coefficient plots from two-level logistic models (AMEs). Models are based on separate country analyses. Full model includes all covariates, see Table A7 in the Online Appendix. Positive values indicate higher educational expectations among immigrant students with positively selected parents.

Even though the gaps between positively and negatively selected immigrant students are non-significant, the test of H2 by quantifying the contribution of explanatory factors to these gaps was performed for the sake of completeness (see Figure A1 in the Online Appendix). Decomposing the expectation gaps between positively and negatively selected immigrant students reveals that the contribution of parental aspirations is highest in England, followed by Germany and the Netherlands. Hence, no support was found for a lower expectation advantage of children with positively versus negatively selected immigrant parents due to a lower influence of parental aspirations when the tracking degree is higher (H2).

Responsiveness to school ability

To investigate whether the tracking degree influences the role that scholastic ability plays in second-generation immigrant students formation of their educational expectations (H3), Figures 6 and 7 visualize the interaction effect between immigrant background and cognitive ability (Figure 6) and language ability (Figure 7) for each country. A lower responsiveness to academic ability among second-generation immigrant students in lower-tracked countries should translate into larger group differences. These group differences are indeed visible in Sweden and England for both ability measures. In England, second-generation immigrant students develop higher expectations compared to ethnic majority students when the overall level of cognitive and language abilities is lower. In Sweden, group differences are more evident in the middle ability distributions. In contrast, German second-generation and ethnic majority students’ expectations evolve quite similarly across the entire cognitive and language ability distribution. Dutch second-generation immigrant students express particularly high expectations when their cognitive ability is low; however, for the language ability measures, group differences are non-significant. Hence, the larger group differences in England and Sweden and the (partially) lower group differences in Germany and the Netherlands support H3 on the assumption that immigrant expectation gaps are smaller in highly tracked countries as a result of a similar responsiveness to prior ability of second-generation immigrant and ethnic majority students.

Figure 6.

Predicted margins of the interaction effect between immigrant background and cognitive ability. Source: CILS4EU. Note: See Table A8 in the Online Appendix.

Figure 7.

Predicted margins of the interaction effect between immigrant background and language ability. Source: CILS4EU. Note: See Table A8 in the Online Appendix.

Sensitivity Analysis

To account for possible selection bias resulting from excluding students who did not know what level of educational degree they expect and parents who had unknown aspirations for their children, the analyses from the Multivariate results section were replicated by including these cases in the reference category of students’ educational expectations and parents’ aspirations. Hence, “don’t know” answers were treated as children's educational expectations or parents’ aspirations below the university degree. The estimates for gaps between second-generation and ethnic majority students reveal no substantial differences from the estimates reported above. However, for group differences by parents’ educational selectivity, the advantage for immigrant children with positively over negatively selected parents became significant in England and Sweden, possibly as the number of cases has increased. Still, results from the Fairlie decomposition technique do not support H2 as the contribution of parental aspirations does not vary along the assumed direction of the tracking degree (see Figures A2–A8 in the Online Appendix).

Discussion

This study has investigated whether differences between second-generation and ethnic majority students in their educational expectations can be related to the degree to which an education system uses tracking. The main channel of influence was assumed to be more pronounced track signals in countries with a higher tracking degree, which lead to a reduced influence of significant others (i.e., parental aspirations) and a higher responsiveness to scholastic ability. The moderating influence of the tracking degree on both of these mechanisms was argued to be responsible for a reduced expectation advantage of second-generation immigrant students in countries with more tracking. Additionally, in order to shed light on possible differences between origin countries, it was investigated whether immigrant children benefit more often from parental educational selectivity in contexts with less tracking. Based on longitudinal data from CILS4EU, the analyses revealed a generally higher level of educational expectations among second-generation versus ethnic majority students in Sweden, England, and the Netherlands and similar educational expectation levels between both groups in Germany. No significant differences between positively and negatively selected immigrant groups were detected.

The first important finding of this study is that track signals are relevant to students’ responsiveness to their scholastic ability. This is true in a general manner, in that the more that a country uses tracking, the more that expectations of all students correspond to their track level. This corroborates findings from other studies on the alignment between track level and students’ expectations in more tracked systems (Buchmann and Park 2009; Lee 2014). By testing this assumption comparatively, this study contributes to previous research about track signaling effects on the development of educational expectations (Buchmann and Dalton 2002; Karlson 2015).

More importantly, the results of this study suggest that more pronounced track signals in countries with a higher degree of tracking reduce immigrant differences in responsiveness to scholastic ability. This is particularly true for the less tracked systems in Sweden and England, where immigrant students’ expectations are higher compared to ethnic majority students at the given ability levels. In Germany, group differences in educational expectations are quite similar along both the cognitive and language ability distributions. The Netherlands lies somewhere in between, in that responsiveness to cognitive ability is quite different in second-generation immigrant students than in ethnic majority students; however, for language ability, this is not the case. This suggests that second-generation immigrant students may be less detached from their ability levels and may more accurately relate their performance to future potential in countries with more tracking. This finding is in alignment with the studies that do not find immigrant differences in responsiveness to school ability or evidence of a lack of information on how to navigate the school system among immigrant students in the highly tracked German system (Salikutluk 2016; Tjaden and Hunkler 2017; Geven and Forster 2021).

The second key finding is that no support for the reduced influence of significant others in more-tracked systems was found. This is the case for the effects of parental aspirations on all students’ expectations across the four countries, where the strongest effects are found in England and the Netherlands and the weakest effects are found in Sweden and Germany. More importantly, the extent to which parental aspirations explain immigrant educational expectation gaps also does not vary with the tracking degree. Parental aspirations represent the highest contribution to explaining gaps between second-generation and ethnic majority students in the Netherlands, followed by Germany, which rather hints at a higher impact of parental aspirations in countries with more tracking. Hence, this study could not replicate the finding of a lower influence of significant others in more tracked systems in secondary education (Buchmann and Dalton 2002), neither in general terms nor in explaining gaps between the expectations of immigrant and ethnic majority students. One explanation for the latter finding could be that the anticipation of barriers in more tracked education systems leads to a greater sense of social exclusion among immigrant families, which propels the aspirations among immigrant parents (Nygård 2017). The strikingly large gap between immigrant and ethnic majority parents’ aspirations in the Netherlands from this study supports this argument. However, regarding the general influence of parents’ aspirations on children's expectations, it seems that track-level signals are not the most influential moderating factor after the transition to secondary education has been made in Germany and the Netherlands. Even though academic tracks pre-structure the route to university in such countries, attending these tracks may not be entirely deterministic and changing tracks during secondary education is still possible (Roth 2017; Henninges, Traini, and Kleinert 2019). Moreover, to fully grasp the varying effects of significant others in different tracking regimes, future research should additionally test the role of peers’ expectations, as the composition of the classroom and resulting peer effects also vary with the degree of educational tracking (Dollmann and Rudolphi 2020).

The results do not provide evidence that parental educational selectivity influences immigrant children's expectations differently in more- versus less-tracked systems. In general, gaps by parental educational selectivity were relatively small and insignificant, most likely due to the low number of cases, as the sensitivity analyses revealed. Hence, empirical findings from this study could not clearly verify the more positive association of educational selectivity and children's educational outcomes in countries with less tracking (Feliciano and Lanuza 2017; Engzell 2019; Van de Werfhorst and Heath 2019; Nygård 2021), at least when it comes to variations within the group of immigrant children. This may also partly be due to the theoretical complexity of the concept, let alone the measurement difficulty of the underlying characteristics that are associated with educational selectivity (Engzell 2019). Still, studying the institutional context should be considered an important research avenue in order to clarify whether children of immigrants equally benefit from the valuable resources stemming from parental educational selectivity across education systems.

In summary, this paper has made an important contribution by clarifying which factors related to the tracking degree are associated with differences in the formation of educational expectations between immigrant and ethnic majority students. The main finding of this study, relating to the influence of track-level signals on the level of responsiveness to school ability for immigrant and ethnic majority students, suggests that track signals can be a way of ensuring greater realism in future expectations and preventing failed expectations with negative consequences for students’ well-being (Jerrim 2014). However, the findings also provide an indication of blocked opportunities for immigrant students, who adjust their educational expectations downwards as a result of limited perceived future prospects. To gain more insights into the early effects of this type of discouragement, future research needs to utilize cross-national longitudinal data to investigate the development of educational expectations in earlier stages of children's educational careers. This way, it would be possible to observe how immigrant expectations gaps develop across countries before tracking even starts (in contexts of between-school tracking), which was not possible to explore with the CILS4EU data. It might also be fruitful to explore the deviation of educational expectations from aspirations as a measure of the discrepancy between students’ wishes and hopes and their experienced realities. Aspirations can also act as compensation for other barriers and difficulties these children face in their educational careers (Jackson, Jonsson, and Rudolphi 2012) and aspirations might be affected differently by the effects of a highly tracked system.

This article faces several limitations, which may guide future research. Given that I studied four countries, I could only account for a small number of cases on the macro level. The investigation of a small sample allows researchers to zoom in on the specific mechanisms that are crucial in explaining expectation differences between countries. However, analyses with large-scale data could enable greater generalizability of the findings and allow researchers to keep other important country-level factors constant.

In this regard, even though education systems should play a decisive role in shaping educational expectations, other contextual characteristics could be influential as well. In particular, the state of the labor market can influence students’ perceptions of lucrative employment options, and anticipated discrimination in the labor market can cause immigrant students to invest more in education (Heath and Brinbaum 2007). Evidence across countries regarding a higher investment in education due to anticipated labor market discrimination among immigrant students is still quite mixed (e.g., Tjaden and Hunkler 2017; Li 2018). This might be due to the varying value of educational credentials in systems where the vocational sector is more developed (Di Stasio and van de Werfhorst 2016). Countries with vocationally oriented education systems, such as Germany, offer better labor market prospects for students who obtain vocational degrees, providing them a reasonable alternative to the university route (Shavit and Müller 2000). In systems where the vocational orientation is less strong (such as England and Sweden), and where vocational degrees are less valued, investment in higher educational routes is more prevalent (Di Stasio, Thijs, and Van de Werfhorst 2016). To disentangle school system effects like ability tracking from labor market signaling effects, future research could study occupational aspirations and the interplay between degree value and anticipated discrimination in countries with more and less tracking.

Finally, the findings from this study indicate some blind spots in the current conceptions of tracking which need to be addressed in future research. For example, even though the Dutch education system is more tracked than the English and Swedish systems, the separation into academic and vocational tracks comes along with a less rigid sorting, resulting in greater possibilities for upstreaming. In fact, in many countries, immigrant students are more likely than ethnic majority students to use second-chance options to gain university eligibility by taking a longer vocational route (Crul, Schneider, and Lelie 2012; Baysu, Alanya, and de Valk 2018). As already laid out by previous research (Blossfeld et al. 2016), such additional characteristics must be considered in order to assess the classification of tracking regimes in a more nuanced way, and thereby enhance our understanding of the effects of tracking on educational inequalities.

Supplemental Material

sj-docx-1-mrx-10.1177_01979183221149917 - Supplemental material for Educational Expectation Gaps Between Second-Generation Immigrant and Ethnic Majority Students in a Comparative Perspective: The Moderating Role of Educational Tracking

Supplemental material, sj-docx-1-mrx-10.1177_01979183221149917 for Educational Expectation Gaps Between Second-Generation Immigrant and Ethnic Majority Students in a Comparative Perspective: The Moderating Role of Educational Tracking by Katja Pomianowicz in International Migration Review

Footnotes

Acknowledgements

I want to thank the editor and the reviewers for their very helpful comments and support, which greatly improved the article. Moreover, I am very grateful for the feedback I received from Kathrin Leuze, Janna Teltemann, Bentley Schieckoff, Frank van Tubergen, Nadja Wehl and Kattalina Berriochoa. Earlier versions of the manuscript have been presented at the Sociology Colloquium, Department of Sociology at the University of Utrecht (Utrecht, 2018); the 2nd Interdisciplinary Workshop for Junior Educational Researchers, hosted by CIDER & LERN (Berlin, 2018); and the conference “Immigrants' Integration: Educational Opportunities and Life Chances” hosted by the University of Bern (Ascona, 2019). The comments from the audience on these occasions are very much appreciated. The CILS4EU research project is funded by the NORFACE ERA NET Plus Migration in Europe-Programme.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Katja Pomianowicz

Supplemental material

Supplemental material for this article is available online.

Notes

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